Download Chemically prepared magnetic nanoparticles

Chemically prepared magnetic nanoparticles
Published by Maney Publishing (c) IOM Communications Ltd
M. A. Willard*1, L. K. Kurihara1, E. E. Carpenter2, S. Calvin3 and V. G. Harris4
Nanotechnology has spurred efforts to design and produce nanoscale components for
incorporation into devices. Magnetic nanoparticles are an important class of functional materials,
possessing unique magnetic properties due to their reduced size (below 100 nm) with potential
for use in devices with reduced dimensions. Recent advances in processing by chemical
synthesis and the characterisation of magnetic nanoparticles are the focus of this review.
Emphasis has been placed on the various solution chemistry techniques used to synthesise
particles, including: precipitation, borohydride reduction, hydrothermal, reverse micelles, polyol,
sol–gel, thermolysis, photolysis, sonolysis, multisynthesis processing and electrochemical
techniques. The challenges and methods for examining the structural, morphological, and
magnetic properties of these materials are described.
Keywords: Chemical synthesis, Magnetic nanoparticles, Superparamagnetism, Reverse micelles, Hydrothermal processing, Precipitation reaction,
Thermolysis, Sonochemistry, Polyol chemistry, Electrodeposition, Hydride reduction, Magnetic characterisation, Ferrofluids
IMR/420
Introduction
Interest in nanoparticle science and technology has
experienced resurgence internationally over the past 10
years largely spurred by the Presidential Nanoscience
Initiative sponsored by both the Clinton and Bush
administrations and their increased utility in a broad
range of application.
Nanoparticles are typically defined as solids less than
100 nm in all three dimensions. Most often they are
particles made to be spherical having diameters on the
order of 10 nm or less. At these length scales, a large
fraction of the atoms of the particle are at or near the
surface providing them with unique properties. In the
case of magnetic nanoparticles, crystal symmetry breaking at the surface has profound ramifications. For
example, in metallic alloys the surface atoms oxidise
quickly forming oxides that are typically ferrimagnetic
or, in some cases, antiferromagnetic. If the metallic alloy
is not prone to oxidation, then there typically exists a
magnetic ‘dead’ layer at the surface of the particle.
Atoms in the dead layer do not have enough magnetic
neighbours in their first and second coordination sphere
to support long-range ferromagnetism. Alternatively,
the surfaces of magnetic oxide particles often experience
bond bending through surface relaxation. The magnetism in oxide systems stems from double-exchange and/or
superexchange interactions, both of which are very
sensitive to the bond angles that form between cation–
anion–cation arrangements. Surface bond bending in
these cases leads to profound changes in the magnetic
1
Naval Research Laboratory, Materials Science and Technology Division,
Washington, DC 20375, USA
Virginia Commonwealth University, Chemistry Department, Richmond,
VA 23284, USA
3
Sarah Lawrence College, Physics Department, Bronxville, NY 10708,
USA
4
Northeastern University, Department of Electrical and Computer
Engineering, Boston, MA 02115, USA
2
*Corresponding author, email [email protected]
ß 2004 IoM Communications Ltd and ASM International
Published by Maney for the Institute of Materials, Minerals and Mining
and ASM International
DOI 10.1179/095066004225021882
interactions, in some instances changing the behaviour
from ferromagnetism to antiferromagnetism or to a
spin-glass like behaviour. This surface relaxation has
been linked to surface spin canting and spin disorder1
that cause anomalously large magnetic anisotropy that
requires very large fields to attain magnetic saturation.
In order to design magnetic nanoparticles for specific
applications, one is challenged by the need to understand the atomic structure of the particle, surface
structure and its magnetic structure or spin dynamics.
Specifically, for metallic nanoparticles this includes
understanding atomic symmetry and chemistry of the
interior atoms and surface atoms, as well as the dynamics of both interior and surface spins. In addition, for
the case of oxide nanoparticles the surface energy and
synthesis methodology may also lead to the stabilisation
of defects. All of these issues become more difficult to
ascertain as the particle diameter is reduced, whereupon
traditional characterisation tools such as X-ray diffraction and electron microscopy have limited utility.
The goal of the present work is to provide a broad
review of the magnetic nanoparticle research that has
been carried out during the past decade. The focus is
on chemical synthesis methods for producing magnetic
nanoparticles, methods of effectively characterising said
particles, and finally a review of the magnetic nature of
these nanoparticles.
Applications
Magnetic nanoparticles have a wide range of uses in
many diverse applications. These applications make use
of magnetic nanoparticles in a variety of forms, e.g. in
solution as ferrofluids for audio speakers; as surface
functionalised particles for biosensing applications;2 as
particle arrays in magnetic storage media;3 as powder
compacts for power generation, conditioning and
conversion; in medical applications including magnetic
targeted drug delivery; contrasting agents in magnetic
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Willard et al.
Chemically prepared magnetic nanoparticles
resonance imaging; and alternatives to radioactive
materials as tracers.
Ferrofluids
Published by Maney Publishing (c) IOM Communications Ltd
A ferrofluid consists of surfactant coated magnetic
nanoparticles in a liquid host that forms a stable
colloidal suspension. A typical ferrofluid has only
5 vol.-% magnetic particles, 10 vol.-% surfactant, and
the balance is the carrier liquid. The particles are coated
with a surfactant that disperses the particles and prevents agglomeration by overcoming the local magnetic
fields and van der Waals forces that exists between
particles. As a result, when the ferrofluid is not in
the presence of an external magnetic field it has no
net magnetisation. However, when a magnetic field is
applied to the solution, the particles spontaneously
orient with respect to and along the magnetic flux lines.
When the field is removed, the particles again disperse
randomising their orientation and establishing a state
of no net magnetisation. Since the ferrofluid is sensitive
to external fields, the particles can be positioned and
controlled by fields with the forces holding the particles
in place proportional to the applied field strength and
the magnetisation of the particles. These unique properties make ferrofluids useful in seals, bearings, dampers,
stepping motors, loudspeakers, and sensors.4
Magnetic recording media
It has recently been shown that surfactant coated
magnetic nanoparticles can self-assemble into periodic
arrays. The equal spacing of the particles gives them
potential for the next generation magnetic storage
materials as individually addressable bits. One example
of this new material is the array of FePt nanoparticles
created by researchers at IBM.3 In this case, FePt
monodispersed nanoparticles were processed by reduction of platinum acetylacetonate and decomposition
of iron pentacarbonyl in the presence of oleic acid and
oleyl amine stabilisers. The particles self-assemble into
a hexagonal self-assembled monolayer with chemical
ordering of the particles created by annealing. The
crucial properties for media applications is that the
particles be monodispersed with a very tight size distribution of ,10%, a high magnetocrystalline anisotropy,
and small interparticle interactions. IBM is considering
this form of media that may hold 100 times more data
than today’s products.5
Power generation, conversion and conditioning
High frequency (i.e. f .1 MHz) electronic components,
including switch mode power supplies, filters for power
conditioning, and power converters, typically use ferrite
cores. Ferrites are desirable since they are insulating
magnetic oxides with high electrical resistance that
minimises conduction related losses. These cores are
made by compaction of ferrite particles. Typically, these
particles have diameters on the order of micrometres
and are processed using chemical reduction methods
followed by mixing, firing, compaction, and sintering.
Recently, nanoparticle ferrites have been considered
for these applications. Benefits of using nanoparticles
include lower heat treatment temperatures, fewer
processing steps, and, in some instances, improved
performance. Difficulties in the use of nanoparticle
ferrites include understanding cation disorder and the
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role of processing and surfaces. In addition, the
compaction of nanoparticles to near their theoretical
densities is very difficult and remains one of the major
obstacles limiting the wide scale acceptance of nanoparticle ferrites.
Targeted drug delivery
It is well known that chemotherapy is an effective
treatment to fight cancer cells, but since it is delivered as
a full body dose, the side effects of its toxicity are often
severe and devastating to the patient. One proposed use
of magnetic nanoparticles that is particularly exciting
is for targeted drug delivery. In this application, the
magnetic particle is coated with activated carbon and
serves to deliver pharmaceuticals to specific sites. In
practice, the administered drug is absorbed to the
particle and is localised to a specific site in the body
by an external magnet field. The physical force created
by the external magnetic field acts to transport the
particles through the vascular wall, thus positioning and
retaining the drugs in close proximity to the cancer cells.
This allows more concentrated doses of the anticancer
drugs to be delivered to the cancer and keep them on site
for longer periods of time. This targeted drug therapy
was in phase I and II trials as of June 2000.6
Magnetic nanoparticles for targeted drug delivery
must be tailor-made for in vivo applications. In order to
prevent dangerous agglomeration of the particles in the
blood stream, the particles must be of a small size
relative to the dimensions of the capillaries, spherical
in shape, and have a size distribution (i.e. standard
deviation) of less than 15%. In addition, the particles
must have a high magnetic moment and switch their
magnetisation quickly and at low fields.7
In the following sections, the chemical synthesis
methods used in processing monodispersed magnetic
nanoparticles, the characterisation tools that allow one
to determine the structure and phase of the nanoparticles, and finally the magnetic nature of fine particles
are discussed. The scope is mainly limited to from 1990
to the present, but reference is made to other reviews
predating this period where appropriate.
Chemical syntheses
Magnetic nanoparticles, like other types of inorganic
materials, are developed with the expectation of product
uniformity, reliable reproducibility, and property control based on manipulation of processing parameters.
Due to the reduced dimensions of nanoparticles,
however, each of these ordinary expectations is at risk
of misinterpretation and/or inaccurate measurement.
Ultimately, as technological advances require ever
smaller device architectures, individual magnetic nanoparticles will be necessary for incorporation. Presently,
the technological goals and the state of the art processing for magnetic nanoparticles are converging on a
solution to these issues. For technological incorporation
of magnetic nanoparticles into magneto-bio-electronic
devices, the chemical processing control of composition,
microstructure, morphology, and phase of the particles
is necessary. This includes control of particle size, size
distribution, and reduction of agglomeration as product
uniformity issues. Knowledge of the most sensitive
processing parameters to the formation of the preferred
phase and conditions to reduce agglomeration is
Published by Maney Publishing (c) IOM Communications Ltd
Willard et al.
necessary for reliable reproducibility. Finally, control of
the processing conditions is needed for manipulation of
the structural characteristics of the particles allowing
control of the intrinsic magnetic properties. In an ideal
sense, the chemical synthesis is controllable for all of
these conditions without compromise. In practice, however, the design requires compromises to achieve the best
possible set of characteristics. This is a difficult task
requiring both careful process control with subsequent
well thought out and thorough experimentation to
characterise the particles. Chemical synthesis techniques
show great promise for producing the high quality
nanoparticles needed for future applications, as will be
described in the following sections.
The three most common approaches used to produce
magnetic nanoparticles are physical vapour deposition,
mechanical attrition, and chemical routes from solution.
In both the vapour phase and solution routes, the
particles are assembled from individual atoms to
form nanoparticles. Alternatively, mechanical attrition
involves the fracturing of larger coarse-grained materials
to form nanostructures.
In this section, an overview of the chemical synthesis
and processing of nanostructured particles is presented.
Solution chemical routes often provide the best method
for production of nanoparticles due to enhanced
homogeneity from the molecular level design of the
materials and, in many cases, cost effective bulk
quantity production. Solution routes also allow control
of particle size and size distribution, morphology, and
agglomerate size through the individual manipulation
of the parameters that determine nucleation, growth,
and coalescence. Surface modification of the particles
during synthesis or post-synthesis is easily accomplished,
providing additional functionality to the nanoparticles.
The synthesis of particles in a solution occurs by
chemical reactions forming stable nuclei with subsequent particle growth. This phenomenon of precipitation of solids in solution has been well studied.8,9 Upon
the addition of precipitating, reducing, or oxidising
reagents to the solution containing the reactants,
chemical reactions occur and the solution becomes
supersaturated. Supersaturation drives the chemical
system far past the minimum free energy configuration
for the precipitating species in solution. The thermodynamically equilibrated state is restored by condensation of nuclei of the reaction product and controlled by
the kinetics of the nucleation and growth.
Kinetic factors control the dynamics of approach to
the thermodynamic equilibrium of the system in the
growth process.10,11 These factors include reaction rates,
transport rates of reactants, and the removal and
redistribution of matter. The reaction and transport
rates are affected by the temperature, pH and mixing of
the solution, as well as the concentration of reactants,
and the order in which the reagents are added to the
solution. Reaction rates and impurities can influence the
structure and crystallinity of the particle. The particle
morphology is influenced by factors such as supersaturation, colloidal stability, nucleation and growth
rates, recrystallisation, and aging times. Generally,
supersaturation has a dominant role in determining the
morphology of precipitates. At low supersaturation, the
particles are small, with shape depending on crystal
structure, composition, and surface energies. As the level
Chemically prepared magnetic nanoparticles
of supersaturation is increased, larger, dendritic particles
form. Finally, at high supersaturation levels, smaller but
compacted, agglomerated particles form.10
When the nuclei form at nearly the same time in
a supersaturated solution, subsequent growth of these
nuclei results in the formation of particles with a very
narrow size distribution.12 This narrow size distribution
can be maintained as long as agglomeration, Ostwald
ripening, and continued nuclei formation do not occur.
The growth in solution is interface controlled when the
particle is small, after reaching a critical size, it becomes
diffusion controlled.12 The formation of stable colloids
and dispersion of agglomerated particles have been
extensively investigated (e.g. see Ref. 13).
As a result of attractive van der Waals forces, and the
tendency of the system to minimise the total surface or
interfacial energy, nanostructured particles often form
agglomerates. Agglomeration of particles can occur
during any of the following stages: synthesis, drying,
handling and/or post-processing. For applications where
dispersed particles or stabilised dispersions are required,
agglomeration must be prevented at each processing
step. To produce monodispersed particles without
agglomeration, surfactants can be used to control the
dispersion during chemical synthesis. Surfactants can
also be used to disperse as-synthesised agglomerated fine
particles.
A surfactant (an acronym for ‘surface-active agent’) is
any substance that affects the surface or interfacial
tension of the medium in which it is dissolved. As
such, surfactants need not be completely soluble and
may decrease or increase surface tension by spreading
over a surface or interface. Surfactants are used during
nanoparticle synthesis in order to reduce interparticle
interaction through an increase in repulsive forces. They
are used to control particle size and distribution in most
chemical synthesis routes. Capping or stabilising agents
may also be used to help control the particle size and
shape.
For some applications, consolidation of nanoparticles
into bulk solid forms is necessary. Annealing, in many
cases, causes an increase in crystallinity, which in turn
greatly affects the magnetic and electronic properties.14
However, the heat treatment can cause grain growth if
the temperatures are too high or the times are too long.
Excessive grain growth adversely affects the magnetic
and electronic properties (e.g. magnetic domain formation). Microwave heating typically increases crystallinity
with insignificant grain growth. The annealing temperature at which significant grain growth occurs has been
shown to be half the melting point of the material.15 It is
important to note that nanoparticles generally possess
reduced melting temperatures, primarily due to the large
surface/volume ratio.
Figure 1 shows the chemical synthesis techniques used
for the formation of magnetic nanoparticles. Some
techniques are frequently used together or in a series
of reactions, as noted by the cross-hatching between
fields in the figure. For clarity, not all of the combinations found in the literature are shown in the figure.
However, the most frequently used combinations are
delineated. The dotted line indicates the demarcation
between syntheses using organic and those using
aqueous solutions. Generally, sol–gel and hydrothermal
reactions produce oxide nanoparticles due to their
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356
357
358
359
360
361
362
363
319, 339
254
327
25
26
362
364
320
TEM, XRD, ICP, SQUID
TEM, XRD, VSM
TEM, XRD, FTIR, VSM, ACSus
XRD, BET, MS
TEM, XRD, FTIR
SEM, XRD, SAXS, SQUID,
TEM, XRD, EXAFS, BET, ICP
TEM, XRD, ICP, FTIR
TEM, XRD, FTIR
XRD, ND, ICP, MS, SQUID
TEM, XRD, ND, EELS
TEM, XRD, BET, DSC, SQUID
TEM, XRD, magnetic fluxmeter
TEM, XRD, VSM
TEM, XRD, ICP, FTIR
TEM, XRD, SQUID, ACSus
TEM, XRD, SQUID, ACSus
Agglomerates
Needles
Spheres
…
Needles
Needles
Needles
Needles
Platelets
…
Spheres?
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
PPC
PPC and M
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
,200
30–180
20–200
7–48
20–200
10–150
10–450
,400
10–100
5–20
y40
4–15
7–25
5–15
,80
,10
,10
Characterisation{
Morphology
Fe
a-Fe (b-FeOOH)
Fe (Fe3O4)
a-FeOOH
a-FeOOH
a-FeOOH
b-FeOOH
c-FeOOH
d-FeOOH
MgFe2O4
MnFe2O4
MnFe2O4
MnFe2O4
MnFe2O4
Fe3O4
Fe3O4
Fe3O4/surfactant
One of the oldest techniques for the synthesis of nanoparticles is the precipitation of products from solutions.
In precipitation reactions, the metal precursors are
dissolved in a common solvent (such as water) and a
precipitating agent is added to form an insoluble solid.
In most cases, a further reduction step is required, either
in solution after synthesis (such as borohydride reduction) or to the collected precipitate (i.e. heat treatment in
hydrogen gas). Many magnetic nanoparticles can be
synthesised using these classical aqueous precipitation
reactions to yield nanoparticles that have broad size
distribution and irregular morphology. These reactions
can generate a wide range of magnetic materials
including spinel ferrites, perovskites, metals, and alloys.
The major advantage of precipitation reactions is
that large quantities of particles can be synthesised.
However, it is difficult to tailor the particle size as only
kinetic factors are available to control growth. Chelating
agents (i.e. ligands with multiple binding sites) may be
used to help control the particle size, decomposing as the
precursor is heated. The chelate modified precipitation
yields magnetic nanoparticles that often have very well
Size, nm
Precipitation
Method{
production in an aqueous solution without a source of
reduction.
In the following subsections, selected examples of
various chemical routes used to prepare magnetic
nanoparticles are given, highlighting some aspects of
each route. Recently, Hyeon has written an overview
focusing on the chemical synthesis of various magnetic
nanoparticles.16 An extensive overview of the types of
nanoparticles, synthesis techniques used for production,
size of particles, and characterisation techniques is given
in Table 1; which also includes, as footnote, explanations of the acronyms used throughout this review.
Compound*
Published by Maney Publishing (c) IOM Communications Ltd
PPC: precipitation; H: hydrothermal; HR: hydride reduction; M: micellar or microemulsion; T(OM): thermolosis –
organometallic decomposition; T(CO): thermolosis – carbonyl
decomposition; UV: photolysis; S: sonolysis; SG: sol–gel; P:
polyol; EC: electrochemical; ED: electrodeposition; MSP:
multisynthesis processing
1 Schematic diagram showing chemical synthesis techniques for magnetic nanoparticles: crosshatched
regions indicate common combinations of synthesis
techniques (for clarity, not all synthesis combinations
that have been examined appear in diagram )
Ref.
Chemically prepared magnetic nanoparticles
Table 1 Survey of nanoparticle materials produced by various chemical synthesis techniques illustrating wide variety of types of nanoparticles that can be formed by such techniques: data
are arranged by synthesis method used to produce particles and provide composition, size, and morphology information along with techniques used to examine particles, as found in
cited references (see table footnote for acronyms in full)
Willard et al.
Method{
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
PPC
HR
HR
HR
HR
HR
HR
HR
HR
HR
HR
HR
Compound*
Fe3O4, CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
Co12xNixFe2O4
Co12xMxFe2O4 (M5Gd, Pr)
NiFe2O4
NiFe2O4
NiFe2O4
NiFe2O4
NiFe2O4
ZnFe2O4
Mn12xZnxFe2O4
Mn0.66Zn0.34Fe2O4
Ni12xZnxFe2O4
Ni12xZnxFe2O4/a-Fe/a-Fe2O3
Ni0.8Zn0.2Fe2O4
Ni0.5Zn0.5Fe2O4
a-Fe2O3/c-Fe2O3
c-Fe2O3
c-Fe2O3
c-Fe2O3
c-Fe2O3
c-Fe2O3
LiFe5O8
SrFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
(Fe,Ni,Cu)
Fe, c-Fe2O3
Co
Co
Co
CoB2, CoFe2O4, Fe3O4, c-Fe2O3
Ni
Ni
CoPt (L10)
(Fe,Zr,B) (Fe3B) (ZrO2)
(M,B) (M5Fe, Co, Ni, Mn)
3–15
7–12
5–20
5–130
600–1000
,30
6–87
4–15
50–200
4–6
3–5
700–900
,100
3–20
y9
10–20
y20
14–1000
y9
20–50
4–12
2–9
6–12
2–15
,100
y10
35–40
250–1000
100–500
100–3000
10–50
10–500
400–3000
10–3000
10–200
y40
20–100
,40
3–8
2–5
25–30
2–5
20–25
5–15
7–12
Size, nm
Spheres, self-assembled (SA)
Spheres
Spheres
Spheres, needles
Spheres
…
…
…
Spheres
…
Spheres
Spheres
Spheres
…
…
Spheres
Spheres
Spheres, agglomerates
…
Spheres
…
Spheres
Spheres
Spheres
Platelets, rods
…
Spheres
…
Hexagonal platelets, agglomerates
Hexagonal platelets, agglomerates
…
Hexagonal platelets, agglomerates
Hexagonal platelets
Platelets
Spheres
Wires
Spheres
Agglomerates
Spheres, SA
Spheres
…
Spheres
Spheres
…
…
Morphology
TEM, XRD, XPS, SQUID
TEM, VSM
TEM, XRD, magnetic fluxmeter
TEM, XRD, VSM
TEM, XRD, XPS, FTIR, AA, magnetic susceptibility
TEM, XRD, VSM
XRD, TGA, VSM
XRD, VSM, MS
SEM, XRD, TGA, BET
XRD, SQUID
TEM, XRD, magnetic birefringence
TEM, UVvis, Zeta potential, VSM?
SEM, XRD, TGA
TEM, XRD, TGA, FTIR, ESR, SANS, VSM
TEM, XRD, AA, FMR, VSM
TEM, XRD, AA, FTIR, VSM
TEM, SEM, XRD, MS, VSM
SEM, XRD, VSM
TEM, XRD, AA, FMR, VSM
SEM, XRD
XRD, ND, SANS, FMR
TEM, XRD
TEM, VSM
TEM, XRD, AA, DLS, SQUID
TEM, XRD, XPS, MS
XRD, FTIR, VSM
TEM, XRD, TGA, DTA, SQUID
SEM, XRD, TGA, DTA, XPS
SEM, XRD, MS
SEM, XRD, DTA, VSM
TEM, XRD, MS, VSM
HRTEM, TEM, XRD, TGA, DTA, Raman, VSM
SEM, XRD, TGA, DTA, VSM
TEM, XRD, TGA, VSM
TEM, XRD, TMA
TEM, HRTEM, SEM, XRD, VSM, MS
TEM, XRD, ICP
TEM, XRD, ICP, DSC, BET, SQUID
TEM, XRD, SAXS, SQUID
TEM, XANES, SAXS
XRD, ICP
TEM, XRD, UVVis
TEM, XRD, ICP, EDX, VSM, SQUID
SEM, XRD, EDX, EXAFS, AA, FTIR, DSC, MS, SQUID
XRD, MS, ACSus
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
365
24
25
26
366
367
368
369
370
371
372
373
374
28, 375
348
29
376
377
348
378
350
379
24
380
381
382
383
384
351
385
20
386
387
388
38
389
390
32
391
56
34
392
393
394
35
Ref.
continued…
Willard et al.
Chemically prepared magnetic nanoparticles
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Method{
HR
HR
HR
HR
HR
HR
HR
HR
HR
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
H
M
M
M
M
M
M
M
Compound*
(Fe,Ni,B)
(Fe,B) amorphous
Fe802xCrxB20
Fe802xCrxB20 amorphous
(Co,B) amorphous
e-Co
e-Co
e-Co
e-Co
MnFe2O4
MnFe2O4
Fe3O4
Fe3O4
Fe3O4
Fe3O4
CoFe2O4
CoFe2O4
NiFe2O4
NiFe2O4
MFe2O4 (M5Cu, Ni, Zn)
ZnFe2O4
ZnFe2O4
Mn12xZnxFe2O4
Mn12xZnxFe2O4
Mn12xZnxFe2O4/a-Fe2O3
Ni12xZnxFe2O4
SrFe12O19
SrFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19
BaFe12O19/Ba5Fe8O17
REFeO3/RE3Fe5O12 (RE5Er–Lu)
a-Fe
Fe
Fe
Fe
a-Fe
a-Fe
a-Fe (b-FeOOH)
,50
50–150
20–200
3–200
y40
y5
y11
7–10
y5
y25
y540
y340
30–200
50–150
12–59
y400
5–25
20–100
y680
3–10
y300
20–80
5–200
10–17
,12
40–70
50–2000
8–30
100–1900
50–800
200–1000
150–1500
150–10000
40–700
100–200
,1000
,80
10–100
2–15
5–150
,5
50–150
20–1000
10–200
Size, nm
Agglomerates
Spheres
Spheres
Spheres, agglomerates
Spheres
Spheres, SA
Spheres, SA
Spheres, SA
Spheres, SA
…
Spheres, polyhedra
Polyhedra
Polyhedra
Spheres
…
Spheres, polyhedra
Spheres
Polyhedra
Polyhedra
…
Polyhedral
Polyhedra
Spheres, polyhedra
…
Spheres, large a polyhedra
Spheres
Hexagonal platelets
Spheres
Hexagonal platelets
Hexagonal platelets
Hexagonal platelets
Hexagonal platelets
Hexagonal platelets, needles
Hexagonal platelets
Hexagonal platelets
Polyhedra, spheres
Spheres
Spheres
Spheres
Needles
Spheres
Spheres
Spheres, needles
Polyhedra, spheres, needles
Morphology
Table 1 Survey of nanoparticle materials produced by various chemical synthesis techniques (continued)
TEM, MS
TEM, DSC, BET, ICP, MS
TEM, XRD, TGA, MS, SQUID
TEM, XRD, MS, SQUID
TEM, XRD, XPS, ICP, MS
SEM, TEM, XRD, SQUID
HRTEM, XRD
HRTEM, XRD, SQUID
TEM, XRD
XRD, FB
TEM, MS, SQUID
TEM, MS, SQUID
TEM, XRD, AA
SEM, XRD, BET
TEM, XRD, FTIR, TGA, VSM
TEM, MS, SQUID
TEM, XRD, TGA, EDAX, SQUID
TEM, XRD, AA
TEM, MS, SQUID
XRD, VSM
SEM, XRD, EDAX, VSM
TEM, XRD, AA
TEM, SEM, XRD, AA, DTA, TGA, AES, FB
XRD, ICP
TEM, XRD, VSM
SEM, XRD, VSM
SEM, XRD, AA, VSM
TEM, XRD, DTA, EPR
SEM, XRD
SEM, XRD, VSM
SEM, XRD
SEM, XRD, BET, VSM
TEM, SEM, XRD, DLS, DTA, TGA, VSM
TEM, XRD
TEM, XRD
TEM, XRD, VSM?
TEM, XRD
TEM, XRD, EELS, AGM, MS
HRTEM, SAD
TEM, XRD, SAD, VSM
TEM, XRD, optical absorption, VSM, SQUID
TEM, XRD, VSM?
TEM, XRD, VSM
TEM
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
36
395
396
397, 398
399
40
41
345
39
400
401
401
402
46
403
401
404
402
401
405
47
402
48
406
407
408
49
409
410
51
411
412
50
413–415
52
44
45
62
63
355
416
417
418, 419
420
Ref.
Willard et al.
Chemically prepared magnetic nanoparticles
International Materials Reviews
2004
VOL
49
NO
3–4
Method{
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
M
Compound*
Fe/FeB
Co
Co
Co
b-Co
Co
b-Co
Co/Au (core/shell)
Ni
(Fe,Cu)
FePt3
(Fe,Cu,B)
Co2B
FeOOH
MgFe2O4, CoFe2O4
MnFe2O4
MnFe2O4
Fe3O4
Fe3O4
Fe3O4
Fe3O4
Fe3O4
Fe3O4 (a-FeOOH)
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoFe2O4
CoxFe32xO4
Co12xRExFe2O4 (RE5Ce–Er)
Zn12xFe2zxO4
Zn12xFe2zxO4
Mn12xZnxFe2O4
Mn12xZnxFe2O4
Co12xZnxFe2O4
Ni12xZnxFe2O4
c-Fe2O3
c-Fe2O3
c-Fe2O3/Fe3O4
SrFe12O19
SrFe12O19
SrFe12O19
,3
,10
5–110
5–10
2–10
5–12
,5
5–25
2–16
5–50
8–10
5–30
2–20
,80
10–30
5–10
3–10
3–15
3–10
3–12
3–12
5–20
8–100
,15
3–10
10–18
2–8
2–15
2–8
5–35
5–20
6–11
17–23
2–6
2–50
25–130
3–1000
,7
20–150
3–12
4–20
2–14
9–120
65–1000
3–100
Size, nm
…
Spheres
Spheres
Spheres, SA
Spheres
Spheres, SA
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Needles
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
…
Spheres, needles
…
Spheres
Spheres
Spheres
Spheres
…
Spheres
Spheres
Spheres
…
Spheres
Spheres
Spheres
Agglomerates
Spheres
Spheres
Spheres
Spheres
Spheres
Hexagonal platelets
Hexagonal platelets, agglomerates
…
Morphology
TEM, XPS, BET, MS
TEM, XRD, SQUID
TEM, Conductivity, AGM
SEM, SQUID
TEM, STM, XRD, SAXS, SQUID
TEM, SEM, SQUID
TEM, XRD, SQUID
TEM, AFM, UVvis
TEM, XRD, SQUID
TEM, XRD, EDS, Conductivity, EELS, AGM, MS, SQUID
TEM, XRD, SQUID
TEM, SEM, XRD, EDS, EELS, MS, AGM, SQUID
TEM, SAD, UVvis, AGM
SEM, XRD, UVvis, Conductivity
TEM, ND, MS, SQUID
TEM, XRD, ND, ICP, MS, SQUID
TEM, XRD, SQUID
TEM, DSC, TGA, SANS, SQUID
TEM, XRD, SQUID
TEM, XRD, AGM, MS, VSM
TEM, XRD, VSM
TEM, XRD, AA, DLS, SQUID
TEM, XRD, BET, DSC, VSM
TEM, XRD, ND, ICP, SQUID
TEM, XRD, SQUID
TEM, XRD, EXAFS, SQUID
TEM, XRD, XANES, SAXS, Conductivity, MS, AGM, SQUID
TEM, XRD, EDS, MS, SQUID
TEM, XRD, SAXS, EDS, SQUID
TEM, XRD, ND, ICP, MS, SQUID
TEM, XRD, VSM
TEM, XRD, SAD, MS
XRD, SQUID
TEM, EDS, MS, SQUID
TEM, XRD, DLS, BET, ICP, SQUID
TEM, XRD, BET, PCS
SEM, XRD, BET, DTA, TGA
TEM, SAD, EDS, AGM, FMR, SQUID
TEM, XRD, BET, PCS
TEM, XRD, AGM, MS, VSM
TEM, SEM, XRD, MS, SQUID
TEM, XRD, VSM
TEM, XRD, BET, DTA, TGA, VSM
TEM, XRD, BET, DTA, TGA, FTIR, MS, VSM
TEM, XRD, DTA, TGA, SQUID
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
International Materials Reviews
2004
VOL
49
NO
continued…
421
34, 422
64
423, 424
425–427
428
317
429
249
430
431
432, 433
434
60
71
435
318
435
318
436
437
438
439
70
318
440
352, 441–443
444, 445
446
253, 447
448
449
450
451
452
65
453
454, 455
65
436
456
457
21
73
458
Ref.
Willard et al.
Chemically prepared magnetic nanoparticles
3–4
131
132
International Materials Reviews
2004
VOL
49
NO
3–4
S
S
S
S
S
S
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(OM)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
T(CO)
UV
S
S
M
M
M
M
M
T(OM)
T(OM)
BaFe12O19
BaFe12O19
Co[Fe(CN)5NO]
Cr3[Cr(CN)6]2 H2O
Co4[Fe(CN)6]4
Co/PVP
Co
Ni/PVP
Ni/PVP
Ni
Ni
CoPt, CoPt3, Co/Pt (core/shell)
CoxPt12x/PVP
CoO, Co3O4/PVP
c-Fe2O3
CoFe2O4
SrFe122xO1921.5x
Fe
Fe/TOPO
Fe/polymer (core/shell)
Fe, c-Fe2O3
Co, CoO
Co
Co
Co
Co, e-Co
Co, e-Co
Co/PS
Co/HPS
e-Co/TOPO
e-Co/TOPO
MnO
b-Fe2O3, c-FeOOH
Fe
Fe/PPO
Fe/SiO2
(Fe,Co)
Fe/Thiol
Fe/PVP
Fe amorphous
Fe, Co, (Fe,Co)
Co
Co
Method{
Compound*
3–15
5–100
22–31
15–200
12–22
,2
3–5
17610
,5
,5
4615
10–15
,10
1–5
5–12
6–7
4–9
200–500
5–8
2–11
,100
10–15
4–5
50–100
5–12
y12
3–17
8–12
5–30
2–15
4–25
15–25
5–10
y30
2–15
1–12
3–8
10–20
3–25
3–8
,30
2–20
5–10
30–200
Size, nm
SA monolayers
Spheres
Spheres
Spheres
Spheres
Platelets
…
Spheres
Polyhedra
Polyhedra
Polyhedra
Spheres
Spheres, SA
rods
Spheres, SA
Spheres, SA
Rods
Rods
Spheres
Spheres
Spheres
Spheres
Spheres, SA
…
Spheres
Needles
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres, rods, cubes, SA
Spheres, discs
Agglomerates
Spheres
Spheres, rods, SA
Spheres, polyhedra
Spheres
Spheres
Chains
Spheres
Agglomerates
Morphology
Table 1 Survey of nanoparticle materials produced by various chemical synthesis techniques (continued)
AES, XRD, XANES, XPS, DSC, TGA, FTIR, MS
TEM, SQUID
TEM, XRD, TGA, DSC, SQUID
TEM, XRD, DSC
TEM, FTIR, SQUID
TEM, SAD, Lorentz microscopy
TEM, EELS, FTIR, EDS
HRTEM, WAXS, SQUID
TEM, SQUID
TEM, SQUID
TEM, SQUID
TEM, FTIR, WAXS, SQUID
TEM, HRTEM, WAXS, SQUID
TEM, XRD
TEM, XRD, SQUID
XRD, DTA, TGA, FTIR, FB
TEM, SQUID
TEM, SQUID
TEM, DSC, ICP, FTIR, NMR, SQUID
TEM, XRD
TEM, EELS
TEM, SQUID
TEM
TEM, SQUID, FMR
TEM, XRD, EELS, HRTEM
TEM, XRD, HRTEM, SQUID
TEM, FTIR
TEM, XRF, FMR
TEM, XRD
TEM, XRD
TEM, XRD, SQUID
TEM, XRD, XPS, FTIR
STM, ESR
HRTEM, SQUID
TEM, XRD, DSC, TPD, TPR
TEM, XRD, VSM
TEM, XRD, DTA, TGA, VSM
TEM, FTIR
TEM, FTIR
TEM, FTIR
TEM, HRTEM, SQUID
HRTEM, WAXS, SQUID
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
105, 106, 111
101
99, 467
100
468
108
460
85
92
93
96
88
75
91
98
461
95
82
322
97
80
94
462
463
78, 79
89
83
81
77
76
464
465
198
466
102
66
459
66
66
66
74
93
Ref.
Willard et al.
Chemically prepared magnetic nanoparticles
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
SG
P
P
P
P
P
5–20
5–30
40–50
100–200
20–60
50–3300
9–50
100–250
10–100
80–400
10–25
80–85
5–500
30–60
30–4520
5–50
5–250
y1200
25–150
1–500
10–90
6–30
SG
SG
SG
SG
SG
SG
SG
5–20
10–50
,10
,25
,10
12–20
,20
20–80
7–11617–21
5–30
,25
5–25
2–10
,10
1–5
5–15 c
2–100 s
10–50
10–50
5–20
10–80
11–30
S
S
S
S
S
S
S
S
S
S
S
S
SG
SG
SG
SG
Ni
Ni/SiO2
(Fe,Co)
(Fe,Ni)
(Co,Ni)
Fe3O4/PVA
Fe3O4
Fe3O4
Fe3O4, c-Fe2O3
Co3O4, Fe3O4
NiFe2O4
Fe2O3/UDA/OPA/DSA/OTS
M12xPx (M5Fe,Co,Ni)
Fe/SiO2
(Ni/Pd)/PVP
Fe2O3/SiO2
Fe3O4/SiO2
CoFe2O4
Co0.9Mn0.1Fe2O4
Co12xCrxFe2O4
CoBi0.1Fe1.9O4
CoGd0.1Fe1.9O4
CoNd0.1Fe1.9O4
Co12xZnxFe2O4
CoY0.1Fe1.9O4
CoLa0.1Fe1.9O4
NiFe2O4/SiO2
NiFe2O4
Ni0.25Cu0.25Zn0.5Fe2O4
Ni0.5Zn0.5Fe2O4/Mg2SiO4
a-Fe2O3
a-Fe2O3
Fe2O3/SiO2
BaFe12O19
Ba4Co2Fe36O60
BaFe12O19
BaFe12O19
Ba12xSrxFe12O19
BaZnCoFe16O27
La0.67Ca0.33MnO3
Y3Fe3O12
Fe, Ni, Co, (Fe,Co), (Fe,Cu), (Co,Cu)
Fe, (Fe,Co), (Fe,Ni), (Co,Ni,Fe)
Co
Co
Co/Mica
Size, nm
Method{
Compound*
Agglomerates
Spheres?
Agglomerates
Agglomerates
Spindles, spheres
Spheres, platelets
Agglomerates
Polyhedra
Spheres, cubes
Hexagonal platelets
Platelets
Hexagonal platelets
Spheres
Agglomerates
Agglomerates
Spheres
Spheres
Agglomerates
…
Agglomerates
Agglomerates
…
…
…
Spheres
…
…
Spheres
Spheres
Spheres
Agglomerates
SA monolayers
Spheres
Spheres
Rods
Needles
Polyhedra
Agglomerates
Spheres
Hexagonal platelets
Agglomerates
Spheres
Spheres
Morphology
XRD, TGA, FTIR, ESR, MS, VSM
TEM, XRD, DTA, BET, SQUID
TEM, XRD, DTA, FTIR, ACPerm
SEM, XRD, ACPerm
TEM, XRD, SAXS
TEM, SEM, XRD, ICP, EDX, FTIR, UVvis
TEM, ESR, BET
TEM, XRD, VSM
TEM, XRD, XPS, BET, VSM
TEM, XRD, VSM
TEM, XRD, TGA, DTA, SQUID, VSM
SEM, XRD, MS, VSM
TEM, XRD, VSM
TEM, XRD, TGA, XPS, FTIR, VSM
TEM, SEM, XRD, VSM, SQUID
TEM, SEM, XRD
SEM, XRD, VSM
SEM, XRD, FMR
TEM, XRD, CHN, SQUID
SEM, XRD, UVvis, IR
SEM, XRD, MS, VSM
XRD, MS, VSM
XRD, MS, VSM
TEM, XRD, MS, VSM
TEM, XRD, ICP, VSM
AFM, XRD, RBS, TGA, MS, VSM
XRD, MS, VSM
TEM, XRD, TGA, DSC, SQUID
TEM, AFM
TEM, SANS, DSC
TEM, XRD, TGA, DSC, BET, MS, SQUID
TEM, SEM, XRD, TGA, BET, VSM
TEM, AFM, XRD, DSC, TGA, MS, SQUID
TEM, XRD, TGA, MS, SQUID
TEM, XRD, TGA, CHN, MS, VSM
TEM, SEM, XRD, MS, VSM
TEM, XRD, DRS, BET
TEM, XRD, BET, ESR, TGA, DSC
TEM, XRD, FTIR, EPR, TGA, MS, SQUID, VSM
TEM, XRD
TEM, XRD, MS, VSM
HRTEM, XRD, XPS, VSM
TEM, Fluorescent microscopy
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
International Materials Reviews
2004
VOL
49
NO
continued…
136
122
471
472
473
474
135
475
131
476
477
129
130
133
132
149, 158
141
166
171
163
128
126
121
123
124
125
127
109
107
103
104
110
114
116
119
118
115
112
113, 117
469
134
108
470
Ref.
Willard et al.
Chemically prepared magnetic nanoparticles
3–4
133
134
Method{
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
P
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
ED
Compound*
Co, Pt, CoPt, CoPt3
Co/Ni/LDH
Co, Ni, (Co,Ni)/PVP
Co, (Co,Ni), (Co,Ni,Fe)
Ni, Co
Ni/montmorillonite
Ni/PVP
(Fe,Co)
(Ni,Co)
(Ni,Co)
(Ni,Co)
(Ni,Co)
(Ni,Co)
(Ni,Co)
(Ni,Co)
(Fe,Ni)
(Ni,Co), (Fe,Ni)
(Ni,Co), (Fe,Ni,Co)
(Ni,Co), (Fe,Ni,Co)
(Ni,Co), (Fe,Ni,Co)
(Ni,Co), (Fe,Ni,Co)
(Ni,Pd)/PVP
(Co,Cu)
Co2FeO4
a-Fe2O3
c-Fe2O3
c-Fe2O3, a-Fe2O3
Fe2O3, CoO
Co
Co
Co
Co, (Co,Fe)
Ni
Ni
Ni
Ni
Ni, Co
Ni, Co
Ni
Ni
Ni, (Pd,Fe)
Fe26Ni74
Cu/Co, Fe20Ni80, Co
CoPt, FePt
CoPt
International Materials Reviews
2004
VOL
49
200–500
25–2000
20–40
25–250
25–3000
35–65
20–30
4–8
50–100
2–8
80–100
30–300
3–5
y200
40–50
18–78
y6
1–20
25–30
50–100
18–500
35–500
,70
20–600
,40
y18
5–10
25–100
40–60
1–3
5–20
100–600
30–1000
20–500
8–45
5–2000
y20
200–700
200–2000
150–700
210–260
60–500
25–600
200–500
Size, nm
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Templated
Templated
Nanowires
Templated
Templated
Wires
Wires
Spheres
Templated
Templated
Templated
Spheres
…
Templated
Wires
Wires
Wires
NO
3–4
nanowires
nanowires
nanowires
nanowires
nanowires
nanowires
nanowires
nanowires
Spheres
Turbostratic aggregate
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Spheres
Morphology
Table 1 Survey of nanoparticle materials produced by various chemical synthesis techniques (continued)
TEM, XRD
TEM, XRD, TGA, DTA, FTIR, UV-NIR
SEM, XRD, TGA, VSM
SEM, XRD, EDS. FMR, ACPerm
TEM, XRD
HRTEM, XRD, VSM
SEM, XRD, FTIR, TPD
TEM, XRD, EELS, ACPerm
SEM, XRD, TGA
SEM, XRD, VSM, Permeability
SEM, XRD, TGA
TEM, SEM, XRD, EDS, Microwave permeability
TEM, XRD
SEM, XRD, WAXS, VSM
SEM, XRD, WAXS, VSM
XRD, TGA, FTIR, VSM
TEM, XRD
TEM, SEM, ACPerm
TEM, SEM, SQUID, ACPerm
TEM, FMR, ACPerm
SEM, XRD, XRF, TGA, GPC, TPD/MS, SQUID, ACPerm
TEM, XRD, XPS, TGA
TEM, XRD, NMR, EXAFS, VSM
TEM, XRD, XANES, MS, DCSus
SEM, XRD, FTIR
TEM, XRD, FTIR
SEM, XRD, DRS
SEM, XRD
TEM, HRTEM, VSM
SEM, XRD, CV, VSM
TEM, FMR, SQUID
HRTEM, TEM, XRD, VSM
TEM
TEM
TEM, SQUID
SEM
TEM, SEM, SQUID, VSM
MFM, SQUID
TEM, Conductivity
SEM, TEM, CV
XRD, cc angluar spectroscopy
TEM, SEM, XRD, VSM
TEM, STEM, XRD, EELS, EDAX
TEM, XRD, VSM
SEM, XRD, VSM
Characterisation{
Published by Maney Publishing (c) IOM Communications Ltd
160
165
152
143
169
161
151
150
156
139,
157
144
148
167
478
479
142
145
146
147
164
480
137,
159
481
173
153,
154
177
178
201
184
186
202
203
196
179,
182
180
194
190
176
200
183
482
Ref.
185
155
138
140
Willard et al.
Chemically prepared magnetic nanoparticles
ED
ED
ED
EC
EC
EC
EC
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
MSP
Fe, Fe2O3, Fe3O4
Fe2O3, NiO, Co3O4, CoFe2O4
SrFewOz
Fe, Ni, (Co,Ni)
a-Fe, c-Fe2O3, Fe3O4
MnxZnyFezOw
c-Fe2O3
a-Fe, Co, Ni, FePt
e-Co, hcp Co, mt-fcc Co
(Fe,Pt)
FePt
FePt/Fe3O4
FePt (L10)
FePt (L10)
FePt (L10)
FePt (L10)
FePt (L10)
FePt (L10)
FePt (L10)
FePt/Pt–Fe2O3
Pt–Fe2O3
CoPt3/ACA
FePd, CoPt, (Fe,Co)Pt (L10)
(Fe49Pt51)88Ag12 (L10)
Mn52.5Pt47.5
(Sm,Co), (Nd,Fe)
Fe3O4
4–12
2–30
2–50
10–10000
9–55
20–2000
1–25
6–10
2–10
2–5
2–50
2–10
3–6
3–10
2–8
2–6
1–4
2–5
3–5
8–12
y10
1–50
2–11
2–5
y3
y9
3–20
Size, nm
Wires
…
Agglomerates
Agglomerates
…
…
Agglomerates
Spheres, SA
Spheres, SA
Spheres, SA
Spheres, triangular platelets
Spheres, SA
Spheres, SA
Spheres, SA
Spheres, SA
Spheres
Spheres, SA
Spheres, SA
Spheres
Spheres
Spheres
Spheres, Wires
Spheres, SA
Spheres
Spheres
Clusters
Spheres, SA
Morphology
TEM, VSM, SQUID
TEM, XRD, DLS, BET
SEM, XRD, ICP, SQUID
TEM, SEM, XRD, XRF, MS, SQUID
XRD, MS
SEM, XRD, ICP–MS, SQUID
TEM, XRD, FTIR, BET, Raman, MS, SQUID
HRTEM, WAXS, VSM, SQUID
HREM, WAXS, SAXS, XRD, SQUID
TEM, PEELS, ICP, RBS, SQUID
TEM, SEM, XRD
HRTEM, XRD, VSM, SQUID
HRTEM, XRD, SQUID
HRTEM, EXAFS, SQUID
TEM, SQUID
TEM, XRD, RBS, XPS, MS
TEM, VSM, SQUID
TEM
TEM, XPS, MS, VSM
TEM, XPS
TEM, XRD, XPS
HRTEM, TEM, SEM, XRD, ICP, AES
TEM, SEM, XRD, AGM, VSM
TEM, XRD, VSM
TEM, XRD, XRF, SQUID
TEM, SQUID
TEM, XRD
Characterisation{
483
189
192
195
249
193
191
211
206
3, 207
218
214
208, 213, 344
215
216
484
209
210
212
223
222
221
217, 220
485
219
204
486
Ref.
*ACA: 1-adamentanecarboxylic acid; DSA: dodecylsulphonic acid; HPS: hyper-cross-linked polystyrene; LDH: layered double hydride; mt-fcc: multi-twinned face centred cubic; OPA: octylphosphonic
acid; OTS: octadecyltrichlorosilane; PPO: poly(dimethylphenylene oxide); PS: polystyrene; PVA: polyvinyl alcohol; PVP: polyvinylpyrrolidone; RE: rare earth; SDS: sodium dodecylsulphate; TOPO:
trioctylphospheneoxide; UDA: 10-undecanoic acid.
{EC: electrochemical; ED: electrodeposition; H: hydrothermal; HR: hydride reduction; PPC: precipitation; M: micellar or microemulsion; MSP: multisynthesis processing; P: polyol; S: sonolysis; SG: sol–gel;
T(CO): thermolosis – carbonyl decomposition; T(OM): thermolosis – organometallic; UV: photolysis.
{AA: atomic absorption spectroscopy; ACPerm: alternating current permeametry; ACSus: alternating current susceptometry; AES: Auger electron spectroscopy; AFM: atomic force microscopy; AGM:
alternating gradient magnetometry; BET: Brunauer–Emmett–Teller (a method of measuring surface area); CHN: carbon–hydrogen–nitrogen analysis; CV: cyclic voltammery; DLS: dynamic light scattering;
DRS: diffuse reflectance spectroscopy; DSC: differential scanning calorimetry; DCSus: direct current susceptometry; DTA: differential thermal analysis; EDAX: energy dispersive analysis of X-rays; EDX/
EDS: energy dispersive X-ray spectroscopy; EELS: electron energy loss spectroscopy; EPR: electron paramagnetic resonance; ESR: electron spin resonance; EXAFS: X-ray absorption fine structure
(spectroscopy); FB: Faraday balance; FMR: ferromagnetic resonance; FTIR: Fourier transform infrared spectroscopy; GPC: gas phase chromatography; HRTEM: high resolution transmission electron
microscopy; ICP: inductively coupled plasma; IR: infrared spectroscopy; MFM: magnetic force microscopy; MS: Mössbauer effect spectroscopy; ND: neutron diffraction; NMR: nuclear magnetic resonance;
PCS: photon correlation spectroscopy; PEELS: parallel electron energy loss spectroscopy; RBS: Rutherford back-scattering spectroscopy; SAD: selected area electron diffraction; SANS: small angle
neutron spectroscopy; SAXS: small angle X-ray spectroscopy; SEM: scanning electron microscopy; SQUID: superconducting quantum interference device magnetometry; STM: scanning tunneling
microscopy; TMA: thermal mass analysis; TEM: transmission electron microscopy; TGA: thermal gravimetric analysis; TPD: temperature programmed desorption; TPR: temperature programmed reduction;
UVVis: ultraviolet-visible spectroscopy; UV-NIR: ultraviolet-near infrared spectroscopy; VSM: vibrating sample magnetometry; WAXS: wide angle X-ray spectroscopy; XANES: X-ray absorption near edge
spectroscopy; XRF: X-ray fluorescence; XPS: X-ray photoelectron spectroscopy; XRD: X-ray diffraction.
Method{
Compound*
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Chemically prepared magnetic nanoparticles
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defined crystallinity, but lack controlled morphologies.
This method is used in the precipitation of many ferrites
such as barium and strontium hexaferrites.
The size and morphology of precipitated nanoparticles can be tailored with limited success through the tight
control of synthesis parameters such as pH, metal cation
concentration, and the type of precipitating agent. These
parameters allow the formation of nanoparticles that
have a large size distribution (greater than 30% of the
mean particle size)17 and are roughly spherical. The
concentration of the metal species present in the initial
reaction mixture has the largest effect on the overall
nanoparticle size.18 Unfortunately, low concentrations
result in limited particle growth, although the resultant
particles are generally more uniform in size. As the metal
concentration is increased, there is increased particle
growth with a subsequent loss of size uniformity. A
precipitating agent has a pronounced effect not only on
the overall particle size, but also on the phase purity of
the particle formed. This is especially true in the case
of mixed metal spinels. Numerous precipitating agents
have been employed, including citric acid19–21 and oxalic
acid.22 In each case, there is a chelating effect that helps
to facilitate complete precipitation. The precipitating
agent is then evaporated through subsequent heating
cycles. Subjecting the metal solutions to alkaline media
facilitates the precipitation of metal hydroxides that
result in a product with less agglomeration.
The first controlled synthesis of magnetic nanoparticles utilising this alkaline precipitation technique was
performed by Massart.17 Using this synthesis, Fe3O4
nanoparticles were precipitated from FeCl3 and FeCl2 at
a slightly basic pH of 8.2. These particles were roughly
spherical, 10 nm in diameter with greater than 50%
size distribution. Through size selection titration the
size distribution can be reduced to less than 5%.23
Size selection titration is a technique that disperses
nanoparticles in a solvent to form a stable colloidal
suspension. The colloidal solution is then systematically
disrupted through titration with a non-solvent or
electrolyte solution or temperature control, causing the
larger nanoparticles to precipitate. The precipitate can
be collected using centrifugation or filtration. This can
reduce the size distribution to less than 5%, generating
a monodispersed colloidal solution.24 The synthesis by
alkaline precipitation was later expanded to include
ferrites (MFe2O4, where M5Co,25–27 Mn,25,26
(Mn,Zn),28 and (Ni,Zn)29). The production of mixed
ferrites presents additional difficulties due to the varying
solubilities of the metal hydroxides. In the case of
(Mn,Zn)Fe2O4, Fe(OH)3 starts to precipitate early at
pH 2.6, while Mn(OH)2 precipitates at a much higher
pH of 9.4. The Zn2z cations are amphoteric and
precipitate as Zn(OH)2 at pH 7.6, but begin to redissolve at pH 9 forming Zn(OH)422 anions.30 For these
reasons, to create uniform metal precipitates, the pH
must be carefully controlled at 8.6. The synthesis is
further complicated by the propensity of iron to oxidise,
forming the c-Fe2O3 phase. The Fe3z cations oxidise
at pH.9 producing this common impurity phase with
corresponding poor magnetic properties. Titration of
the metal by the base increases pH to the target value
more slowly than does a titration of the base by the
metal. A slow titration tends to cause additional
problems due to inhomogeneity. As the pH is slowly
136
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2 TEM image of e-Co as deposited superlattice prepared
by injection of lithium triethylborohydride into hot
organic solution containing cobalt chloride and
organic stabilisers TOP and oleic acid (reprinted with
permission from Ref. 40)
increased, the Fe3z approach complete precipitation
before the Zn2z and finally the Mn3z begin to precipitate.
This results in a central core which oxidises to form
c-Fe2O3 coated by a shell of iron-deficient ferrite.
Hydride reduction
The reduction of metal salts using sodium borohydride
can form very uniform spherical nanoparticles. The
chemistry of the reduction can be very complex, however
the reduction of iron,31 cobalt,32,33 and nickel34 has
been explained in detail by Klabunde and co-workers.
Although metal boride formation is a stable reaction, it
can be eliminated with careful control of atmosphere
and water content in the reaction. For this reason, the
reactions are typically carried out in non-aqueous media
(dimethylglyoxime, tetrahydrofuran, etc.) to obtain a
pure phase metal. Mixing metal salts to form one reaction before reduction can form alloys,35–37 for example,
(Fe,Ni,Cu) alloys were processed this way by Stolk and
Manthiram.38 In this case, the particles reduced by
borohydride are spherical, 10–20 nm in diameter, and
of predominantly Invar phase with some impurities of
Cu2O and Fe(BO2)2 present. This material can be heated
where it undergoes a conversion to pure phase Cu–Invar
with the particle size increasing to 200 nm.
Cobalt nanocrystals can also be formed when lithium
triethylborohydride is injected in a hot organic solution
containing trioctylphosphene (TOP) and oleic acid.39–42
The e-Co crystal size can be controlled by the amount of
metal precursor, the reducing agent concentration, and
the amount of TOP and oleic acid used. The nanocrystals
that are produced will self-assemble into superlattices,
as can be seen in Fig. 2. This figure shows an example
of the as deposited superlattice with the interparticle
spacing controlled by organic capping groups.
Hydrothermal
Hydrothermal reactions are aqueous reactions carried
out using autoclaves or high pressure reactors where
the pressure can be over 2000 psi at temperatures above
Published by Maney Publishing (c) IOM Communications Ltd
Willard et al.
200uC. Water acts as a reactant at these supercritical
conditions, accelerating the kinetics of the hydrolysis
reactions. At increased temperatures, the solubility of
most ionic species increases and, with the lower viscosity
of water, exhibits greater mobility. The increased
mobility allows Ostwald ripening to continue at a faster
rate increasing the uniformity of the precipitates.
Size and morphological control in hydrothermal
reactions is achieved by controlling time and temperature. The reaction conditions of precursor material and
pH have an impact on phase purity of the nanoparticles.
There are two main routes for the formation of ferrites
via hydrothermal conditions: hydrolysis and oxidation,
and neutralisation of mixed metal hydroxides. Some
lesser routes involve the hydrothermal treatment of
mixed metal oxides,43,44 or the use of other solvents
such as ethylene glycol at supercritical conditions.45,46
Hydrolysis and oxidation reactions are very similar to
neutralisation reactions where the former uses ferrous
salts as opposed to ferric salts in the latter.47
Rozman and Drofenik48 gave a detailed account of
the synthesis of (Mn,Zn)Fe2O4 ferrite nanoparticles by
the neutralisation of the mixed metal hydroxides. The
hydrothermal parameters of temperature and time were
varied resulting in 11 nm nanoparticles at both 95uC
for 50 h and 140uC for 0.5 h. The shorter reaction time
resulted in a nanoparticle surface with a greater amount
of hydroxide groups, while reduced temperatures
allowed additional water to be incorporated in the
crystal structure that caused increased lattice distortions.
Differential thermal analysis showed that the water is
actually incorporated into the lattice with final dehydration at temperatures in excess of 700uC. This distortion
and poor surface quality deteriorates magnetic properties. Rozman and Drofenik also noted that the spinel
phase starts to crystallise at 90uC and continues through
to 200uC. At temperatures greater than 200uC, the spinel
phase can recrystallise as c-Fe2O3. The nanoparticle
grains grow via Ostwald ripening.
Strontium49 and barium50 hexaferrites can be more
difficult to form due to the limited solubility of the
strontium and barium precursors. Initial reactants have a
greater impact on the final size, morphology, and phase of
the hexaferrites than in other mixed metal ferrites. As with
other ferrite preparations, temperature and reaction time
influence size, as does the ratio of Fe/Ba. The choice of
precipitating reagent has a pronounced effect on nanoparticle crystallinity. The larger the size of the spectator
ion of the precipitating agent, the poorer the crystallinity.
This phenomenon is presumably due to a change in the
electrostatic potential of the metal hydroxides. The lower
the electrostatic potential of the metal solution, the greater
is the likelihood that the metal sols coagulate. This
coagulation tends to facilitate the formation of c-Fe2O3.51
Since coagulation favours side reactions, stirring is often
used to break up coagulating sols. Stirring the hydrothermal solution has resulted in improved nanoparticle
uniformity and phase purity.
Nanoparticles of barium hexaferrite have been
synthesised hydrothermally under supercritical conditions using a rapid heat flow system.52 This allows the
formation of barium hexaferrite in brief times (as short
as 30 min) and in a non-stoichiometric, continuous flow
synthesis. An example of the product from this synthesis
is shown in Fig. 3.
Chemically prepared magnetic nanoparticles
3 TEM micrograph of BaFe12O19 prepared by hydrothermal synthesis in supercritical water: thin hexagonal
platelets are the typical morphology for M-type hexaferrites due to easier growth perpendicular to crystallographic c axis52
Micelle routes
Surfactant molecules when in solution spontaneously
form spherical aggregates called micelles or microemulsions. The difference between microemulsions and
micelles is more than simple semantics, although
recently these terms have been used interchangeably.
The micelle aggregates have sizes of 1–10 nm in
diameter, while microemulsions contain aggregates that
are 10–100 nm in diameter.53
Direct micelles have the hydrophilic portion of the
surfactant on the outside of the aggregate exposed
to polar solvent, while reverse or inverse micelles have
the hydrophobic portion on the outside exposed to a
non-polar solvent. Micelles can form in the presence
or absence of water. In the case of reverse micelles
formed in hydrocarbon, water can be readily solubilised
forming a ‘water pool’ where size is characterised by a
water/surfactant ratio. In this fashion, the water pools
within micelles impose kinetic and thermodynamic
constraints on particle formation resulting in restricted
‘nano-reactors’.
Aerosol OT or AOT (sodium dioctylsulphosuccinate)
was the first and most characterised surfactant system
used in the synthesis of magnetic nanoparticles.54–56
Other systems, such as cetyltrimethylammonium bromide (CTAB),57 sodium dodecylsulphate (SDS),58 and
polyethoxylates (Igepal, Brij, Tween, C12E5)59 have been
used, and more are being developed to optimise
morphology and chemical parameters. Many of the
reactions carried out in micelles are very similar to those
performed in bulk aqueous reactions, but with the added
morphological controls afforded by the surfactant
system.
The first magnetic nanoparticles formed in micelles
were from the oxidation of Fe2z salts to form Fe3O4 and
c-Fe2O3.60 This reaction was carried out in an AOT/
isooctane system and formed spherical nanoparticles
with surprisingly tight size distributions of less than
10%. Later, other reactions using hydrogen peroxide
were used to form MnFe2O4. The initial reaction
conditions not only controlled the particle size, but also
the cation occupancy.61
An interesting phenomenon seen with iron reductions
is the influence of the surfactant on the iron crystal
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5 TEM image of cobalt hexacyanoferrate
synthesised using reverse micelles69
a polyhedral 13 nm average particle size synthesised by
quenching reaction after short reaction time; b spherical
39 nm particles formed after reacting for 2 h
4 Antiferromagnetic KMnF3 nanoparticles synthesised by
reverse micelle reactions (TEM)67,68
structure. If anionic surfactants (such as AOT) are used,
a-Fe is formed with the body centred cubic (bcc) crystal
structure expected from thermodynamic equilibrium of
the bulk metal at room temperature.62 Conversely, if
a non-ionic surfactant is used (for instance, nonyl
phenol polyethoxylate), a face centred cubic (fcc) crystal
structure forms.63 The process for the formation of
metals can be expanded to form metal alloys. Instead
of using a single metal salt, mixed metal salts are used
and reduced simultaneously.64 It is essential that the
reduction is carried out simultaneously or mixed phase
products will be formed.
The precipitation of precursors that are subsequently
fired to produce an oxide end product is an important
synthetic process. This has been used in the synthesis
of many different ferrite materials: (Mn,Zn)Fe2O4,
(Ni,Zn)Fe2O4, ZnFe2O4,65 and BaFe12O19.66 In these
cases, the particles were formed with sizes between 5 and
50 nm. The particles had spheroidal morphology with
typical size variations of 10%, although higher conversion temperatures generally widen the size distribution
to 10–20%.
Transmission electron microscopy images of antiferromagnetic KMnF3 nanoparticles synthesised using
reverse micelles are shown in Fig. 4. The reaction time
of the metathesis reaction controlled the morphology
and size of the particles for this reaction. Particles
synthesised by quenching the reaction after short
reaction times developed polyhedral morphology and
13 nm average particle size (Fig. 4a). Similar reactions
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nanocubes
carried out for 2 h resulted in particles with spherical
morphology and 39 nm average grain diameters
(Fig. 4b).67,68 Cobalt hexacyanoferrate nanocubes have
been prepared using reverse micelles and AOT.69 Figure 5
shows the cubic morphology of the resulting cobalt
hexacyanoferrate.
Although there are many examples of inverse micelles
used as microreactors, there are only a few examples of
the use of direct micelles. Sodium dodecylsulphate is the
principle surfactant used in these reactions due to the
morphology of the aggregate. The most striking example
of direct micelle synthesis was presented by Liu and
co-workers with the synthesis of CoFe2O4.70,71 In this
example, a chemometric model was created for predicting the size of a ferrite from the synthesis conditions
of surfactant concentration, metal concentration, base
concentration, and temperature. The synthesis was later
expanded to include the mixed ferrites of MnFe2O4 and
MgFe2O4.71,72
In order to control side reactions and precipitation
common to aqueous systems, micelles are formed using
alcohol as the polar phase. Fang et al.73 employed
ethanol-based micelles to form SrFe12O19. In this
case, Sr(OH)2 has such a high solubility in water that
inhomogeneous and strontium deficient precipitates
are formed, thus the change to ethanol was necessary.
The particles display a large size distribution and a
platelike morphology with an average particle size of
100 nm.
Thermolysis, photolysis, and sonolysis methods
One of the simplest methods to prepare nanoparticles is
the decomposition of organometallic precursors. This
decomposition may be driven by heat (thermolysis),
light (photolysis), or sound (sonolysis). The relatively
low decomposition temperature of organometallic compounds is a distinct advantage over other processing
techniques. The decomposition temperature controls the
nanoparticle growth. Since size and morphology have
an effect on the properties of the nanoparticles, control
of these properties is a primary goal. In many cases,
polymers, organic capping agents or structural hosts are
used to limit the size of the nanoparticle.74–85 The
Willard et al.
Published by Maney Publishing (c) IOM Communications Ltd
6 TEM micrograph of hcp cobalt rods, prepared by rapid
thermal decomposition of Co(CO)8 in hot organic solution containing TOPO, oleic acid and o-dichlorobenzene76
polymers and capping agents are generally used to
stearically protect the particles so that they do not
coalesce. None the less, the particles synthesised are
often agglomerated and have a large size distribution.
Even if they are stabilised with surfactants or other
organics to prevent agglomeration, they can interact
with the surface, changing the magnetic properties.
As an example, it has been shown that the magnetic
properties of nickel are affected by the presence of
surface moieties.85–87 However, there has been a great
deal of research on preparation of monodispersed,
unagglomerated nanoparticles as outlined in the following subsections.
As stated above, polymers can be used to limit particle
growth. One polymer, polyvinylpyrrolidone (PVP), has
been shown to interact minimally with the surface of
cobalt.74,75 It is suggested that the polymer matrix
determines the cluster size and efficiently protects the
particles. Cobalt nanoclusters were prepared by reduction of organometallic compounds of Co(g3-C8H13)(g4C8H12) in hydrogen and in the presence of PVP.74
Dried colloids were made up of non-interacting superparamagnetic particles. By varying the decomposition
temperature, the size of particles was controlled. Organometallic precursors were also used to prepare other
colloidal metals with a variation of size and structure.
An example of this approach is the CoxPt12x alloy,
prepared from an organometallic precursor with PVP.88
In most cases, when carbonyls are decomposed in
the presence of stabilising polymers, spherical nanoparticles are formed. However, Alivisatos et al., have shown
that cobalt nanorods could be prepared by modifying
the thermal decomposition of cobalt carbonyl in the
presence of oleic acid and trioctylphospheneoxide
(TOPO).76–78 They rapidly injected the organometallic
precursor into a hot surfactant mixture. This rapid
injection of the precursor allowed for a ‘size distribution
focusing’ by separating nucleation from growth.77,78 The
decomposition of the precursor and nucleation occurs
immediately upon injection, and metal nuclei are coated
with the coordinating ligands. When a surfactant mixture is used (such as oleic acid and TOPO) and quenched
shortly after injection, nanoparticles (4625 nm) of
hexagonal close packed (hcp) cobalt are formed, as
can be seen in Fig. 6. This morphology indicates that the
surfactants link to different crystal faces with different
strengths.77,78 If the reaction is allowed to proceed, the
Chemically prepared magnetic nanoparticles
7 c-Fe2O3 nanoparticles formed when organometallic precursor CupFe (iron cupferron complex) was injected
into solution of hot surfactants (TEM)91
rods transform to monodispersed spherical e-Co nanoparticles. If the coordinating ligand is a linear amine,
both spherical e-Co and hcp cobalt discs are simultaneously formed.89 Increasing the amount of surfactant
or adding the amine with the carbonyl leads to more
disc formation. This e-Co crystal structure has been
reported for cobalt nanoparticles prepared by a variety
of solution techniques.76–79
TOPO along with other organic capping and stabilising agents has also been used to synthesise nanorods
of iron.90 Spheres of nanosized c-Fe2O3 are easily
formed when the iron cupferron complex is rapidly
injected into trioctylamine at 300uC.91 The results of this
injection are shown in Fig. 7. When the organometallic
precursor, nickel bis-cycloocta-1,5-diene (Ni(COD)2)
undergoes thermolysis in the presence of hexadecylamine (HAD) or TOPO, nanorods, spheres or tearshaped nanorods (Fig. 8) are formed, the shape being
related to the concentration of the organic species.92
When [Co(g3-C8H13)(g4-C8H12)] is decomposed in anisole in the presence of an amine under 3 bar of H2, the
resulting nanoparticles formed have greatly varying
morphologies. For instance, they can be anywhere from
3 nm and relatively monodisperse to agglomerates with
8 TEM image of nickel nanorods prepared by decomposition of Ni(COD)2 in presence of 10 equivalent of hexadecylamine (HAD)92
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a large size distribution to the formation of wires, having
a 4 nm diameter and 1–3 mm in length.93 The type of
amine and its concentration with respect to oleic acid
are determining factors as regards wire formation. Using
cobalt carbonyl under similar conditions results in
10 nm nanoparticles, while varying the organic stabilising agents used, results in other morphologies. Bracelet
arrays of 27 nm cobalt particles are formed in the
presence of resorcinol tetraphosphonate94 and tetrahedral structures95 are found when cobalt nanoclusters are
reacted with NaAOT/toluene at 130uC.
CoPt alloys and cobalt with a platinum shell have
been prepared using transmetallation and CO decomposition.96 Alloys are prepared by the addition of
Co2(CO)8 to a hot solution of an organic solvent
containing a platinum organometallic compound and
oleic acid. As the carbonyl decomposes to form cobalt
nuclei, it also undergoes a transmetallation reaction with
the platinum organometallic compound. To prepare a
core/shell material, cobalt colloids are first formed by
the decomposition of the carbonyl and then they are
refluxed with the platinum organometallic compound
with dodecane isocyanide as a stabiliser.
The decomposition process may also be applied to
form magnetic oxides.97 This can be done by either
oxidising the metal particles or through an oxidative
decomposition. In the first case, an iron oleate precursor
is formed from the decomposition of iron carbonyl in
the presence of octyl ether and oleic acid at 100uC. This
solution is cooled to room temperature and the mild
oxidising agent, (CH3)3NO, is added and the solution
refluxed. This results in 11 nm Fe2O3 particles that will
also form a two-dimensional hcp lattice. When the
solution is refluxed, the iron oleate complex breaks
down and iron particles are formed and then oxidised
by (CH3)3NO. Variations in particle growth may occur
by changing the amount of reactants or adding already
prepared 11 nm nanoparticles into a fresh solution and
reheating. Oxidative decomposition occurs when an
oxidising agent and surfactant are added to the original
solution. If a bimetallic organometallic precursor is
used, such as (g5-C5H5)CoFe2(CO)9, CoFe2O4 nanoparticles with sizes of 4–9 nm are formed.98
Sonolysis or sonochemistry uses ultrasound or acoustic waves to decompose the organometallic precursors.
The formation, growth, and collapse of bubbles in a
liquid, drive high energy sonochemical reactions, without any molecular coupling of the ultrasound with the
chemical species. This acoustic cavitation provides a
localised hot spot with temperatures of about 5000 K,
and pressures of y1800 atm. Subsequent cooling rates
of about 109 K s21 are produced by the implosive
collapse of bubbles in the liquid.99–109 Generally, volatile
precursors in low vapour pressure solvents are used to
optimise the particle yield. Acoustic irradiation is carried
out with an ultrasound probe, such as a titanium horn
operating at 20 kHz.
Nanostructured particles are easily produced by
sonochemically treating volatile organometallic precursors.99–117 The powders formed are usually amorphous,
agglomerated, and porous. To obtain the crystalline
phases, these powders may be annealed at relatively low
temperatures.
Highly porous amorphous powders are formed when
organic solvents with high boiling points are used for
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sonolysis. For example, an amorphous iron powder
was produced by the sonocation of iron carbonyl in
decalin,99–101 yielding powder with a surface area of
120 m2 g21. Annealing this powder at 350uC under
nitrogen resulted in a2Fe that was 50 nm in diameter.
(Fe,Co),102,103 (Fe,Ni),104 and (Co,Ni)110 alloys have
been prepared by this method. The as synthesised
powders are amorphous. Annealing these powders in
argon at 450uC for 5 h provides crystallisation. The
(Fe,Co) is comprised of bcc iron and a mixture of fcc
and hcp cobalt, while the (Fe,Ni) and (Co, Ni) alloys
are fcc.
Starting with the organometallic precursor,
Fe(tBu)2(THF)2, Biddlecombe et al. were able to use
ultrasound to prepare nanocrystalline Fe3O4 or Fe2O3,
depending on the post-preparative conditions.118 If the
as prepared powders are dried in vacuo, approximately
19 nm Fe3O4 particles are formed. On the other hand,
if the as prepared powder is dried in air at 200uC,
then 9 nm c-Fe2O3 is formed. The dried Fe3O4 nanoparticles form micrometre sized plate-like structures,
whereas the dried c-Fe2O3 nanoparticles form needlelike structures.
When stabilisers or polymers are added during or
after sonication, then metal colloids result.101,102,105,111
These stabilisers could be alkyl thiols,103,106,111 PVP,101
oleic acid,101 octadecyltrichlorosilane (OTS),111 and
sodium dodecylsulphate (SDS).84 Gedanken and coworkers104,105,112 have also used sonochemical routes to
prepare nanoparticles of Fe, Fe3O4, Fe2O3, CoFe2O4,
and CuFe2O4. If the sonication is carried out in the
presence of oxygen, then oxides are formed.112,113 In the
case of Fe2O3, when the coating solution was present
during sonolysis, amorphous powder resulted, that was
then converted to c-Fe2O3 upon annealing at 300uC
for 3 h under an argon atmosphere. If the powder is
first converted to c-Fe2O3, the OTS does not coat the
powder. In general, nanoparticles with dimensions less
than 10 nm will self-assemble to the thermodynamically
stable form, usually an hcp assembly of particles. By
pressing the nanoparticle solution on a substrate or
interface, careful removal of the solvent will result in
self-assembled monolayers (SAM). The size of the SAM
coated nanoparticles is determined by the surfactant
concentration in the coating solution. Oxide formation
(Fe3O4, Co3O4) was also seen if the sonication was
carried out in aqueous conditions and with noncarbonyl precursors, however the resulting powders
were crystalline.113–116 When cyclodextrin is added to
the aqueous solution, Fe3O4 nanorods are formed.119 An
example of the nanorods formed by this process is
shown in Fig. 9.
If the sonolysis is carried out in the presence of a
support or porous host, then colloidal metal particles are
formed. These powders have a surface area and catalytic
activity greater than those of commercially available
or conventionally prepared materials. For example, 3–
8 nm amorphous iron particles on silica support were
synthesised at 20uC from iron pentacarbonyl (Fe(CO)5),
decane and silica gel.102 The sonochemically prepared
Fe/SiO2 has an order of magnitude more active surface
than the conventionally prepared material for the
Fischer–Tropsch reaction. However, these materials
are generally considered for catalytic reactions and not
for magnetic applications.
Willard et al.
9 Fe3O4 nanorods prepared sonchemically in aqueous
solution containing iron (II) acetate and b-cyclodextrin
(TEM)119
Published by Maney Publishing (c) IOM Communications Ltd
Sol–gel methods
Sol–gel processing can be used to prepare a variety of
materials, including glasses, powders, films, fibres, and
monoliths. Traditionally, the sol–gel process involves
hydrolysis and condensation of metal alkoxides. Metal
alkoxides are good precursors because they readily
undergo hydrolysis, i.e. the hydrolysis step replaces an
alkoxide with a hydroxide group from water and a free
alcohol is formed. Once hydrolysis has occurred the
sol can react further and condensation reaction (polymerisation in some cases) occurs.
Factors that need to be considered in a sol–gel process
are solvent type, temperature, precursors, catalysts,
pH, additives and mechanical agitation. These factors
can influence the kinetics, growth, and hydrolysis and
condensation reactions.120 The solvent influences the
kinetics and conformation of the precursors, and the pH
affects the hydrolysis and condensation reactions. The
pH also affects the isoelectric point and the stability of
the sol. These in turn affect the aggregation and particle
size. By varying the factors that influence the reaction
rates of hydrolysis and condensation, the structure and
properties of the gel can be tailored. Because these
reactions are carried out at room temperature, further
heat treatments need to be carried out to achieve the
final crystalline state. Due to the metastability of the
as synthesised particles, annealing and sintering can be
performed at low temperatures.
Sol–gel routes have been used to prepare pure, stoichiometric, dense, equiaxed and monodispersed particles
of TiO2 and SiO2,120 but this control has not been
extended to the ferrites. Generally, the particles produced are agglomerated. Ultrafine powders of CoFe2O4
and NiFe2O4 have been synthesised after being calcined
at 450 and 400uC, respectively.121,122 Most of the ferrite
sol–gel synthesis focus has been on cobalt ferrite compositional substitution studies with Mn,123 Cr,124 Bi,125
Y, La,126 Gd, Nd,127 and Zn.128
Sol–gel routes have also been attractive for the
preparation of hexagonal ferrites. For example, the
M-type hexagonal ferrite, Ba12xSrxFe12O19, formed 80–
85 nm hexagonal platelets after a 950uC calcination
for 6 h.129 And nanospheres of the W-type ferrite,
BaZn22xCoxFe16O27, resulted after calcination in air for
4 h at 650uC.130 The particle size ranged from 10 to
500 nm corresponding to annealing temperatures of 650
Chemically prepared magnetic nanoparticles
and 1250uC, respectively, and increased with increasing
calcination temperatures. U-type hexagonal ferrites were
also prepared, with 10–25 nm spherical particles formed
at 750uC.131 The grain size could be changed by
increasing the calcination temperature. These calcined
powders had an amorphous layer coating. Sol–gel routes
have also been used to prepare precursors of BaFe12O19,
which upon calcining at 850uC, yields the hexagonal
ferrite. Yttrium iron garnets with particle sizes from
45 to 450 nm have also been prepared.132 Mathur
and Shen133 have prepared the manganite perovskite
La0.67Ca0.33MnO3 by dissolving the metal precursors in
an acidic ethanolic solution. Drying the solution at
120uC and calcining at 300–400uC leads to preceramic
foam which forms nanocrystalline La0.67Ca0.33MnO3
(40 nm) after a heat treatment at 650uC.
It should be noted that the sol–gel process is
particularly attractive for the synthesis of multicomponent particles with binary or ternary compositions using
double alkoxides (two metals in one molecule) or mixed
alkoxides (with mixed metaloxane bonds between two
metals). Atomic homogeneity is not easily achieved by
coprecipitating colloidal hydroxides from a mixture of
salt solutions, since it is difficult to construct double
metaloxane bonds from metal salt.120
Hybrid materials such as metal oxide–organic nanocomposites can be prepared using the sol–gel approach.
For example, controlled nanoheterogeneity can be
achieved in metal/ceramic nanocomposites.120 Reduction of metal oxide particles in hydrogen provided the
metal–ceramic nanocomposite powders such as iron in
silica,134 Fe2O3,135 and NiFe2O4.136 The metal particles,
a few nanometres in size with a very narrow size
distribution even for high metal loading, were statistically distributed in the oxide matrix without any
agglomeration, as a result of anchoring the metal
complexes to the oxide matrix. The narrow particle size
distribution could not be achieved if the sol–gel
processing was performed without complexation of
metal ions.
Polyol
The polyol method, in which the polyol acts as solvent,
reducing agent, and surfactant, is a suitable method for
preparing nanophase and micrometre size particles with
well defined shapes and controlled particle sizes.137–170
By this method, precursor compounds such as oxides,
nitrates, and acetates are either dissolved or suspended
in a diol, such as ethylene glycol or diethylene glycol.
The reaction mixture is then heated to reflux between
180 and 199uC. During the reaction, the metal precursors become solubilised in the diol, form an intermediate, and then are reduced to form metal nuclei,
which form metal particles. Submicrometre size particles
can be synthesised by increasing the reaction temperature or inducing heterogeneous nucleation via adding
foreign nuclei or forming foreign nuclei in situ. Nanocrystalline powders such as Fe, Co, Ni, Cu, Ru, Rh,
Pd, Ag, Sn, Re, W, Pt, Au, (Fe,Cu), (Co,Cu), (Co,Ni),
and (Ni,Cu) were also synthesised using different salt
precursors by this method.137–165 In many cases, use of
nucleating agents to assist formation of nanoparticles
was not required. For example, nanostructured powders
of CoxCu1002x (4(x(49 at.-%)137,138 were synthesised
by reacting cobalt acetate tetrahydrate and copper
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Chemically prepared magnetic nanoparticles
10 Fe48Co52 nanoparticles prepared by a polyol method
(SEM)149
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acetate hydrate in various proportions in ethylene
glycol. The mixtures were refluxed at 180–190uC for
2 h, the powders precipitated out of solution, and were
subsequently collected and dried. Since copper was more
reducible than cobalt, nucleation of copper occurred
first, and cobalt subsequently nucleated on copper
crystallites. X-ray diffraction showed evidence for
formation of a metastable alloy. Diffraction peaks due
to fcc copper were detected in all samples, however
diffraction peaks due to cobalt were not detected until
x519. To confirm the structure of powders, studies of
local atomic environment were performed using
extended X-ray absorption fine structure (EXAFS)
spectroscopy and solid state nuclear magnetic resonance
(NMR). The results from these investigations and
vibrating sample magnetometry (VSM) ruled out the
formation of metastable alloys, but confirmed the
synthesis of nanocomposites of (Co,Cu).
The polyol method has also been a useful preparative
technique for the synthesis of nanocrystalline alloys and
bimetallic clusters. Fiévet and co-workers have extensively
studied the ferromagnetic system of (Co,Ni), (Fe,Co),
(Fe,Co,Ni).139–148 The (Co,Ni) alloy particles had densities and saturation magnetisation close to the bulk
values, and showed a shift to higher FMR resonance frequencies as the Co/Ni increased. This was also observed
in the (Fe,Co,Ni) particles that were 50–150 nm in size.
An example of the morphology of alloy nanoparticles
formed by the polyol technique is shown in Fig. 10. The
particles depicted by the SEM image consist of Fe48Co52
and possess a mean particle size of 30 nm.149 Nanocrystalline Fe10Co90 powders with grain size of 20 nm
were prepared by reducing iron chloride and cobalt
hydroxide in ethylene glycol without nucleating agents.150
Nickel clusters were prepared using platinum or
palladium as nucleation agents.151 The nucleating agent
was added 10 min after the nickel hydroxide–PVP–
ethylene glycol solution began refluxing. The nickel
particle size was reduced from about 140 to 30 nm when
a nucleating agent was used. Reduction of particle size
was also obtained by decreasing the nickel hydroxide
concentration and by the use of PVP. Nickel prepared
without nucleating agents oxidised at a temperature of
370uC. Smaller nickel particles synthesised with nucleating aids oxidised at a lower temperature of 260uC, as
expected from the higher surface area of finer particles.
Desorption studies showed the adsorbed surface species
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11 TEM image of Co nanoparticles prepared by polyol
method from acetate medium171
were CO moieties and H2O, and nitrogen containing
species were not observed. This indicated that ethylene
glycol, not the polymer, was adsorbed on the surface of
particles. The ethylene glycol had only half monolayer
coverage. When this protective glycol was completely
removed from the surface, oxidation occurred. It was
suggested that the Ni–Pd and Ni–Pt particles had a
7–9 nm palladium and a 6–8 nm platinum nucleus,
respectively. Oxidation studies showed that some alloying of nickel with platinum occurred.
Cobalt nickel alloys of 210–260 nm particle sizes were
also prepared using either silver or iron as nucleating
agents.152 Recently, anisotropic particles of cobalt and
(Co,Ni) have been prepared.171 By adding sodium
acetate or sodium hydroxide to the polyol solution, or
ruthenium as a nucleating agent, non-spherical particles
resulted. If sodium acetate is added to the solution,
agglomerates of rods (25 nm dia.) formed. Addition of
the hydroxide to the polyol solution leads to 25–40 nm
hexagonal platelets. An example of the hexagonal
structure can be seen in Fig. 11.
Polymer protected bimetallic clusters were also
formed using a modified polyol process.152 The modification included addition of other solvents and sodium
hydroxide. In the synthesis of (Co,Ni) with average
diameters between 150 and 500 nm, PVP and ethylene
glycol were mixed with cobalt and nickel acetate with
PVP. The glycol and organic solvents were removed
from solution by rinsing in acetone or filtration. The
PVP covered particles were stable in air for months.
Compared to aqueous methods, the polyol approach
resulted in the synthesis of metallic nanoparticles
protected by surface adsorbed glycol, thus minimising
the oxidation. The use of non-aqueous solvent such as
polyol also further reduced the problem of hydrolysis of
fine metal particles as often occurred in the aqueous
case.
By modifying the polyol method with the addition
of water to act more like a sol–gel reaction (forced
hydrolysis), oxides can be prepared.153–155,172 For
example, 6 nm CoFe2O4 was prepared by the reaction
of ferric chloride and cobalt acetate in 1,2-propanediol
with the addition of water and sodium acetate. In this
case, spherical particles formed, however the reaction
did not use the ruthenium nucleating agent. Soluble
c-Fe2O3 nanoparticles can be prepared similarly to the
method of the CoFe2O4, however an amine capping
agent (n-octylamine) must be added to the solution.173
Willard et al.
Other heating sources for the polyol method have
been reported besides the conventional heating mantle.
Alternative sources include a 2.45 GHz microwave
gyrotron169 and millimetre wave beam sources.170 One
technique, the laser–liquid method, uses a laser to heat
the solution.174,175 This has been used to prepare
submicrometre nickel particles.
Published by Maney Publishing (c) IOM Communications Ltd
Electrochemical/electrodeposition
Electrochemical and electrodeposition routes are generally used to prepare nanocrystalline coatings, and are
not the focus of this paper. However, electrodeposition has been used to prepare wires of magnetic
materials176–186 and recently it has been used to prepare
particles.187–195 Grain growth is favoured at low overpotentials and high surface diffusion rates, and nuclei
formation is favoured at high overpotentials and low
diffusion rates. These conditions are experimentally
achieved when using pulsed modes. Under pulsed
conditions, the peak current density can be considerably
higher than the limiting current density attained for the
same electrolyte during direct current plating. It has
been shown that nanostructured materials will result
when the deposition variables (i.e. bath composition,
pH, temperature, current density, overpotential, and
additives) are chosen so that nucleation is favoured with
reduced grain growth.
Recently, Penner187 has carried out a detailed study
and modelling of the parameters that affect the
nucleation and growth in electrodeposited nanoparticles
and wires. He has followed the LaMer and Dinegar
model11 to explain the formation of electrodeposited
platinum nanoparticles on graphite electrodes. Penner
and co-workers found that when instantaneous nucleation and diffusion controlled growth conditions were
satisfied, the particles formed were 7 nm in diameter
with a standard deviation of 3.2.196 From these results,
two factors were considered for the broadening of the
particle size distribution. In electrodeposition, the nuclei
are distributed on the electrode surface in a ‘pseudorandom’ process. On the terraces, the nucleation process is
random, yet, while on the step edges, the nuclei are
aligned along the edge. The growth step is dependent on
the number and proximity of the neighbouring nuclei.
Penner points out that interparticle diffusion coupling
(IDC) is the most important mechanism for broadening
of the size distribution for randomly nucleated particles.
This condition also exists in solutions, but instead of
nucleating heterogeneously, the particles in solution
collide, react, and move on. Experimentally, to overcome IDC, the slow growth method187,188,196,197 or H2
coevolution method was used. In the slow growth
method, a high overpotential is applied to provide
nuclei on the electrode. A second low overpotential
pulse is then applied to promote the growth step. Nickel
nanoparticles were synthesised using this slow growth
method.189 In H2 coevolution, convective mixing equalised the growth rate of the nanoparticles. The formation
of gas bubbles and their release and movement through
the solution caused convective mixing. By varying the
deposition time and potential, nickel nanoparticles of
2–250 nm were synthesised.187,188
Another electrochemical method that has been used to
prepare nanoparticles involves the use of a sacrificial
anode.189–191,198 Based on a method developed by Reetz
Chemically prepared magnetic nanoparticles
et al.,199 Pascal et al.191 have prepared 3–8 nm iron
oxide nanoparticles from a sacrificial iron electrode
in an aqueous solution of dimethylformamide (DMF)
and cationic surfactants. Adjusting the current density
controls the particle size. The as prepared nanoparticles
showed a broad scattering peak by X-ray diffraction,
consistent with an amorphous phase. Dierstein et al.
have used a similar strategy to prepare other metal
oxides.189 This technique is termed ‘electrochemical
deposition under oxidising conditions’ (EDOC). Here
the anode is oxidised to produce Mnz species in
solution, which are then reduced by electrons generated
by the cathode, in the presence of stabilisers. These
stabilised metal species are then oxidised by oxygen that
is bubbled into the system.189 The EDOC technique has
been used to prepare nanoparticles of Fe2O3, Fe3O4,
Co3O4, NiO, and CoFe2O4.176 The difference between
the method used by Pascal et al. and EDOC, is that, in
EDOC, oxygen is bubbled in, whereas, in the Pascal et al.
synthesis, oxygen is produce from the electrochemical
breakdown of water. Mixed oxides of strontium
hexaferrites,192 and (Mn,Zn) spinel ferrites193 have also
been prepared using sacrificial electrodes.
Nanowires are easily formed in porous templates by
electrodeposition. Unlike precipitation methods and
chemical vapour deposition, where great care must be
taken so as not to plug the pores during wire formation,
templated electrodeposition provides material growth
from the base, thus plugging is avoided. This technique
has been used to prepare nanowires of cobalt
(Refs. 177–181, 199–201), nickel (Refs. 178–182, 190,
194, 202, 203), FePt (Ref. 183), FeCo (Ref. 184), FeNi
(Ref. 176), CoPt (Ref. 183), with the common template
materials, polycarbonate,204 anodised alumina,177,182
and mica.176
Multisynthesis processing methods
The IBM nanoparticle synthesis route3 is a combination
and variation of the polyol method and the thermal
decomposition routes used by Alivisatos et al.77–79 This
multisynthesis process (MSP) involves a high temperature organic or solution phase synthesis followed by a
size selective separation technique to obtain relatively
monodispersed (,5%) nanoparticles. More specifically,
rapid injection of the organometallic precursor into a
hot solution containing the stabilising agents allows
nucleation immediately upon injection. Because the
capping agents and surfactants are present, the size
and shape of the nanoparticles are controlled. Size and
morphology can be controlled by adjusting the reaction
conditions such as time, temperature, precursor concentration, surfactant type, and surfactant concentration.
Sun et al.3 have prepared monodispersed FePt
nanoparticles and self-assembled superlattices by the
high temperature reduction of platinum acetylacetonate
and the thermal decomposition of iron carbonyl in
the presence of stabilising agents. In the case of FePt,
both reactions were carried out together in the presence
of oleic acid and oleyl amine. The composition was
controlled by the ratio of the iron precursor to that of
the platinum precursor. The nanoparticles were produced with sizes tunable in the range 3–10 nm. A
colloidal solution of the nanoparticles was prepared by
flocculating the particles and redispersing them in a nonpolar solvent. This solution was put on a substrate and
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Willard et al.
Chemically prepared magnetic nanoparticles
12 a Superlattice of Fe50Pt50 prepared by multisynthesis
process (MSP) and b resulting superstructure when
oleic acid/oleyl amine is replaced with hexyl analogs
(TEM)3
the solvent allowed to evaporate. This led to the selfassembly of the nanoparticles. An hcp three-dimensional
superlattice was formed by the self-assembly of 6 nm
Fe50Pt50 with oleic acid and oleyl amine stabilisers
(Fig. 12). Changing the alkyl group on the stabilisers can
change the interparticle distance and superlattice symmetry. This is evident in Figure 12b, in which the oleic
acid/oleyl amine was replaced with hexanoic acid/
hexylamine. Changing the alkyl group from dodecyl
to hexyl leads to a particle spacing of 1 nm, and a
superlattice having a cubic close packed structure. This
hcp to cubic transition was also seen with e-Co. The
superlattices show no aggregation at temperatures up to
600uC.
The as synthesised 4 nm Fe52Pt48 has a fcc structure
and annealing at 560uC for 30 min leads to particles with
an ordered L10 crystal structure. Particle superlattices of
these particles exhibit a similar trend. The as synthesised
assembly has a chemically disordered fcc structure where
annealing results in the iron and platinum atoms
rearranging into the chemically ordered L10 structure.
(The term fct – face centered tetragonal – has been used
to describe the ordered phase of FePt, CoPt, FePd, and
CoPd intermetallics by the nanoparticle community.
This is strictly incorrect, as the L10 phase is primitive
tetragonal with ordered layers of atoms along the [001],
e.g. Fe atoms on z50 plane and Pt atoms on z51/2
plane.205) The amount of ordering can be controlled by
temperature and annealing time. Since the initial paper
on FePt synthesis,3 there has been an explosion of
research on FePt prepared by this method206–216 or
variations on this method217,218 and other magnetic
materials, i.e. Mn52.5Pt47.5 (Ref. 219), CoPt (Refs. 220,
221), FePd (Ref. 220), and SmCo (Ref. 204). Recently,
core/shell particles of platinum on iron and platinum on
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Fe2O3 have been prepared using this method.222,223 In
this case, the Pt(acac)2 solution was injected in the hot
organic solution, then the temperature was lowered to
70uC and the iron carbonyl was added to the Pt–organic
solution. After the iron carbonyl addition, the temperature was raised again. This route yielded 10 nm cores
of platinum and an iron shell that was 2–3 nm thick.
Even with the presence of oleic acid in the organic
solution, the iron shell oxidised. Powder XRD could not
distinguish between c-Fe2O3 and Fe3O4, so XPS was
used to determine the nature of the oxide formed. It
was found to be c-Fe2O3 which was also confirmed by
HRTEM lattice imaging.
One of the greatest advantages of chemical routes is
that they are carried out in solution. This allows a great
deal of versatility and compatibility. Since many of the
chemical routes use similar solvent systems, they may be
interchanged for one another or carried out concurrently. Therefore, combining one or more techniques is
relatively simple. For instance, micellar techniques are
often used to regulate the size of the nanoparticles in
sol–gel synthesis. The versatility also comes from the
fact that a broader spectrum of materials can be
prepared by combining techniques. In addition, because
this is a solution technique, additives, capping agents,
and functionalities are easily added to the reaction.
These additives can be added pre-synthesis, in situ, or
post-synthesis. It is also possible to prepare nuclei or
cores by one technique and inject them into the solution
of a second, thereby either forming particles or core/shell
structures.
Structural characterisation
The magnetic properties of nanoparticles are determined
by their physical structure: the size and shape of the
particles, their microstructure, the chemical phase or
phases that are present, the defects, and differences
between the crystal structure of nanoscale phases and
their bulk counterparts. Although individual structural
probes are sometimes capable of providing definitive
information about some aspect of the particles, in many
cases the results of a single probe are ambiguous,
inconclusive, or difficult to interpret. This may be true
even when the technique is reliable for bulk measurements. Consider, for example, an X-ray diffractogram of
nanoparticles believed to consist of a single phase (see
Fig. 13). Compared to a bulk standard, the peaks will
be broadened. In the case of subnanometre particles,
structural relaxation may change the lattice constant
measurably. Surface effects, negligible in a bulk crystal,
may play a significant role. These effects will result in
differences between the nanoparticle diffractogram and
the diffractogram of a standard bulk material, reducing
the utility of diffraction as a ‘fingerprinting’ technique.
Accordingly, a suite of complementary tools is
generally used to determine the physical characteristics
of nanoparticles. Self-consistence between these techniques increases the confidence in the accuracy of a given
characteristic. In some cases, the use of parameters
found by one technique can be used to refine parameters
found by another technique, thereby providing a better
picture of the particle assembly. This is especially true
of diffraction techniques (XRD and TEM) aiding
Mössbauer effect spectroscopy or synchrotron radiation
probes.
Willard et al.
Chemically prepared magnetic nanoparticles
complete descriptions of their use and applications,
interested readers should consult the references cited.
Conventional techniques
Published by Maney Publishing (c) IOM Communications Ltd
Mean particle and crystallite size
13 Diffraction patterns for sample of manganese zinc ferrite nanoparticles 12 nm in diameter (pattern a) and
bulk manganese zinc ferrite sample (pattern b):
although diffraction patterns look similar, EXAFS analysis of samples indicated that particles were multiphase; broad peaks of manganese zinc ferrite largely
mask iron oxide impurity phase
The advent of increasingly sophisticated synchrotron
radiation probes has been important in this regard.
Concurrent with the rapid increase in the intensity of
ultraviolet and X-ray beamlines available to the
scientific community has been the development of
increasingly powerful experimental and analytical techniques for structural determinations.
In the subsections below, the use of conventional tools
for determining the structure of magnetic nanoparticles
is discussed followed by the application of synchrotron
radiation to the problem. Finally, a few examples of
state of the art analyses are given. A subjective summary
of the relative applicability of the various probes
discussed here is given in Table 2. (A similar table of
structural probes, but without the emphasis on magnetic
nanoparticles, can be found in Ref. 224.) Note that
while this review includes a discussion of several
methods of structural characterisation, it is not detailed
enough to teach the use of these techniques. For more
The defining characteristic of nanoparticles is, of course,
their size. In principle, most structural probes are
sensitive in one way or another to the size of the
particles. In practice, however, nanoparticle ‘size’ is an
ambiguous concept. An assembly of nanoparticles
generally consists of some distribution of sizes, approximating a log normal distribution. This distribution has a
significant affect on magnetic properties; for example,
the superparamagnetic blocking temperature is strongly
dependent on the size and size distribution of the
particles. This distribution is also likely to be skewed,
often a log normal distribution approximates the
data.225 A log normal distribution is one in which the
number of particles is normally distributed as a function
of the logarithm of some measurement of the particle
size (typically the diameter for spherical particles). Two
parameters are required to specify a log normal
distribution. Often, the mean and standard deviation
of the distribution as a function of the logarithm of the
measured particle size are used; these are known as
the geometric mean and geometric standard deviation,
respectively. It should be noted that the geometric mean
is equivalent to the median of the size distribution as a
function of measured particle size.
Using N for the number of particles with radii r¡Dr,
r0 for the geometric mean, and s for the geometric
standard deviation, the formula for a log normal
distribution may be written
"
#
1
{(ln r=r0 )2
N(r)!
exp
Dr
(1)
r ln s
2(ln s)2
Please note that the literature does not always
agree regarding the meaning of the symbol s for log
normal distributions. In this paper, s is always the
quantity used in equation (1). Figure 14 shows typical
volume-weighted log normal distributions for small
nanoparticles.
Different techniques will thus yield different values for
the same sample, depending on the weighting scheme
implicit in the technique. For example, mean diameters
calculated from TEM images generally weight each
particle equally (‘number weighting’). This is in contrast
to techniques which weight each atom equally (‘volume
Table 2 Relative utility of various structural probes for characterising magnetic nanoparticles: one check indicates
technique that provides uncertain or incomplete information for wide range of materials or is only applicable in
especially favourable situations; three checks indicates technique that is widely (but not universally) applicable
and often gives fairly reliable information; two checks, of course, provides intermediate level of information
Size
Morphology
Phase identification
Site occupancy
Chemical composition
Kinetics
EM
DLS
XRD
ND
MS
ICP
XAS
XPS
EDXAS
DAFS
333
333
33
…
333
…
33
…
…
…
…
33
33
…
33
3
…
3
33
…
33
33
…
3
…
…
3
33
…
3
…
…
…
…
333
…
33
…
33
33
3
3
…
…
3
3
3
33
3
…
33
33
3
333
3
…
33
333
3
3
EM: electron microscopy; DLS: dynamic light scattering; XRD: X-ray diffraction; ND: neutron diffraction; MS: Mössbauer effect
spectroscopy; ICP: inductively coupled plasma; XAS: X-ray absorption specroscopy; XPS: X-ray photoelectron spectroscopy; EDXAS:
energy dispersive X-ray absorption spectroscopy; DAFS: diffraction anomalous fine structure.
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15 Nanoparticles comprising iron oxide shell on iron
core (TEM): difference in contrast between oxide and
metal allows shells to be clearly visible241
a r051.91 nm, s51.35; b r054.78 nm, s51.35; c
r054.98 nm, s51.11 (in c, there is not room to label
volume weighted mean size; it is identified by unlabelled line between Scherrer and EXAFS sizes)
14 Volume weighted log normal size distributions for
nanoparticles: mean sizes as found using volume,
Scherrer (XRD), EXAFS (extended X-ray absorption
fine structure), and # (number) weightings are indicated (note scales on x axes differ)
weighting’). For volume weighting, equation (1) must be
multiplied by an additional factor of r3. If particles are
not single crystals, either because of aggregation, multiple phases, or amorphous regions, it is also important to
note whether a technique yields a crystallite size or the
physical size of the particle.
For determinations of crystallite size, Scherrer analysis of X-ray diffractograms (XRD) is commonly
used.48,226,227 This technique relies on the broadening
of diffraction peaks due to the limited number of
diffracting planes. Because other factors, such as strain,
can broaden XRD peaks, the claim is often made
that Scherrer analysis provides a lower limit on mean
crystallite size. It must be emphasised, however, that this
is not the case for small nanoparticles in polydispersed
samples. The X-ray diffractogram intensities for a given
phase are proportional to the square of the volume of
the particle, thus selecting a ‘mean’ weighted heavily
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toward the high end of the distribution. In fact, it is
straightforward to demonstrate that for log normal
distributions with s>exp(!6/6)<1.5, the Scherrer formula (properly corrected for strain and instrumental
broadening) diverges, yielding an infinitely large mean
diameter! Values of the geometric standard deviation of
this size or greater are not unusual.225,228–230 Of course,
although the log normal distribution given in equation
(1) extends to arbitrarily large values of r, distributions
of actual particles do not. Nevertheless, the divergence
of Scherrer determined sizes for moderately broad ideal
log normal distributions should be taken as an indication that Scherrer analysis is not reliable for moderately
polydispersed samples, yielding more information about
the size of the largest crystallites than about the mean of
the distribution. Although more sophisticated techniques for extracting information regarding particle sizes
from XRD have been known for decades and are
capable of analysing polydispersed samples,231 the
requisite data quality and complexity of the techniques
have prevented them from being utilised in the area of
magnetic nanoparticles.
One of the most powerful tools for determining
particle size and morphology is transmission electron
microscopy (TEM). This technique will generally report
the total particle size (as well as crystallite size) and has
the virtue of providing details of the size distribution. In
many cases, aggregates of smaller particles can be
discerned. If the nanoparticles consist of more than one
phase and the phases provide enough contrast, then the
individual phases may also be visible (Fig. 15). For further
discussion of the capabilities of electron microscopy for
investigating the physical and magnetic structure of nanostructured materials, see the review article by Thomas
and Hütten;232 imaging of small metallic nanoparticles
is discussed by Ascencio et al.233 A few representative
examples of the application of TEM imaging to magnetic
nanoparticles are given in Refs. 191, 234–240.
Dynamic light scattering242 (DLS), also known as
photon correlation spectroscopy (PCS) or quasi-elastic
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Willard et al.
light scattering (QELS), is an important supplemental
technique for determining the sizes of particles in solution, particularly when the size distribution is narrow
and approximately log normal. Because of the ability
to size particles in solution (including aerosols), DLS
shows promise for in situ studies of nanoparticle
synthesis.243 The DLS technique is sensitive to total
particle size, and like Scherrer analysis, yields information which is weighted by the square of the particle
volume, although results are generally ‘converted’ to
volume or number weighting. It is important to note
that these converted values assume a particular form for
the distribution, and may differ substantially from the
true volume or number weighted mean size. Also, like
Scherrer analysis, DLS is not appropriate for samples
with broad log normal distributions.
Finally, extended X-ray absorption fine structure
(EXAFS), see below, also contains information about
particle size, particularly for small particles. As with
XRD, sophisticated techniques exist for extracting size
information from samples comprising well characterised
particles, such as metal structures on supported catalysts,244,245 but these techniques are not generally
applicable to moderately polydispersed samples of
magnetic nanoparticles. In analogy with Scherrer
analysis, a simple model based on the assumption of
spherical particles has been used.241,246–248 It has been
shown that this technique yields values smaller than the
volume weighted mean diameter for the crystallites, and
is thus a suitable complement to Scherrer analysis. The
‘EXAFS size’ is therefore a well defined value for all log
normal distributions for which the volume weighted
mean diameter is well defined, i.e. for all log normal
distributions with s>exp(!3/3)<1.78.
Figure 14 compares theoretically calculated mean
sizes, weighted in the same way as the techniques
described above, for typical log normal distributions of
small nanoparticles. Figure 14a is for small (4.0 nm
number weighted mean diameter) nanoparticles with
a moderately broad size distribution. Figure 14b and
c both exhibit number weighted mean diameters of
10.0 nm, but in the latter case the distribution is
relatively narrow. In all cases, the weighted means
follow the order: number weighted,EXAFS,volume
weighted,Scherrer. This order will be followed for all
distributions, even those which are not log normal,
except that it is possible for distributions with large
numbers of very small particles to yield an EXAFS value
smaller than the number weighted value. As a practical
matter, it should also be noted that in some cases it is
possible for the TEM to ‘miss’ small crystallites, leading
to a value somewhat greater than the true number
weighted mean.
As can be seen from Fig. 14a–c, the fractional difference between the mean diameter as determined by the
various techniques is strongly dependent on the width
of the distribution, but only weakly dependent on its
number weighted mean. Indeed, the ratio of the Scherrer
determined mean to the EXAFS determined mean is
a useful measure of width for moderately broad
distributions.
Like the mean, the width of a distribution can be
defined in a variety of ways. It may be taken as twice the
standard deviation of the distribution, or as half of the
range which encompasses 95% of the particles. These
Chemically prepared magnetic nanoparticles
definitions, although similar, are not identical if the
distribution is not Gaussian. Similarly, the width is often
specified as a fraction of ‘the’ mean size, which is of
course somewhat dependent on the way in which the
mean is defined and measured. These differences in
definition introduce difficulties in comparing the width
of size distributions presented in the literature. As a rule
of thumb, however, these definitions rarely differ by
more than a factor of two from one another. For
example, a distribution with a reported width of 5% of
the mean can be safely said to be narrower than one with
a reported width of 15% of the mean, regardless of the
definitions in use. If syntheses by different groups yield
widths reported as 20 and 30% of the mean, however,
the definitions used must be considered before concluding that the first distribution is actually narrower.
Phase identification
Although XRD is often considered the gold standard
for determination of crystal structure, it does possess
significant limitations. As discussed in the introduction
to this section, differences between nanoparticle and
bulk crystal structures in combination with peak broadening and multiple phases may make XRD results
inconclusive. Sometimes, it yields almost no information: very small particles less than a nanometre across,
core/shell structures with shells a few monolayers thick,
and amorphous phases all are difficult to discern using
conventional XRD. Certainly, XRD is still the method
of choice for confirming the presence of a single expected
phase with crystallite size greater than about 10 nm,
but the nature of magnetic nanoparticles often yields
samples that do not meet those criteria.
The high intensities and small spot sizes of electron
beams may make electron diffraction useful.236,240,249,250
Selected area electron diffraction (SAED or SAD)
sometimes allows discrimination of phases as small as
1–2 nm in size, but at this scale double diffraction,
calibration issues, and the close proximity of diffraction
spots arising from different phases often prevents an
unambiguous identification.232
Site occupancy
Magnetic materials with the same nominal chemical
composition, even with very high phase purity, often
differ markedly from one another due to a different
distribution of species or defects (i.e. atoms, ions, or
vacancies) among the available crystallographic sites.
This is especially true for ferrimagnetic materials
containing multiple sublattices. Spinel ferrites, for
example, have two sublattices with parallel coupling of
the magnetic moments within each sublattice and
antiparallel coupling between them. The result is that
the magnetisation of the material arises from the
difference in magnetisation of the sublattices. Often,
different species reside on each sublattice. If vacancies
are found preferentially on one sublattice, or if some of
the atoms on one sublattice are switched with those on
the other, the magnetisation may be altered substantially.251 It is thus very important to determine site
occupancy in these materials.
If the material possesses atomic ordering and the
crystallites are large enough that the peaks are not
prohibitively broad, then diffraction techniques are
often applicable. Even if the occupancy is random or
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quasirandom in nature, diffraction can often be used to
obtain the average structure. For example, XRD can
reveal the percentage of sites in the octahedral sublattice
of a spinel compound that are vacant.252 It cannot,
however, conclusively reveal the local distortions caused
by these vacancies, nor the tendency of vacancies to
cluster or disperse. In the case of one atom substituting
for another, however, XRD is only useful if the
substituted atom differs substantially in its atomic
scattering factor from the one being substituted. The
atomic scattering factor is primarily a function of the
number of electrons in the atom. Since in ferrimagnetic
oxide materials the substitution is often one first-row
transition metal for another (particularly manganese,
iron, cobalt, nickel, and zinc), this prevents XRD from
being used to find average site occupancy in many cases.
The same restrictions apply to electron diffraction.
Neutrons, on the other hand, are uncharged, and thus
interact predominantly with the nucleus of atoms rather
than the surrounding electrons. Since the coherent
scattering cross-section of nuclei is not correlated with
atomic number, elements with very similar atomic
scattering factors for X-rays may have very different
scattering cross-sections for neutrons. For example, iron
(with its isotopes present in their natural abundance) has
about 6 times the cross-section for coherent scattering
of thermal neutrons as does manganese, and more than
14 times that of cobalt. The atomic scattering factors for
X-rays for these three elements, in contrast, are within a
few per cent of each other. In some cases, therefore,
neutron diffraction (ND) can be useful for probing
differences in site occupancy to which XRD is not
sensitive.253,254 Since this is a diffraction technique, only
the average structure can be obtained. In addition,
neutrons possess a magnetic dipole moment, and thus
are sensitive to magnetic ordering (for some examples of
this use, see Refs. 255, 256). Unfortunately, due to the
small number of neutrons available for experimentation,
relatively large sample sizes are necessary for this
technique. This is sometimes difficult for investigative
studies in which nanoparticles synthesised by chemical
means, however it is not prohibitive.70,72,103
Mössbauer spectroscopy depends on the ability of
57
Fe nuclei embedded in a crystal to emit ‘recoil-free’
gamma radiation (i.e. momentum is conserved by the
recoil of a macroscopic number of atoms, rather than an
individual nucleus). Because essentially no energy is
lost to recoil, the energy distribution of the c-rays is
extremely narrow, and is dependent on the chemical and
magnetic environment of the 57Fe nuclei. To create a
spectrum, the source of the photons is vibrated, imparting a time dependent Doppler shift to the photons.
These photons can then undergo the inverse process in a
sample, in which those of the appropriate energy are
absorbed by 57Fe nuclei (‘resonant absorption’). Thus,
information is conveyed regarding the local environment
of 57Fe in the sample, generally including coordination
number and oxidation state. Because Mössbauer spectroscopy also depends on the magnetic environment, it is
an important tool for investigating iron containing
nanoparticles.227,239,257–264
Remarkably, thermal analysis techniques such as
thermogravimetric analysis (TGA), differential thermal
analysis (DTA), and differential scanning calorimetry
(DSC) have been used to determine site occupancies.
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Each technique measures the value of a physical
parameter as the temperature is changed in a controlled
fashion. For TGA, the parameter is the mass of the
sample (outgassing or oxidation accounts for the mass
changes); for DSC the parameter is the power required
to keep the sample at the same temperature as a
reference material; for DTA the temperature of the
sample relative to a reference material is measured.
Some site occupancies in magnetic nanoparticles have
been deduced from DSC and TGA,265 since the
temperature at which ions oxidise (e.g. Fe2z going to
Fe3z) is dependent on the local environment of the
ion.266 Depending on the synthesis technique and
particle size, however, this effect may be obscured by
the effects of materials adsorbed on to the surface of the
nanoparticles.
Chemical composition
In addition to size, phase, and site occupancy, the
magnetic properties of nanoparticles depend on the
chemical composition, i.e. the fraction of each element
that is present. There are a number of techniques for
determining chemical composition accurately. Inductively coupled plasma–atomic emission spectroscopy267
(ICP–AES) is widely used because of its sensitivity, wide
applicability, and ease of use. In this technique, a plasma
torch is used to atomise, ionise, and excite the atoms in
a solutionised sample, which are then quantified by the
intensity of their characteristic emissions. The sensitivity
of the technique varies considerably between elements,
but is generally accurate to better than 2% for the
main constituents of magnetic nanoparticles. A notable
exception is oxygen: environmental oxygen prohibits
the direct measurement of the amount of oxygen in the
sample. If all other elements can be accounted for, it is
possible to estimate the amount of oxygen present by
subtracting the mass of the other elements from the
total mass of the sample. Because of the difficulties in
measuring the mass of sample in solution, this method
frequently yields only a rough estimate of oxygen
content.
Another family of techniques for determining chemical composition employs the high energy electron beam
of an electron microscope to generate secondary
electrons in the sample, causing the formation of holes
and the subsequent emission of X-rays when the holes
are filled. These X-rays are measured by energy dispersive spectroscopy (EDS or EDX, the X standing for
X-ray analysis) or by wavelength dispersive spectroscopy (WDS or WDX). When an instrument is optimised for determining chemical composition rather than
for imaging, this technique is sometimes called electron
probe microchemical analysis (EPMA). These techniques are more sensitive to heavier elements than lighter,
with the limit for quantitative analysis depending on
the instrument, sample, and detection method (oxygen
and carbon fractions are often achievable). Accuracy
of better than 2% is readily obtainable. Recently, with
a field emission gun electron source, EDX has been
shown to have subnanometre spatial resolution.268 More
generally, resolutions of under 10 nm are readily
obtainable, allowing the chemical composition of
individual nanoparticles to be determined. For further
discussion of this technique as well as other methods
for determining chemical composition using electron
Willard et al.
Chemically prepared magnetic nanoparticles
microscopy (e.g. electron energy loss spectroscopy), see
the review by Mackenzie.269
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Synchrotron based techniques
The suite of techniques discussed above can provide
considerable structural information about many types of
magnetic nanoparticles. There are, however, significant
gaps. Diffraction, for example, can provide only very
limited information about amorphous phases. Likewise,
the structure of nanoparticle materials consisting of
multiple chemical phases may resist solution via the
above techniques. Fortunately, techniques that utilise
synchrotron radiation are well suited to both of these
scenarios.
About forty dedicated ‘light source’ synchrotrons on
four (soon to be five) continents are currently available
to the scientific community. Although each facility has
different capabilities, they generally provide broad
spectrum ultraviolet and X-ray radiation that is more
than 6 orders of magnitude brighter than a conventional
X-ray tube. These characteristics allow high resolution
spectroscopy to be conducted in a reasonably short
time frame, sometimes even allowing the kinetics of a
synthesis to be observed in situ. Although there are a
variety of modes in which this spectroscopy can be
conducted, many of which will be discussed below, the
essential feature of these spectra is that they provide
information about electronic structure and/or local
environment that is completely element specific.
Because the information is inherently local, amorphous
materials can be investigated; because the information is
element specific, the structures of materials consisting of
multiple phases, or of those exhibiting point defects, can
often be clarified.
Modes of data collection
X-ray absorption spectroscopy (XAS) experiments filter
the photons emerging from the synchrotron with a
monochromator so that only a narrow band of energies
impinge on the sample at any given time; this energy is
then scanned through the absorption edge to produce
the spectrum. The intensity of transmitted photons, yield
of fluorescent photons, and/or total electron yield, may
be measured independently. Total electron yield is
surface sensitive, with most of the signal coming from
the first few tens of nanometres of material (depending
on the material and the energies involved). Fluorescence
is less surface sensitive, typically probing to a depth on
the order of ten micrometres, and is suitable for
extremely dilute samples or those that are too thick for
transmission. Transmission is sensitive to the entire
thickness of the sample, but requires the sample to be on
the order of several micrometres thick.
In emission techniques, a monochromator is still used,
but the energy is left fixed. Instead, the distribution of
kinetic energies produced by the emitted electrons is
recorded, providing information about the electronic
structure of the material. This is known as X-ray or
ultraviolet photoelectron spectroscopy (XPS, UPS), or
sometimes as electron spectroscopy for chemical analysis (ESCA).
Energy dispersive X-ray absorption spectroscopy270,271
(EDXAS or DXAS), utilises a curved polychromator
to send photons through the sample with a range of
energies corresponding to different diffracted angles, so
16 X-ray absorption spectroscopy of iron foil near K
edge: dotted line divides XANES (X-ray absorption
near edge structure) from EXAFS (extended X-ray
absorption fine structure) region
that an entire spectrum can be collected simultaneously
with a linear or areal detector. The EDXAS technique
holds promise for investigating the kinetics and mechanisms of reactions on the sub-second time scale.272–276
The high intensity and selectable energy of synchrotron radiation can also be used to advantage in XRD;
this can be combined with XAS in a number of ways.
In diffraction anomalous fine structure277,278 (DAFS)
experiments, for example, the angle of diffraction is
varied simultaneously with the incident photon energy in
such a way that the same Bragg peak is being sampled at
different energies. The result is an element specific
spectrum that is sampling only atoms in sublattices that
obey the Bragg condition for that peak. In this way, the
local environment of an element in a particular phase,
or, under favourable conditions, a particular type of
lattice site,279–282 can be probed. A comparison of
DAFS and XAS analyses of nanoparticulate metals is
given by Bazin et al.283
In DAFS, many energies are sampled at one Bragg
peak. In anomalous diffraction, entire diffractograms
are sampled at a small number of energies. This
technique has recently been used to determine the site
occupancy not only by element, but by valence as
well.284
Data interpretation and analysis
The interpretation of synchrotron based X-ray absorption spectra is often not straightforward. For example, a
portion of the X-ray absorption spectrum for iron is
shown in Fig. 16. The binding energy of the K electrons
in iron is 7112 eV; therefore, the absorption shows a
large jump (the ‘edge’) as the energy of the incident
photon exceeds that energy. This binding energy will
increase by a few electronvolts if the iron is oxidised
and the edge will shift accordingly; thus the position
of the edge can be used to estimate the oxidation state.
The detailed structure within about 30 eV of the
edge, known as X-ray absorption near edge structure
(XANES), is generally interpreted in terms of core
electron transitions to available energy states (either
above or below the Fermi level); XANES therefore
yields information on bonding and the local symmetry
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of the atoms surrounding the absorber. The features
revealed by extended X-ray absorption fine structure
(EXAFS), i.e. the quasi-oscillatory features above
30 eV, are due to coherent scattering off of atoms in
the local environment up to a distance of several
angstroms from the absorbing atom. Depending on the
sample, type and region of spectrum, and desired
information, several techniques are used to analyse this
information. (References immediately after the technique name are to applications of the technique to
magnetic nanoparticles.)
Published by Maney Publishing (c) IOM Communications Ltd
Fingerprinting285,286
The simplest method of analysis is to compare the
spectrum with a known reference material (the ‘empirical standard’). Of course, if the material is crystalline
and sufficiently similar to the reference, XRD can
perform this task without the need for a synchrotron.
On the other hand, nanoparticle materials are often
similar on a local scale to a bulk analogue, but lacking
(or different) in long range order. If the XANES (or the
XPS) of the material is similar to the reference, it
suggests that the immediate environment of the atoms
is similar; if the EXAFS is similar, then the local
environment may be similar out to several angstroms.
Comparison to theory264,287,288
This may represent either qualitative assignments of
particular spectral features to particular causes (e.g. a
particular electronic transition or backscattering from
a particular coordination shell) or comparison to an
ab initio calculation289,290 of a spectrum (a ‘theoretical
standard’).
Curve fitting to theoretical standard291,292
This technique is used most often to analyse EXAFS,
including the oscillatory portion of DAFS.293 In this
technique, a model of the material, with several
parameters left free, is hypothesised.
For example, a sample may be hypothesised to consist
of nanoparticles composed of bcc iron mixed with
Fe2O3. Free parameters might include the size of the
particles and the fraction of each phase present. A
theoretical standard is then calculated for reasonable
values of the free parameters; theoretical expressions can
be used to compute how the spectrum changes for
different values of the parameters. Subsequently, the
values of the free parameters are optimised by a least
squares fit of the modified theoretical standard to the
data. A poor fit indicates that the model is poor; a good
fit indicates that the model may be good. If the model
is good, then the values of the free parameters that
produce the fit are expected to reflect the actual structure
of the material.
When used judiciously, this technique is among the
most powerful and can be used profitably even when the
material is made up of multiple phases. It is, however,
prone to misinterpretation if used carelessly, partly
because more than one model may correspond to the
same spectrum or similar spectra (the model that does
not correspond to the material is often termed a ‘false
minimum’). For this reason, an EXAFS fit of a single
coordination shell of a single sample under a single set
of conditions is generally suspect. There are, however,
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several methods of reducing the likelihood of false
minima. For example, the probability of a good fit being
achieved with a poor model is considerably reduced if
more than one absorption edge is refined simultaneously. Likewise, fitting more than one coordination
shell simultaneously is advisable, at least for crystalline
phases, because this will reduce the correlation between
parameters (a single-shell fit, for example, cannot
distinguish the coordination number from the EXAFS
quantum efficiency S 2o ) and because it will act as a
powerful constraint on valid models. Of course, it is
helpful if the number of free parameters can be reduced
by using the results of other probes. Chemical composition, for example, can be determined reliably by
methods given in the subsection of that name, above.
The chemical composition, in turn, can be used to
constrain site occupancies of materials exhibiting substitutional disorder.
It is also worth noting that analyses of EXAFS by the
curve fitting method are almost always dominated by
systematic error; this error may stem from limitations of
the ab initio calculation, the choice of free parameters,
the values chosen for fixed parameters, the method used
to extract the EXAFS oscillations from the raw data,
or the way in which the samples were prepared for
measurement. Fortunately, these sources of systematic
error do not vary much for a set of samples prepared
and analysed in the same way. Thus, if a series of
measurements and fits are performed on a sample while
varying some extrinsic parameters (e.g. temperature,
pressure) or measurements are performed on a series of
samples differing in some way (e.g. nanoparticle size,
composition variation), the differences between the
values of the parameters as determined by the fits are
much more reliable than the values themselves. This is a
particularly valuable strategy if one of the samples has
been well characterised by another method (i.e. it is an
empirical standard), since the degree of systematic error
can then be ascertained.
Principal component analysis294 (PCA)
This technique requires a family of samples presumed to
have differing (but unknown) proportions of chemical
phases present, some (or all) of which may be unknown.
For example, a sequence of core/shell nanoparticles
could be prepared in such a way that the ratio of shell
volume to core volume varies. As another example, an
aging study could be performed on metallic nanoparticles: the ratio of oxide to metal could be expected to
increase over time. The PCA technique decomposes the
spectra of such families into components: mathematically
orthogonal functions from which all of the sample
spectra can be constructed. The number of components
required to reproduce all of the spectra to within
reasonable experimental error is the number of distinct
phases present in the family of samples. If all the phases
are unknown, PCA will yield only the number of phases
present. If the identity of each of the phases is known
and empirical or theoretical standards are available,
then PCA reveals the fraction of each phase that is
present. Finally, if the structures of some phases are
known and others unknown, PCA may be combined
with curve fitting to a theoretical standard; this combination is sometimes called ‘residual phase analysis’.
Willard et al.
Chemically prepared magnetic nanoparticles
The PCA technique has recently been used to analyse
EXAFS,294–296 XANES,274,276,297,298 and XPS.299,300
Selected examples of synchrotron
characterisation
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Multi-edge modelling of site occupancy
As described above, ferrimagnetic materials derive their
magnetic properties from the interaction between
magnetic cations located on two sublattices. In the case
of manganese zinc ferrite nanoparticles, XRD is not well
suited for determining on which sublattice each metal
species resides, since the atomic scattering factors of
manganese, zinc, and iron are very similar. Mössbauer
spectroscopy can determine the site occupancy of the
iron atoms, but not the other two species. In the past
several years, EXAFS has been used to observe
differences in site occupancies for all elements between
samples (e.g. as a function of synthetic method,291
annealing,301 or milling302), but comprehensive quantitative occupancies for this three-cation mixed ferrite
have been difficult to obtain.
For materials containing multiple metals, the EXAFS
of each edge has traditionally been analysed separately.
Ideally, this approach provides site occupancies that are
consistent with the stoichiometry of the sample. In
practice, uncertainties and correlations present in the
analysis may lead to ‘best-fit’ occupancies which are
prima facie incorrect, requiring, for example, more than
100% of one kind of site to be occupied. To take full
advantage of the redundant information present in
multiple spectra, a simultaneous refinement of multiple
spectra can be performed.302 Calvin et al.292 have
applied this to manganese zinc ferrite nanoparticles by
first using ICP–AES to determine the stoichiometry of
the samples. Assuming sample composition and site
occupancy did not vary significantly from particle to
particle, this stoichiometry was then used to reduce the
number of free parameters related to site occupancy to
two: the fraction of manganese ions on tetrahedral sites
and the fraction of zinc ions on tetrahedral sites. By
reducing the number of free parameters, the precision
of the results is improved: site occupancies for most
samples were determined to within ten percentage
points.
DAFS and site specific valences
Another approach to investigating ferrimagnetic materials is offered by DAFS. Because the symmetry of
the sublattices in a ferrimagnetic material differ, each
contributes to different (albeit overlapping) subsets of
the diffractogram. For example, the octahedrally coordinated sublattice in magnetite (Fe3O4) contributes to
the (222) and (444) reflections, while the tetrahedral site
contributes to the (022), (224), and (444) reflections.
Thus, XAS collected at the (222) reflection contains
information about the octahedral sublattice only, while
the (022) and (224) reflections contain information
about just the tetrahedral sublattice.
Frenkel et al. used this property to study the valence
distribution in magnetite.280 Figure 17 shows their data
in the XANES region of the spectra. The difference
between the spectra is notable, and reflects the differences in symmetry of the local environment and the
different valences of cations on the two sublattices. In
17 DAFS (diffraction anomalous fine structure) analysis
of magnetite: trough near 7118 eV in (222) reflection
corresponds to trough near 7130 eV in other reflections – large shift is indicative of lower average
valence in octahedral sites (figure adapted from
Ref. 280)
particular, the higher average valence of the iron on the
tetrahedral sublattice is clearly indicated by the large
energy shift between the octahedral and tetrahedral
spectra. The authors of the study then proceeded to
use curve fitting of the (222) spectra to a theoretical
standard to yield quantitative information on the local
environment of the iron cations on the octahedral
sublattice.
Using PCA and empirical standards to analyse mixtures
Although it is possible to analyse mixtures of a few
components with methods such as fitting EXAFS to
theoretical standards, it can be quite tedious if there are
a large number of possible components to choose from.
One solution is to use PCA to identify the component
phases, and then proceed with more traditional fitting
techniques to refine the parameters.
Ressler et al. recently used this approach on mixtures
of nanoparticulate manganese compounds generated by
internal combustion engines.298 Although their interest
was environmental, the challenges are not unlike those
sometimes encountered in magnetic nanoparticle syntheses: according to the authors, ‘X-ray diffraction
measurements yielded little or no information due to a
combination of insufficient sample mass, amorphous
nature of the particulate matter, and/or small particle
size.’ Principal component analysis requires samples that
differ in non-trivial ways; the study authors accomplished this by collecting 12 samples from engines
operating under various conditions. The PCA indicated
that the 12 XAS spectra could be constructed out of
just three components, implying just three manganese
containing compounds were present in the exhaust.
The study authors then examined the XANES of each
sample to establish the average valence of the samples;
this, along with ESCA results, allowed them to narrow
the likely compounds to 10. Of these 10, only Mn3O4,
MnSO4, and Mn5(PO4)[PO3(OH)]2?4H2O could be
constructed from the components present in the
samples, suggesting that these were the three compounds
present.
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Future trends in synchrotron characterisation of
magnetic nanoparticles
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As the synthesis of magnetic nanoparticles has become
more sophisticated, moving from ball milling methods
which generate a broad size distribution of disordered
single phase particles to wet chemical techniques which
show promise for producing nearly monodisperse
particles with a high degree of structural order, so have
the techniques used to characterise them. Increasingly,
synchrotron radiation has played a role, with both
experimental and analytical techniques rapidly advancing and proliferating. High intensity sources, for
example, have stimulated the development of DAFS,
enhancing the element specificity of XAS with the
ability, in many cases, to probe individual phases. The
EDXAS technique is now allowing the progress of
synthesis reactions to be monitored at a scale of seconds
or below; this technique has as yet been little used with
magnetic nanoparticles, but that is likely to change as
researchers broaden their focus from the end-product of
a synthesis to its mechanism and kinetics. Curve fitting
to theoretical standards is becoming increasingly sophisticated, with simultaneous multi-edge refinements292,303
and models that account for the size and shape of
nanoparticles244–246 beginning to appear. Finally, PCA
promises to yield significant structural information from
materials that had previously resisted characterisation.
Magnetic properties of nanoparticles
This section of the review emphasises the magnetic
characteristics important to nanoparticles. The following subsections provide a general overview of the
relevant parameters, behaviour, and experimental tools
used to examine magnetic properties. Additionally,
selected examples from recent literature have been
included as examples of the types of research being
conducted and to emphasise the strengths of many
characterisation techniques.
Magnetism of fine particles
In general, the magnetic behaviour of nanocrystals is
dependent on the physical properties of individual
particles and their environments. The most important
physical characteristics include chemical composition,
particle size, particle morphology, intrinsic materials
parameters (e.g. magnetocrystalline anisotropy, saturation magnetisation, etc.), surfaces/interfaces, and particle size distribution. Most of these parameters are
easily obtained (or are relatively unimportant) for bulk
magnetic materials; however, as described in the
previous section, this is not necessarily true for
nanoparticles.
The terms pertaining to the environment of the
nanoparticles are generally controllable during experimentation (albeit occasionally with difficulty). These
terms include temperature, applied magnetic fields,
measurement time, and interparticle distance. In many
experiments, even the sequences in which fields and
temperatures are changed are quite important. All of
these factors lead to potentially confusing results. Due
to the large amount of existing data, comparisons of
bulk magnetic material behaviour can be made to
alleviate some of the confusion in nanoparticle analysis.
Although, when the particles are isolated and sufficiently
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small, magnetic responses similar to bulk magnetic
materials fail to describe their performance.
When the critical length scales for physical properties
are similar in size to the structural length scales of the
material, interesting physical phenomena arise. In the
case of exchange coupled magnetic materials, this length
is 1–100 nm and called the ‘exchange correlation length’.
For this reason, nanoparticulate materials have provided an interesting magnetic phenomenon that has
been studied over the past half century. However, the
technological importance of miniaturisation (especially
in the burgeoning fields of nanoelectronics and bioelectronics) requires a better understanding and control of
producing these materials with reliable properties. Size,
shape, composition, and distributions of these qualities
about their means will determine the success of these
materials for application.
In recent years, new processing techniques and novel
use of proven characterisation techniques have advanced
our knowledge of magnetic nanoparticles. However,
the recent technological attention adds to over half a
century of basic research in this field. A number of
excellent reviews have been published over the years that
encompass many of the aspects of the topics contained
herein.304–306 The following subsections introduce definitions of magnetic quantities (see Appendix also) and
forms of magnetic behaviour that are important to the
further discussion of magnetic nanoparticles.
Magnetic materials parameters
Intrinsic and extrinsic materials properties are generally
easy to distinguish from each other for bulk materials.
Intrinsic characteristics are generally invariant with
respect to microstructure of the material, depending
mainly on the crystal structure and chemical composition (or stoichiometry) of the material. Examples of
intrinsic magnetic properties include Curie temperature
Tc, saturation magnetisation Ms, exchange stiffness A,
and magnetocrystalline anisotropy K. Extrinsic parameters, on the other hand, depend upon the microstructure of the material and are naturally affected by
the size, shape, and morphology of the particles.
Extrinsic magnetic properties include coercivity Hc,
remanent magnetisation Mr, and magnetic susceptibility
x. However, this clear demarcation is not necessarily
the case for nanoparticles, where the large amount of
surface area may convert conventionally intrinsic
properties into extrinsic properties due to surface
relaxation and broken bonds at the particle surfaces.
This has been demonstrated by Sun et al., where nickel
nanowire arrays exhibit reduced Curie temperatures
when the wire diameter is reduced below 100 nm.185 As
might be expected, the deviations from the bulk intrinsic
properties increase as the particle size is reduced.
Paramagnetism
All materials respond to applied magnetic fields. Those
that possess strong interaction with magnetic fields are
generally called magnetic, however many other types of
phenomenon are more common than this class, more
properly called ferromagnetic or ferrimagnetic materials.
Paramagnets are one of the other classes of magnetic
materials that are especially important due to the close
relation of paramagnetism to ferromagnetism.
Willard et al.
Paramagnetic materials possess unfilled electronic
shells giving them a permanent magnetic moment. This
moment consists of contributions from the spin and
orbital momentum of the electrons of the atom.
Paramagnets differ from the more technologically useful
ferromagnetic materials in the fact that their magnetic
moments do not interact strongly with each other or
with applied magnetic fields. The magnetic moments
tend to align with an applied magnetic field in a
stochastic manner, yielding a slightly positive magnetic
susceptibility (y1026). The temperature dependence of
the susceptibility for many paramagnetic materials
follows the well known Curie law (x5C/T, where C is
the Curie constant – a term dependent on the properties
of the paramagnet).
Chemically prepared magnetic nanoparticles
18 Non-interacting particles (compositionally invariant
and single phase) as function of particle size, indicating magnetisation reversal mechanism regimes at isothermal temperature T0
Published by Maney Publishing (c) IOM Communications Ltd
Ferromagnetism/ferrimagnetism
More complex, and interesting, magnetic phenomena are
found when the magnetic moments on adjacent atoms
interact. Ferromagnetic materials have interactions causing the alignment of the magnetic moments. These materials have high susceptibility (up to 106) and net magnetic
moments even in the absence of an applied field.
Still more complex, yet equally interesting from a
technological standpoint, are ferrimagnetic materials.
These materials consist of antiparallel arrangements of
the magnetic moments, yet the material maintains a net
magnetisation. This is due to either the numbers of
moments being different in each direction, or the size of
the magnetic moments in alternating directions being
different (or both). Ferrimagnets have high susceptibility
(up to 106) and net magnetic moments even in the absence
of an applied field, much the same as ferromagnets. At
sufficiently high temperatures, the magnetic ordering of
both ferromagnetic and ferrimagnetic materials is disturbed, causing a change to paramagnetic behaviour (at
the Curie temperature, as shown in Fig. 19c).
The most important technological bulk materials have
ferrimagnetic or ferromagnetic behaviour with their high
susceptibility and net magnetisation. Common examples
of technologically important ferromagnetic materials
include iron, cobalt, nickel, and their alloys and rare
earth intermetallics (i.e. Nd2Fe14B and Sm2Co17).
Prevalent ferrimagnetic materials include iron based
oxide materials with the inverse spinel crystal structure
(called ferrites), barium based or strontium based
magnetoplumbites, and rare earth/iron based oxides
(called garnets). As a result of their excellent bulk
magnetic properties, these materials are synthesised as
nanoparticles for magnetic applications.
Ideal particle systems
The magnetic behaviour of nanoparticles is diverse and
complicated. The characteristics of particles and their
environments will be discussed below in the simplest
manner. This means a discussion of spherical, monodisperse particles without magnetic interactions between
adjacent particles or agglomerations. Then, the
‘Mechanisms for complicating magnetic behaviour’,
e.g. interparticle interactions, particle size distributions,
will be discussed.
Single domain particles
Bulk ferromagnetic materials are generally polycrystalline with each grain consisting of thousands of magnetic
domains separated by boundaries called domain walls.
In the simplest case, the magnetisation in adjacent
domains continuously changes direction by 180u over
the width of the domain wall. The domain wall is a
defect in the material that requires energy to form. As
mentioned above, the multiple domains form in a grain
to alleviate the magnetostatic field exiting the grain.
Figure 18a shows a multidomain particle with 90u
domain walls. It should be noted that the magnetic
domain walls have significant width, generally in the
tens to hundreds of nanometres.
In many respects, the most technologically important
characteristic of magnetic materials is the process of
magnetisation reversal. Whether the material requires
very little field to reverse the magnetisation (i.e. a soft
magnet) or maintains a single magnetisation direction
to very high magnetic fields (i.e. a hard magnet), the
magnetisation reversal determines the performance of
the material. This is true for bulk magnets and magnetic
nanoparticles alike. In bulk magnetic materials, the
nucleation and motion of domain walls through the
material control the reversal. The ease with which
the domain walls move through the material when a
magnetic field is applied determines the application for
which the material is best suited. Pinning of domain
walls on grain boundaries, voids, or inclusions causes an
increase in the field necessary for magnetisation reversal
by hindering the motion of domain walls. The nucleation of magnetic domains arises to minimise the
magnetostatic energy. As the size of a bulk ferromagnet
is reduced, the nucleation of reverse domains becomes
more difficult because of the large magnetostatic energy.
A small ferromagnetic particle made up of a single
spherical grain has a magnetostatic energy with the form
(pm0M 2s r2w)/9 and the domain wall energy (2pr3c)/w,
where m0 is the permeability of free space, r is the
particle radius, c is the domain wall energy per unit area,
and w is the domain wall width. Minimising the total
energy with respect to the particle radius yields a
relation, in terms of the materials parameters, for the
critical radius under which a domain wall will not
form309
rcrit ~(324AK)1=2 =(m0 Ms2 )
In a practical sense, particles below this limit consist
of a single domain that thermodynamically cannot
support the formation of a domain wall (as indicated
by Fig. 18b). This requires magnetisation reversal by
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rotation of the magnetisation into the applied field
direction.
The preferred direction of the magnetisation of a
ferromagnetic material for instance, in the absence
of an applied field, is determined by magnetic anisotropies, which arise from many sources, including
the shape of the magnet, its crystalline structure,
chemical composition, the strain in the material and
effects of surface chemistry. Their origins are quite
different and affect the characteristics of magnets
of all sizes, particles and bulk alike. Generally, many
types of anisotropy are combined to fully describe
nanoparticles.310
Shape anisotropy arises from the field formed by the
magnetisation of the material (a consequence of the
Maxwell equations).311,312 It is described analytically for
ellipsoids of revolution, with a uniaxial form for prolate
ellipsoids (i.e. acicular particles)
1
Ms2 (Nb {Na ) sin2 h
E~
2
Published by Maney Publishing (c) IOM Communications Ltd
where h is the angle between the magnetisation and the
applied field, Ms is the saturation magnetisation, and
Nb and Na are the demagnetising factors for the long
and short axes of the ellipsoid, respectively. Spherical
particles have isotropic shape anisotropy, which is easy
to visualise since all directions are equal. Slight aspheric
distortions of near spherical particles yield inconsequential differences in the shape anisotropy until the length
of the aspheric axis exceeds approximately 30% of the
sphere radius.
The magnetocrystalline anisotropy forms due to spinorbital coupling and, in general, possesses the symmetry
of the crystal structure of the magnet. Uniaxial
anisotropy for tetragonal, rhombohedral, and hexagonal
crystal structured materials has the form
E~K1 sin2 hzK2 sin4 h
while cubic materials have energies described by
E~K1 (a21 a22 za22 a23 za23 a21 )zK2 (a21 a22 a23 )
where ai are the direction cosines for the magnetisation
with respect to the Cartesian directions of the cubic
primary axes and h is the direction of the magnetisation
with respect to the uniaxial direction. The angles used
for magnetocrystalline anisotropy are in relation to the
lattice vectors with energy minima corresponding to
specific crystallographic directions. An example of the
uniaxial energy density is shown in Fig. 19a and b. The
lowest energy corresponds to the unique crystalline axis
found in the tetragonal, rhombohedral, or hexagonal
crystal systems. The strain derivative of the magnetocrystalline anisotropy provides additional anisotropic
response through the magnetostriction coefficient ls.
For a single axis of stress, this term is uniaxial, with the
form
3
E~
l s sin2 h
2 s
where s is the stress on the material.
Although shape, magnetocrystalline, and magnetostriction anisotropies are the most common terms,
additional forms of magnetic anisotropy have been
examined, including one important to nanoparticles.
Due to the large surface/volume ratio, the relaxation of
atoms at the particle surfaces and the interaction of
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a uniaxial anisotropy energy density surface for
blocked single domain particle (K is magnetic anisotropy, V is volume, and kT0 is Boltzmann energy term);
b cross-section of energy density surface showing two
energy wells at magnetic easy axes; c typical saturation magnetisation as function of temperature
(H5constant); d hysteresis loops for ferromagnets
below Curie temperature Tc
19 Schematic diagrams for single domain particles
ligands with atoms on the surfaces of the particles can
have a significant effect on the anisotropy of particles.
A simple, elegant model of the hysteretic behaviour of
single domain particles was developed in the late 1940s.
This Stoner–Wohlfarth model313,314 considers the energy
due to the magnetocrystalline anisotropy, shape anisotropy, and magnetostatic interactions of the particle as a
function of a magnetic field applied at a fixed angle from
the magnetic easy axis. As the applied field is increased,
the magnetisation is coherently rotated into the field
direction.
Calculations based on the Stoner–Wohlfarth model
are presented in Fig. 20. The ideal cases of isolated,
monodisperse, non-interacting nanoparticles, both single domain and superparamagnetic are shown. For an
assembly of non-interacting particles with aligned
uniaxial anisotropy directions, a square hysteresis loop
with high coercivity and remanent magnetisation is
found (Fig. 20, curve a). An assembly of randomly
oriented uniaxial anisotropy directions, on the other
hand, exhibits lower remanence and coercivity (Fig. 20,
Willard et al.
Chemically prepared magnetic nanoparticles
Published by Maney Publishing (c) IOM Communications Ltd
20 Stoner–Wohlfarth model calculations of hysteresis
loops for assembly of aligned single domain particles
(curve a) and randomly oriented single domain particles (curve b): Langevin function calculation of
assembly of superparamagnetic particles is also
shown (curve c)
curve b). The Stoner–Wohlfarth model works well for
single domain particles; however, as the particle size
is reduced further, the magnetostatic and anisotropic
magnetic energies are no longer the only two of
consequence – thermal energy plays an increasing role.
As demonstrated in Fig. 20, curve c and discussed in the
next subsection, this thermally activated magnetisation
reversal, or superparamagnetic behaviour, exhibits no
remanent magnetisation, no coercivity, and the necessity
of very large fields for saturation of the magnetisation.
Superparamagnetism
Superparamagnetism is a magnetisation reversal
mechanism for fine particles driven by thermal
energy.315 At large particle sizes, the magnetisation is
confined to specific directions determined by the shape,
crystal structure, lattice strain, etc. As the particle size
is reduced, stochastic thermal fluctuations exceed the
energy barrier keeping the magnetisation in its energy
well (Fig. 18d). Similar to a ferromagnetic material, the
magnetic moments of adjacent atoms remain aligned
and acting as one large magnetic moment for the whole
particle (i.e. exchange coupled), however their direction
is not fixed (as indicated by the isotropic energy density
in Fig. 21a). An assembly of these particles with ‘super
moments’ acts like a paramagnetic material, hence the
term superparamagnetism. However, this should not be
confused with the magnetic material having ‘supermagnetic’ properties. In the end, superparamagnetism is
not terribly useful for technological applications.
The thermal activation over the magnetic anisotropy
energy barrier takes the form
f ~f0 exp({Eb =kT)
with Eb as the energy barrier (equal to KV in the absence
of an applied field), f0 is an attempt frequency on the
order of 109 Hz, and kT is the Boltzmann energy term.
When the time for activation over the energy barrier is
long compared to the experimental measurement time,
the superparamagnetic particles are ‘blocked’. The
blocking of superparamagnetic particles occurs below
a temperature aptly named the blocking temperature
TB. However, the blocking temperature is dependent
on the time of measurement, applied magnetic field,
and particle size distribution, making it an ill defined
parameter.
a nearly isotropic energy density surface; b typical
magnetisation as function of temperature for small
fixed fields, H5constant (ZFC is zero field cooled; FC
is field cooled) – particles are considered blocked
below TB; c ‘hysteresis’ loop for superparamagnets
above blocking temperature TB
21 Schematic diagrams for superparamagnetic particles
Below the blocking temperature, the magnetisation as
a function of temperature and magnetic field are similar
to the curves found in Fig. 19c and d, respectively. The
particles possess coercivity, remanent magnetisation,
and saturation magnetisation. However, in contrast to
the single domain particles, the Curie temperature is
rarely exceeded prior to the blocking temperature upon
heating. Therefore, superparamagnetic behaviour takes
over long before significant reduction of saturation
magnetisation as the temperature is raised. Figures 21b
and 21c show the magnetisation changes typical of
superparamagnetic particles above the blocking temperature and the characteristic magnetisation versus
magnetic field curve with neither remanence nor
coercivity.
The size scale between superparamagnetism and single
domain particles is best described by its magnetisation
reversal behaviour. The constant fluctuation of the
superparamagnetic particles is not entirely present,
however magnetic relaxation does occur. The coherent
rotation mechanism of the single domain particles does
not describe the particles, although they maintain
hysteretic behaviour. This size range intermediate to
superparamagnetic and single domain particles exhibits
incoherent rotation of the magnetisation, one example
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22 Diagram for blocking temperature as function of particle diameter for constant measurement time t and
magnetic anisotropy K: if measurement time is
decreased, then blocking temperature is increased for
given grain size (indicated ‘a’) or if magnetic field H
is raised then blocking temperature is lowered for
given grain size (indicated ‘b’)
of which is the magnetisation curling mechanism (see
Fig. 18c).316 Magnetic curling has been examined by
Ferré and co-workers on nickel and cobalt nanowires
where the competing shape and magnetocrystalline
anisotropies are at 90u angles to each other.182
Isolated particles
The magnetisation of an assembly of superparamagnetic
particles has the same dependence on applied magnetic
field as a paramagnetic material, replacing the atomic
magnetic moment of the paramagnet with the particle
magnetic moment of the superparamagnet. The
Langevin function describes this behaviour
L½b~coth ½b{1=b
where b5mH/kT (m5MsV). The magnitude of the
magnetic moment m of an individual particle is a strong
function of particle radius (V3r3). This is important
when particle size distributions are considered. The
Langevin function as applied to superparamagnetism
reveals the chief characteristics of the superparamagnet
response to a magnetic field, namely, no coercivity, no
remanent magnetisation, and very high field saturation
of the magnetisation.
Since superparamagnetism is a stochastic phenomenon, the direction of particle magnetic moment
fluctuates with time. Any specific particle will change
its direction of magnetisation during the time of
magnetisation measurement. For example, measurement
by SQUID (superconducting quantum interference
device) magnetometry has a measurement time of
roughly 102 s, yielding a blocking temperature defined
by
25~KV =kTB
whereas Mössbauer spectroscopy has a measurement
time of 1028 s, providing a blocking temperature of
2:7~KV =kTB
In other words, when the measurement times are much
greater than the relaxation time, thermal activation will
provide a statistical average of the magnetisation (for
temperatures above blocking temperature of a particle).
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As illustrated in the schematic Fig. 22, the perceived
blocking temperature can be manipulated by changing
the measurement time t or the applied field H for a
given set of nanoparticles (possessing constant magnetic
anisotropy K). Decreasing the measurement time
increases the blocking temperature when the particle
assembly and magnetic fields are kept constant (Fig. 22,
indicated ‘a’). This is illustrated by the comparison in the
previous paragraph between SQUID magnetometry and
Mössbauer spectroscopy. When the magnetic field is
increased (for a single measurement time and particle
assembly) the blocking temperature is reduced (Fig. 22,
indicated ‘b’). This is due to the stabilising effect of the
magnetic field on the particle assembly.
The general trend of larger blocking temperatures at
large particle size has been demonstrated experimentally, e.g. MgFe2O4 and CoFe2O4 (Refs. 70, 71) and
cobalt (Ref. 317). The reduction of TB when the
magnetic field is increased has been shown, e.g.
(Fe,Cu),317 Fe3O4, CoFe2O4, MnFe2O4 (Ref. 318), and
MgFe2O4 (Ref. 319). Dilution of samples also has an
effect on the blocking behaviour of nanoparticles.
Separate studies on cobalt (Ref. 39) and Fe3O4
(Ref. 320) have shown reduction in the blocking
temperature as the interparticle interactions are
increased. This is supported by energy calculations for
self-assembled monolayers containing particles with
uniaxial anisotropy and magnetostatic interactions.321
The blocking temperature of the nanoparticle array
decreased as the inverse cube of the interparticle spacing.
The smallest nanoparticle materials, with sizes below
1–2 nm, behave in a manner that is difficult to relate to
their bulk counterparts. Superparamagnetic materials
have enough particle volume to remain bulk-like in the
case of magnetocrystalline anisotropy and magnetisation. However, when the fraction of surface atoms
becomes too great, these intrinsic material properties
are highly influenced by surface relaxation effects,
thereby modifying their values. This in turn makes
comparisons to the models for superparamagnetism
difficult. This has been indicated in Fig. 18e, with the
title ‘sub-superparamagnetic’ particles for lack of a
better term.
Mechanisms for complicating magnetic
behaviour
Up to this point, the magnetic properties have been
simplified to a large degree to avoid confusing issues.
These ideal particle systems have avoided the effects of
oxidation, organic ligands bound to the particle surface,
particle shape, agglomeration, multiphase materials, etc.
All of these have contributed to the difficulty of
characterisation and analysis of the magnetic characteristics of nanoparticles. The magnetic behaviour of the
nanoparticles is sensitive to the physical characteristics
of individual particles (including morphology, intrinsic
materials parameters, and size) and their environments
(such as, interparticle interactions, material at the
particle surfaces, temperature, and applied magnetic
fields). Therefore, a complete characterisation of the
particles and their surroundings should accompany any
magnetic study. Failure to provide these prerequisites
makes meaningful determination of the intrinsic magnetic properties of the nanoparticles difficult.
Willard et al.
23 Schematic phase diagram for interparticle interactions
as function of particle size
Chemically prepared magnetic nanoparticles
1: shell exterior surface; 2: shell relaxation
shell material; 4: shell interphase interface
core interphase interface; 6: core material
24 Schematic diagram of metallic nanoparticle
dation at surface, indicating various
regions
region; 3:
region; 5:
with oxistructural
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Interparticle interactions
Interparticle interactions cause a multitude of complications in assessing the magnetic properties of nanoparticle assemblies. Each particle generates a local magnetic
field that can change the local energy minima for magnetisation of adjacent particles. This has been examined by
Zeng et al., where an effective demagnetisation factor
has been used to describe increased particle packing
densities.177 The magnetostatic field generated by the
particles can promote chaining of particles and agglomeration if the particles are free to move (as found by
Burke et al.322 for example). As schematically shown in
Fig. 23, interparticle interactions play an increasing role
as the distance between particles decreases. Particles are
considered to be isolated when they have a sufficiently
small interaction, as the magnetic field generated by
adjacent particles is generally the longest range interaction, this limit is determined by some small arbitrary
field generated by the particles in the assembly. The
particles shown in Fig. 18 are considered isolated; this is
indicated in Fig. 23 by a dashed line.
At large separation distances d12, the simple cases of
superparamagnetic and single domain particles are
found. The shaded region between the two indicates
the region where incoherent reversal modes make
significant contributions to the magnetisation reversal.
When the particles touch each other, short-range
exchange interactions are possible. Depending on the
amount of interface, this might be considered a
polycrystalline ferromagnetic material at this point
(assuming a large fraction of particle surface is
represented by interparticle interfaces). This is the
desirable case for using nanoparticles as precursors for
bulk compacted material, although there are great
difficulties in achieving this goal.
Intraparticle effects
Other forms of anisotropy may form when copious
surface area is available. Anisotropy due to surface
termination of the particle, exchange coupling to
antiferromagnetic oxides, or bonding to surfactants
alter the magnetic behaviour and, in some cases, the
anisotropy of the material directly.
In many cases, a passivating coating has been applied
to protect metallic nanoparticles from oxidation, as
a means of making them compatible with specific
environments (biological or chemical) or to avoid
agglomerations (ferrofluids). The addition of shells to
nanoparticles adds new dimensionality to the complexity
of the magnetic response. In Fig. 24, the simplest form
of a core/shell nanoparticle is represented schematically.
Six regions are enumerated for their potential to affect
the magnetic properties of the composite material. It is
noteworthy that some of these regions may share a
coherent interface making them difficult to distinguish
from one another.
The shell surface has been shown to modify the
‘magnetic volume’ of the particle, making it differ from
the structural volume (as found by TEM for example).
This might be due to the direct bonding of ligands to the
surface, missing bonds at the particle surface, or
development of a non-magnetic phase at the surface.323,324 Reduced magnetisation due to the expansive
surface of nanoparticles has been explained by spin
canting or pinning at the surface of the nanoparticles,325
and the introduction of a ‘dead’ layer at the surface
(y5 Å thickness).326,327 Surfactants coating the surfaces
of particles can have significant impact on the magnetic
properties of the nanoparticles.27,322,328 The effect of
various surfactants bound to the surfaces of Fe2O3
nanoparticles has been examined by Shafi et al.113 They
found phosphonate coated nanoparticles had much
reduced magnetisations compared to carboxylate and
sulphonate coated particles. Modelling of the surface
effects on the anisotropy of magnetic nanoparticles has
been approached by adding radially symmetric anisotropy terms to compete with uniaxial anisotropy terms
for the bulk of the particles.329
Depending upon the thickness of the shell, there may
be a region with near bulk properties for the shell
material. However, that region is sandwiched between a
surface dominated region and an interphase interfacial
region near the core material. The shell material within a
few unit cells of the surface of the particle presumably
has a relaxation of the bonds due to the missing bonds at
the surface, which can significantly change the magnetisation, especially in magnetic oxides. The interdiffusion of material from the core into the shell material has
significant feasibility, depending on how the particles
were passivated. This region may also have significant
strain produced during the formation of the shell and
the interphase interface. Similarly, the diffusion of
oxygen into the core material is possible, with the same
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consequences as for the shell material. Finally, presuming that the particles do not fully oxidise, a metallic core
with intrinsic magnetic properties similar to the bulk
resides at the centre.
Intentional encapsulation of magnetic nanoparticles
into a matrix can have profound effects on the magnetic
behaviour of the array. A non-uniform change in the
saturation magnetisation as a function of silica coating
thickness was observed for iron nanoparticles by
Atarashi et al., for example.330 Another complication
to understanding the magnetic properties is found when
the crystal structure accommodates a large range of
compositions (such as metallic alloys or spinel ferrites).
In these cases, the compositions of the particles may
deviate significantly from their parent solutions.141,193
The assumption that the solution composition and the
particle composition are identical should be avoided as
this will make meaningful magnetic characterisation
difficult to interpret.
Published by Maney Publishing (c) IOM Communications Ltd
Imbedded and consolidated particles
Magnetic nanoparticles are designed for a variety of
applications, as described at the start of this review. The
applications mentioned there indicate the necessity for
both single particle and consolidated particle systems.
Single particle applications include ferrofluids and
targeted drug delivery. Consolidated particle applications include inductor applications and, in some cases,
magnetic recording media. Thus far, the present section
has addressed single particle magnetic behaviour. In this
subsection, consolidated nanostructured materials will
be discussed. In many cases, these materials possess
unique magnetic properties due to the structural and
magnetic correlation lengths being similar in size.
Individual nanoparticles brought into close proximity
to each other experience magnetostatic interactions from
their neighbours’ local fields (produced by the existence
of the magnetisation). The magnetostatic energy is a
major driving force for agglomeration. This can cause
chaining of magnetic particles into long ‘pearl necklace’
like structures to minimise the magnetostatic fields for
the whole system. This usually occurs for freely mobile
particles that do not have a capping layer to limit the
distance between particles, thereby reducing the energy
well for minimisation of the magnetostatic energy.
Consolidated nanoparticles differ from the freely
moving nanoparticles in the respect that they are rigidly
affixed to one another and they share substantial
interfaces. Ideally, the nanoparticles could be compressed into completely dense bulk forms, however
this has proven quite difficult in practice. Generally,
consolidation to a fully dense form requires physical
compaction followed by annealing. If the annealing step
is too short or at too low a temperature, the compact
maintains voids. When the annealing process is too long,
significant grain growth occurs. In many cases both of
these problems arise concurrently.
There has been some success in consolidated nanoparticle materials. Inductor core materials have been
consolidated using a microwave sintering process.
Exchange spring nanocomposite materials have also
been produced by using two types of nanoparticles.331 In
both of these cases, the development of the nanocrystalline microstructure is advantageous for improved
magnetic properties.
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a 0.024 powder/binding polymer ratio (Tmax540 K); b
1.2 powder/binding polymer ratio (Tmax565 K); c highly
agglomerated powders of oxide (Tmax588 K)
25 Zero field cooled (ZFC)/field cooled (FC) results for
9 nm diameter c-Fe2O3 nanoparticles with increasing
amounts of interparticle interactions:334 applied field
for all three experiments was 50 Oe
The substantial interfaces in the consolidated nanoparticle materials change the interparticle interactions
from magnetostatic to exchange coupling. The exchange
coupling is essential for the improved magnetic properties found in many nanostructured materials (i.e.
exchange spring magnets332 and nanocrystalline soft
magnets333). The nanocomposite materials possess
hysteresis loops similar to those of single phase magnets
when exchange coupled. However, if the phases are not
fully exchange coupled for whatever reason, the hysteresis loop develops a shoulder in its second quadrant.
This indicates the phases have different coercivities and
are switching independently.
Measurement techniques
Due to the stochastic nature of many magnetic
nanoparticle effects, the magnetic properties obtained
by different measurement techniques are dependent on
the time scales of measurement, the measurement
temperature, and the applied magnetic field strength.
Complications arise when the effects of surface atoms,
particle size distributions, and interparticle interactions
are considered. The wide variety of measurement
techniques described in this section highlight some of
the research using each technique. Table 1 gives a
comprehensive listing of characterisation techniques
used for examination of nanoparticles produced by
chemical routes.
Direct current susceptibility
Direct current susceptibility measurement is a common
method of determining the superparamagnetic blocking
temperature. This is accomplished by examining a
Published by Maney Publishing (c) IOM Communications Ltd
Willard et al.
a 11 nm diameter particles measured at 5 K
(Hc52000 Oe); b 9 nm diameter particles measured at
5 K (Hc5897 Oe); c 6 nm diameter particles measured
at 5 K (Hc5291 Oe); d 9 nm diameter particles measured at 290 K (Hc50 Oe)
26 Typical hysteresis loops from blocked and superparamagnetic hcp cobalt nanoparticles produced by multisynthesis process206
particle system assembly under zero field cooled (ZFC)
and field cooled (FC) experimental conditions (see e.g.
Fig. 25). The ZFC experiment requires cooling the
sample to a low temperature with subsequent application of a small, applied magnetic field. The temperature
is then raised at a constant rate and susceptibility data
are collected. The susceptibility reaches a maximum at a
temperature near the blocking temperature, with superparamagnetic decay of the susceptibility above the
blocking temperature. The experiment proceeds with a
second cooling of the sample, this time in an applied
field. The FC experiment provides more certainty in the
temperature at which superparamagnetic behaviour sets
in. This experiment requires cooling the sample in a
small magnetic field of the same strength as the ZFC
experiment, again collecting susceptibility data as the
temperature is increased. The measurement relaxation
time for these experiments is near 10 s.
Sun and Murray have shown that ZFC experiments
on monodisperse self-assembled nanoparticles can be
used for examination of interparticle interactions.39 The
magnetostatic fields generated by the nearby nanoparticles in the array shift the peak in the ZFC curve to
lower temperatures in addition to sharpening the peak.
It should be noted that these experiments were
supported by evidence from X-ray diffraction, transmission electron microscopy, and inductively coupled
plasma experiments, all of which added to the analysis
of the magnetic properties.
The work of Puntes and Krishnan shows interparticle
dipolar interactions through the use of ZFC/FC experimentation.335 The experiments on e-Co self-assembled
nanoparticles showed a broad peak in the ZFC susceptibility characteristic of dipolar interactions. These
authors also observed a strong increase in the FC
susceptibility at low temperatures, presumably due to
Brownian motion of the particles in the viscous oleic acid
when the field was applied at high temperature.
Chemically prepared magnetic nanoparticles
27 Magnetisation as function of magnetic field/absolute
temperature for PVP coated iron nanoparticles (3–
8 nm in diameter): data were collected at 200, 250,
and 290 K – universal curve formed when magnetic
field is normalised by absolute temperature is characteristic of superparamagnets101
The importance of shape anisotropy is shown by Park
et al. in their study of 2611 nm iron nanorods and 2 nm
diameter spherical particles.82 The ZFC/FC experiments
show an order of magnitude lower blocking temperature
for the spherical nanoparticles, consistent with the
calculated anisotropy difference between the sphere
and rod morphologies.
Direct current hysteresis
Lack of coercivity and remanent magnetisation in
particulate samples are hallmarks of superparamagnetism. The hysteretic behaviour of a magnetic material can
be probed by cycling a large magnetic field between
opposite directions relative to the sample. The theoretical hysteresis curves shown in Fig. 20 compare the
ideal cases of isolated, monodisperse, non-interacting
nanoparticles, either single domain or superparamagnetic. More generally, a particle size distribution where some of the particles are large enough to be
blocked while others remain superparamagnetic is
necessary to describe a real material. As first demonstrated by Bean in 1955,336 a weighted average of
contributions from the superparamagnetic (Langevin
function) and blocked particles (Stoner–Wohlfarth
model) describes the hysteretic behaviour, barring
interparticle interactions. Realistic models of this
behaviour have been developed in recent years to
describe the variety of measured loop shapes.337,338
Typical hysteresis loops for magnetic nanoparticles are
shown in Fig. 26. These loops were produced using
samples of hcp cobalt synthesised from the multisynthesis processing techniques pioneered by the
authors, Murray et al.206 The results show increased
coercivity at 5 K for larger particles and superparamagnetism when the 9 nm sample was heated above the
blocking temperature (in this case 290 K). An illustration of an effect unique to superparamagnetic particles is
shown in Fig. 27. When the magnetisation is plotted
against magnetic field normalised by absolute temperature, the data fall onto a universal curve.101,336
If an applied field is large enough, the magnetisation
of the sample will stop increasing with applied field
(saturate). This value of magnetisation is an intrinsic
property and is most closely linked to the composition
of the material. For comparison between different
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Chemically prepared magnetic nanoparticles
Published by Maney Publishing (c) IOM Communications Ltd
materials, the measured magnetic moment for the
hysteresis loop at high fields (generally above 1.5 T) is
normalised by volume or mass. Error bars should accompany these values for magnetic nanoparticles due to the
small sample sizes used in many cases. Large errors will
accompany samples normalised by the mass of the
magnetic transition metal used in the sample.
A basic type of hysteresis loop study for nanoparticle
materials entails the measurement of loops above and
below the blocking temperature of the material. This is
illustrated by the work of Chen and Zhang for MgFe2O4
spinel ferrites.339 They demonstrated the increased
susceptibility for large sized superparamagnetic particles
at high temperatures and the coercivity dependence on
particle size for blocked particles.
Sun et al. used a superconducting quantum interference device (SQUID) magnetometer to examine the
phase transformations via hysteresis loops of monodisperse self-assembled FePt nanoparticles.207 Their
hysteresis results identify annealing conditions and composition ranges that were optimised for large coercivity.
SQUID magnetometry studies of the surface effects
on the magnetisation of nanoparticles were performed
by Toneguzzo and co-workers.146,164 These experiments
showed a common effect in nanoparticle systems,
namely, that the saturation magnetisation varies linearly
with the inverse of the mean particle diameter (or
proportional to the surface area divided by the volume).
This has been explained by spin canting or pinning at
the surface of the nanoparticles,325 the introduction of
a ‘dead’ layer at the surface,326 and the formation of
surface oxides during various studies. Toneguzzo et al.
used a metallo-organic and oxide phase shell model to
analyse their data.146 A particle core/shell model was
used by Gangopadhyay et al. to describe this reduction
in magnetisation with decreasing particle size.340 Their
parameters included magnetisation and densities of the
core and shell materials (score, sox, rcore, rox), thickness
of the shell tshell, and mean radius of the particle rmean,
leading to the following equation
rcore
tshell
spart ~score {3 score {sox
(2)
rox
rmean
This model has been shown effective for metals, alloys,
and oxides, e.g. (Mn,Zn)Fe2O4 (Ref. 48), CoFe2O4
(Ref. 70), Y3Fe5O12 (Ref. 132), Fe,341 and (Ni, Co,
Fe)146 (see Fig. 28). Additional complexity has been
observed by Verelst et al. for Co/CoO nanoparticles,
where the blocked particles exhibit exchange bias
behaviour due to the antiferromagnetic coupling of the
CoO with the metallic Co core.75
A similar study of yttrium–iron garnet (Y3Fe5O12) by
Sánchez et al. showed the saturation magnetisation is
lower than the bulk value by a term inversely proportional to the particle diameter.132 In this case, the oxide
particles have a decreased magnetisation presumably
due to either a non-magnetic surface layer or noncollinear spin arrangement. Shafi et al. have examined
the surface effects of various surfactants on the surfaces
of amorphous Fe2O3 nanoparticles.113 They attribute
low magnetisation found in hysteresis loops for particles
coated with octyl phosphonic acid as an indication of antiferromagnetic coupling to the nanoparticles.
Sun et al. have studied the coercivity as a function
of temperature for FePt nanoparticles with different
160
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28 Saturation magnetisation of (Co,Ni) and (Fe,Co,Ni) nanoparticles plotted against reverse mean particle radius:
fits use equation (2), with extrapolation indicating near
bulk values for saturation magnetisation146
isothermal annealing temperatures.207 They found
higher coercivity at higher annealing temperatures, due
in part to atomic ordering of the FePt into the L10
crystal structure with concomitant high magnetocrystalline anisotropy. Although the analysis was successful
for this study due to careful experimentation and
choice of materials, in general, the comparison of
coercivity between samples is complicated by the
changes in morphology producing changes in reversal
mechanism. This problem was avoided by Sun et al. due
to the charring of the surfactant coating during
annealing, which prevented large changes in microstructure. In general, this type of analysis can be difficult,
especially if agglomeration or oxidation of the samples
occurs.
Temporal remanent magnetisation
The switching and relaxation behaviour of nanoparticles
can be examined by a number of different temporal
remanent magnetisation techniques. Thermoremanent
magnetisation (TMR) studies provide relaxation information about particles that have been field cooled below
the blocking temperature with ensuing removal of
the magnetic field at the measurement temperature.
Isothermal remanent magnetisation (IMR) experiments
require zero field cooling to the measurement temperature with subsequent application and removal of a
magnetic field. Finally, similar to the IMR curves, dc
demagnetisation curves involve zero field cooling of
the sample, however a large magnetic field is applied
to the sample and then a field is applied in the
opposite direction from which it is finally removed.
The combination of dc demagnetisation and IMR
experiments can provide interparticle interaction information through the calculation of the dM parameter.342,343 Since superparamagnetic particles do not
have remanent magnetisation, the magnetic remanence
will come from the blocked magnetic particles at a
given temperature.
The experiments of Zeng et al. have shown the
interparticle interactions of FePt nanoparticles by use of
dM curves.344 The particles in this case are annealed and
thereby aggregate showing a trend of negative dM values
indicating dipolar interactions for low annealing temperatures and large positive dM indicating exchange
coupling at high annealing temperatures.
Willard et al.
Chemically prepared magnetic nanoparticles
Published by Maney Publishing (c) IOM Communications Ltd
29 Thermal remanent magnetisation (TRM) and zero field
cooled (ZFC) data for MnFe2O4 sample with 8 nm dia.
grains: TRM curve was produced by cooling in
100 Oe field and same field was used for ZFC curve –
full relaxation of TMR curve coincides with blocking
temperature72
Thermal remanent magnetisation was used to examine
MnFe2O4 nanoparticles with a mean particle size of
8 nm (see Fig. 29).72 These experiments by Lui et al.
showed a reduction of Mr to zero near the blocking
temperature of the nanoparticle assembly. Thermal
remanent magnetisation experiments have also been
used by Held et al. to investigate the interparticle
interactions in diluted samples of 7 nm diameter cobalt
particles.345 An accompanying analysis provides context
for a simple model of the TMR curves as a function of
particle spacing.
Alternating current susceptibility
Alternating current susceptibility measurements are
a valuable source of magnetic characterisation with
measurement frequencies from 10 Hz to 10 kHz. This
technique gives information about the dynamic behaviour of the nanoparticles with the capability for initial
susceptibility measurements at very small fields. Alternating current susceptibility measurements are carried
out as a function of temperature with fixed, small field
amplitude. Multiple experiments at different frequencies
indicate the changes in blocking temperature. Experiments show the real part of the susceptibility x9 is
frequency independent at high temperatures due to
thermal equilibrium of the superparamagnetic particles.
When some of the superparamagnetic particles are
blocked as the temperature is reduced, increased
frequencies shift the x9 peaks to higher temperatures
with a decreased magnitude.
These attributes are clearly shown by the work of
Dormann et al. on c-Fe2O3 nanoparticles (Fig. 30).346
Nanoparticles in varying sizes and degrees of interaction
were examined by ac susceptibility. Particle samples
(7 nm dia.) were examined as chains of particles and
as entangled chain agglomerates. The particles with a
chain-like environment possessed larger susceptibility
than the agglomerated sample for all measurement
frequencies. Additionally, the chained particle sample
exhibited lower peak temperatures for x9, indicating
lower stability of the particles to thermal fluctuations
than the agglomerated sample that possesses more near
neighbours (thus higher magnetostatic interparticle
interactions).
The effect of dilution on relaxation times of amorphous Fe0.78C0.22 particles as a function of temperature
a chains of particles with 7 nm particle diameter; b
highly agglomerated particles with 7 nm particle diameter: note higher blocking temperatures for higher
frequencies and greater degree of agglomeration
30 Alternating current susceptibility data for samples of
c-Fe2O3 at measurement frequencies of 10, 95, 1000,
and 10 000 Hz and field amplitude of 1 Oe346
was examined by Djurberg et al.347 The more dilute
sample showed much smaller relaxation times for a
given temperature. This reflects the significance of
interparticle interactions, where higher degrees of
magnetostatic interaction provide stability to the system
of particles.
Ferromagnetic resonance
Ferromagnetic resonance (FMR) experiments provide
information about the anisotropy, the distribution of
particle easy axis orientations, and surface effects of
magnetic nanoparticles. The experiment uses a strong
magnetic field to align the magnetic moments of the
particles and a transverse high frequency field to
produce a precession of the magnetic moment about
the strong applied field. These experiments are generally
accomplished by fixing the high frequency field component and measuring the magnetic susceptibility as a
function of the direction and magnitude of the large
applied field. In general, the resonance frequency is
lowered for smaller magnetocrystalline anisotropy (at
a constant external field). This has been shown by
Fannin et al. for (Mn,Zn)Fe2O4 and (Ni,Zn)Fe2O4
nanoparticles with 9 nm mean diameters.348 The many
GHz frequency range of the high frequency field
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Chemically prepared magnetic nanoparticles
Published by Maney Publishing (c) IOM Communications Ltd
31 Ferromagnetic resonance data for Co80Ni20 nanoparticles and microparticles – complex permeability m i0 of
particles was measured in 0.1–18 GHz frequency
range in absence of external magnetic field: 220 nm
sample exhibited spin-wave resonance as indicated
by numerous resonance peaks145
component gives a measurement time of greater than
1029 s.
Viau and co-workers have examined (Ni,Co) and
(Ni,Fe,Co) by FMR over a large particle size range (see
e.g. Fig. 31).139,143–145,147 For micrometre sized, multidomain particles, they found a single broad resonance
peak, while for particle below 50 nm, a single sharp
resonance was observed. The large sized particles have
resonance consistent with a curling process. The sharp
peak for the sub-50 nm particles was consistent with
non-uniform exchange resonance modes. In between
these two extremes, multipeak resonance was observed,
where the peaks have been correlated with spin-wave
resonance modes for the particles (similar to those found
in thin films). Spinel ferrites show similar behaviour.
NiFe2O4 nanoparticles, 10–25 nm in diameter, show a
single sharp resonance peak which broadens at reduced
measurement temperatures.112
Studies carried out by Diehl et al. show the general
trends of line sharpening for smaller particle size and
higher measurement temperatures for e-Co and twinned
fcc cobalt samples.349 These effects are due to the
thermal relaxation of the nanoparticles, yielding a single
sharp resonance peak. The peak shape changes were
accompanied by shifts in the resonance lines due to
changes in the presence or magnitude of the particle
anisotropy. The effects of surface anisotropy were
examined by Gazeau et al. for c-Fe2O3 nanoparticles
below 10 nm diameter.350
Mössbauer spectroscopy
Mössbauer spectroscopic measurements use the absorption and emission of c-rays to examine the local
hyperfine fields at atomic nuclei. Generally, c-rays with
frequencies in the range 1018–1019 Hz are used for these
experiments to excite the 57Fe isotope within the sample.
This technique can be used to reveal information about
the crystal structure (refer to the subsection ‘Site
occupancy’ above) and magnetic characteristics of the
nanoparticles with roughly a 1028 s measurement time.
Modelled Mössbauer spectra can be superimposed to
incorporate many crystalline and amorphous phases,
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32 Mössbauer spectra from 57Fe in CoFe2O4 nanoparticles with 3 nm diameter at various measurement temperatures in zero field: solid lines are fits to data,
including sextet terms from tetrahedral and octahedral spinel ferrite sublattices and superparamagnetic
doublets353
distinguishing different oxidation states of iron and different site symmetries, including separate contributions
from surface atoms when relaxation effects are not significant. Due to thermal activation, superparamagnetic
particles exhibit fluctuations in the hyperfine field
parameters as a function of time.
Barium hexaferrites (BaFe12O19) have five incommensurate iron sublattices which produce complex
Mössbauer spectra with a sextet for each sublattice
and an additional doublet for any superparamagnetic
contributions. These materials (as well as other complex
oxides) have been probed for samples with different
particle sizes and annealing temperatures.20,129,351 The
simpler crystal structure of spinel ferrites reduces the
number of incommensurate iron sublattices to two. For
this reason, many Mössbauer effect spectroscopy studies
have been conducted on these materials.
Prasad and Gajbhiye examined NiFe2O4 nanoparticles by room temperature Mössbauer spectroscopy for
samples isothermally annealed at temperatures ranging
from 473 to 1173 K.352 The resulting data showed a
transition in behaviour from superparamagnetism for
samples annealed at 473 K to ferrimagnetism for
samples annealed at 973 K due to grain growth. Intermediate to these results were samples annealed at 673 K,
showing both a pair of sextets from the octahedral and
tetrahedral sublattices of the ferrimagnetic phase and a
doublet from the superparamagnetic phase. Another
study by Chen et al. shows the temperature dependence
(55–300 K) of the Mössbauer spectra for 6 and 12 nm
diameter MgFe2O4 nanoparticles.319 These samples
showed low temperature sextets with the addition of a
doublet when the measurement temperature reached the
Published by Maney Publishing (c) IOM Communications Ltd
Willard et al.
blocking temperature of some of the particles. At 300 K,
only the superparamagnetic behaviour was observed.
Samples of (Co,Zn)Fe2O4 nanoparticles of varying
composition and size have been examined by Lee
et al.128 Room temperature Mössbauer spectroscopy
was carried out for Co0.9Zn0.1Fe2O4 particles annealed
at temperatures between 473 and 1073 K. Results
similar to those of Prasad and Gajbhiye were found.
Figure 32 shows Mössbauer absorption spectra from
3 nm CoFe2O4 particles measured at temperatures from
4.2 to 180 K.353 The 4.2 K spectrum shows ferrimagnetic behaviour, while the 180 K spectrum shows
superparamagnetic behaviour. The intermediate temperatures provide examples of the progression through
the blocking of progressively smaller particles as the
temperature is lowered.
The effects of large surface area were examined by
Bødker et al. by Mössbauer experiments on metallic iron
nanoparticles.354 The anisotropy of the particles was
determined in situ as a function of grain size from the
observed hyperfine field. The results indicted an increase
in the anisotropy as the particle size decreased which
was mainly attributed to magnetocrystalline anisotropy
of the particles.
Closing remarks
The goals of this review are to describe the chemical
synthesis options available for the processing of
magnetic nanoparticles, provide a review of useful and
novel characterisation methodologies to better understand the structure and chemistry of these particles, and
to broadly review the magnetic properties of these
particles in terms of their intrinsic magnetism as well as
cooperative effects. The review has been limited to the
time period beginning in 1990 and extending through
2003. Where appropriate, the reader is directed to other
reviews and papers that provide the needed background
to understand the outstanding issues addressing magnetic nanoparticles.
The scope has been focused on the chemical methodologies that have been used to synthesise magnetic
nanoparticles. Since these techniques use similar solvent
systems, they offer the widest versatility and flexibility in
Chemically prepared magnetic nanoparticles
processing. Combining one or more of these techniques
is relatively simple and allows the synthesis of many
types of oxides and alloys. Of particular interest is the
use of surfactant-mediated synthesis, including micellar,
sol–gel, and polyol techniques. These techniques offer
the ability to control particle size to less than 10% and
allow a wide range of materials and morphologies.
Notwithstanding these powerful processing methods,
gaining insight into the composition, phase, and structure of the particles remains elusive. To address this
challenge, the use of synchrotron radiation techniques
is proposed, to supplement the more routine laboratory
characterisation tools. The X-ray absorption fine
structure (EXAFS) technique has recently been used to
analyse magnetic nanoparticles to determine element
specific phase purity, cation disorder, and particle size.
This powerful tool can address many of the difficulties
that exist in determining the nature of nanoparticles.
Finally, the intrinsic and extrinsic magnetic properties of
nanoparticles are reviewed. Since the magnetism of these
materials depends not only on particle chemistry and
phase, but also on the particle size and environment, the
roles of interparticle interaction and surface functionalisation are explored in determining the magnetic properties of the system.
Appendix
Units of measurement for magnetic applications suffer
from unusual definition conventions, making it difficult
to convert easily between CGS and SI systems. This
appendix provides definitions and unit conversions for
some of the salient terms necessary for understanding
the magnetics of nanoparticles (see Table 3). More in
depth descriptions of these terms and their uses can be
found elsewhere.307,308
Curie temperature Tc is the phase transformation
temperature from ferromagnetic (or ferrimagnetic)
behaviour to paramagnetic behaviour.
Saturation magnetisation Ms is the magnetic moment per
unit volume of the material when a sufficiently
large magnetic field is applied to remove all domain
walls and align the magnetisation of the sample with the
field.
Table 3 Magnetic units table for CGS to SI conversion
Quantity
Symbol
CGS unit
SI unit
Magnetic induction
B
gauss (G)
Magnetic flux
W
maxwell (Mx)
Magnetic field
Magnetisation
Magnetic polarisation
H
M
4p M
J
oersted (Oe)
emu cm23
gauss (G)
gauss (G)
Specific magnetisation
Magnetic moment
Molar susceptibility
Mass susceptibility
Volume susceptibility
Permeability
Relative permeability
Magnetic anisotropy
Magnetostriction coefficient
Exchange stiffness
s
m
xm
x
k
m
mr
K
l
A
emu g21
emu
emu Oe21 g21 mol21
emu Oe21 g21
Dimensionless
G Oe21
Not defined
erg cm23
ppm
erg cm21
1024 tesla (T)
(T5kg A21 s22)
1028 weber (Wb)
(Wb5kg m2 A21 s22)
103/4p A m21
103 A m21
103/4p A m21
1024/4p tesla
(T5kg A21 s22)
1 A m2 kg21
1023 A m2
4p 1026 m3 mol21
4p 1023 m3 kg21
4p dimensionless
4p 1027 kg m A21 s21
Dimensionless
1021 J m23
ppm
J m21
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Exchange stiffness A is the strength with which adjacent
magnetic moments remain aligned due to exchange
interactions.
Magnetocrystalline anisotropy K is the internal energy
density dependence on the direction of the magnetic
moment with respect to the crystalline lattice. In this
review, magnetic anisotropy is discussed in detail in
the subsection ‘Single domain particles’, due to its strong
influence on the magnetic properties of nanoparticles.
Coercivity or coercive field Hc is the applied magnetic
field required for reduction of a saturated magnetic
material to zero magnetisation.
Remanent magnetisation Mr is the magnetisation that
remains after an applied field has been removed.
Magnetic susceptibility x is the magnetisation normalised
by the applied magnetic field. The magnetic susceptibility
acts as a technological figure of merit for magnetic
nanoparticles, since it links the particles (through their
magnetisation) with a readily applied field.
Published by Maney Publishing (c) IOM Communications Ltd
Acknowledgements
The authors gratefully acknowledge support for this
work from the Office of Naval Research, Defense
Advanced Research Projects Agency, and the National
Research Council. The authors would like to thank Dr
Bruce Ravel, Dr William O’Grady, Dr David Pena, and
Dr Marc Raphael for many fruitful conversations.
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