Download Characterization of FBK-irst 3D Double Side Double Type Column

UNIVERSITÀ DEGLI STUDI DI TORINO
Characterization of
FBK-irst 3D Double Side
Double Type Column
Silicon Sensors
Candidate: Rivero Fabio
A.A. 20082009
M A S T E R1 T H E S I S
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UNIVERSITÀ DEGLI STUDI DI TORINO
FACOLTA’ DI SCIENZE MATEMATICHE, FISICHE E NATURALI
Corso di Laurea Specialistica in Fisica Ambientale e Biomedica
MASTER THESIS
Characterization of FBK-irst
3D Double Side Double Type
Column Silicon Sensors
Candidate: Rivero Fabio
Supervisor: Prof. A.M. Solano
Co-supervisor: Prof. G.-F. Dalla Betta
Co-supervisor: Dott. A. La Rosa
A.A. 2008-2009
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Abstract: 3D pixel silicon detectors are being investigated because of their promising properties for
experimental physics experiments and other applications. Their main advantages with respect to traditional
silicon detectors are the high radiation hardness and the possibility of having active edges, reducing the
dead zones in the sensor. After an introduction into this field of research, this thesis focuses on the
characterization of 3D Double Side Double Type Column pixel silicon detectors developed at the
Fondazione Bruno Kessler (FBK-irst) in Trento, Italy, with laboratory characterization, test beam and
irradiation of these detectors at CERN.
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Table of contents
1 - Introduction ..........................................................................................................................................11
2 – Physics of Semiconductor Detectors.....................................................................................................15
2.1 – Ionizing radiation ............................................................................................................................ 17
2.2 – Interaction of electromagnetic radiation with matter ..................................................................... 17
2.2.1 –Photoelectric effect .................................................................................................................. 19
2.2.2 – Compton scattering ................................................................................................................. 20
2.2.3 – Pair production ........................................................................................................................ 20
2.3 – Interaction of charged particles with matter ................................................................................... 20
2.3.1 – Stopping power ....................................................................................................................... 20
2.3.2 – Energy loss by heavy charged particles .................................................................................... 21
2.3.3 – Energy loss by light charged particles ...................................................................................... 24
2.4 –Physics and behaviour of semiconductors........................................................................................ 25
2.4.1 – Conduction in a solid ............................................................................................................... 25
2.4.2 – Classification of semiconductors .............................................................................................. 26
2.4.3 – Silicon ..................................................................................................................................... 27
2.4.4 – Doping of silicon ...................................................................................................................... 27
2.4.5 – Generation and recombination of charge carriers .................................................................... 28
2.4.6 – Charge transportation ............................................................................................................. 29
2.4.7 – PN junctions ............................................................................................................................ 30
2.4.8 – Diffusion across the junction.................................................................................................... 30
2.4.9 – Biasing the junction with forward bias .................................................................................... 31
2.4.10 – Biasing the junction with reverse bias .................................................................................... 32
2.4.11 – I-V characteristic curve of a PN junction ................................................................................. 33
2.5 –Semiconductor silicon detectors ...................................................................................................... 34
2.5.1 – Capacitance ............................................................................................................................. 34
2.5.2 – Substrate and electrodes type ................................................................................................ 35
2.5.3 – Signal development ................................................................................................................ 35
2.5.4 – Photon detection ..................................................................................................................... 36
2.5.5 – Charged particle detection....................................................................................................... 36
2.5.6 – Functionality of silicon detectors ............................................................................................ 36
2.5.7 – Signal readout ......................................................................................................................... 37
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3 – Silicon Pixel Detectors ..........................................................................................................................39
3.1 – Strip detectors ................................................................................................................................ 41
3.2 – Pixel detectors ................................................................................................................................ 42
3.2.1 – Pixel capacitance ..................................................................................................................... 43
3.2.2 – Cross talk, spatial resolution and charge sharing in pixel detectors .......................................... 43
3.3 – Planar and 3D pixel detectors ......................................................................................................... 44
3.3.1 – Active edges ............................................................................................................................ 46
3.3.2 – 3D detector concepts............................................................................................................... 47
3.4 – Devices under test .......................................................................................................................... 49
3.4.1 –FBK-3D sensors ......................................................................................................................... 49
3.4.2 – Hybrid Pixel Detectors ............................................................................................................. 51
3.4.3 – Single Chip Assembly (SCA) ...................................................................................................... 52
3.4.4 – Current ATLAS Silicon Pixel detectors ....................................................................................... 52
3.4.5 – Front-End Electronics description ............................................................................................ 54
3.4.6 – Single channel.......................................................................................................................... 56
3.4.7 – FE-I3 calibration....................................................................................................................... 57
4 – Characterization and Test of FBK-3D Pixel Silicon Sensors ...................................................................59
4.1 – Sensor properties and performance tests ....................................................................................... 61
4.2 – TurboDAQ setup ............................................................................................................................ 61
4.2.1 – Hardware description .............................................................................................................. 63
4.2.2 – Software description ............................................................................................................... 64
4.2.3 – Fixed setup at CERN Lab 161 .................................................................................................... 65
4.3 – The SCAs and their characterization................................................................................................ 67
4.4 – I-V measurements .......................................................................................................................... 68
4.4.1 – Measurements results on FBK-3D and planar sensors .............................................................. 69
4.4.2 – Leakage current from Monleak Scan ........................................................................................ 72
4.5 – Threshold and noise ....................................................................................................................... 73
4.5.1 – Measurements results on FBK-3D and planar sensors ............................................................. 74
4.5.2 – Noise versus bias voltage of the sensor .................................................................................... 76
4.6 – Time over Threshold (ToT) measurements and internal calibration of the detector ........................ 78
4.6.1 – Measurements results on FBK-3D and planar sensors ............................................................. 80
4.7 – Gamma source measurements with 241Am and 109Cd ..................................................................... 81
4.7.1 – Measurements results on FBK-3D and planar sensors ............................................................. 81
4.8 – Beta source measurements with 90Sr ............................................................................................. 84
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4.8.1 – Measurements results on FBK-3D and planar sensors ............................................................. 84
4.9 – Test Beam ..................................................................................................................................... 87
4.9.1 – The experimental setup ........................................................................................................... 88
4.9.2 – Selected events ....................................................................................................................... 90
5 – Irradiation.............................................................................................................................................91
5.1 – Radiation-induced effects on silicon ............................................................................................... 93
5.1.1 –Bulk damage............................................................................................................................. 93
5.1.2 – Leakage current and annealing ................................................................................................ 94
5.1.3 – Effective doping and fluence dependence ................................................................................ 96
5.1.4 – Charge trapping ....................................................................................................................... 98
5.1.5 – Surface effects ......................................................................................................................... 98
5.1.6 – Consequences of irradiation damage on sensor operation ....................................................... 98
5.2 – PS irradiation facility overview........................................................................................................ 99
5.3 – Irradiation of FBK-3D and planar sensors ...................................................................................... 101
5.3.1 – Irradiation of FE-I3 ................................................................................................................. 101
5.3.2 – Irradiation of SCAs - Setup ..................................................................................................... 103
5.1.3 – Irradiation of SCAs - Results .................................................................................................. 105
6 – Conclusions ........................................................................................................................................ 111
7 – Appendixes ........................................................................................................................................ 115
Appendix 1 – FE-I3 ................................................................................................................................ 117
Appendix 2 - TurboDAQ ........................................................................................................................ 118
Appendix 3 – Complete plots collection................................................................................................. 125
References ............................................................................................................................................... 135
Acknowledgements ................................................................................................................................. 141
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Chapter 1 – Introduction
CHAPTER 1
INTRODUCTION
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Chapter 1 – Introduction
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Chapter 1 – Introduction
N
ew sensor concepts and materials are currently being investigated in the field of particle detection,
mainly due to the proposed luminosity upgrade of the LHC at CERN, when tracker detectors will
have to cope with high density of events and survive very high radiation fluences up to 10 16
protons per cm2. 3D silicon pixel detectors can be a possible answer to these uprising needs, and at present
are being fully investigated, tested and characterized within ATLAS. This thesis focuses on the
characterization of a particular type of 3D pixel silicon detectors, the DDTC ones developed and produced
at the Fondazione Bruno Kessler (FBK-irst) in Trento, Italy, in comparison to the current planar silicon pixel
detectors mounted inside the ATLAS inner tracker.
Chapter 2 gives an introduction to the theoretical aspects of particle (electromagnetic, light and heavy
charged particles) interactions with matter. In the second part of the chapter, semiconductors and in
particular silicon detectors are described.
Chapter 3 describes pixel silicon detectors, and in particular FBK-3D pixel detectors and their
characteristics, explaining the differences between 3D and planar sensors. Moreover, a description of the
front-end electronics (ATLAS FE-I3 chip) used to readout signals coming out of the sensor is given.
In Chapter 4 the work done for this thesis on the characterization of FBK-3D detectors is presented, starting
from the electronics tests and coming to calibration of SCAs (Single Chip Assembly) and source tests to
verify the correct performance of the detectors. The 3D May 2009 Test Beam, to which I contributed for
data acquisition is also described.
Finally, Chapter 5 focuses on irradiation of FBK-3D detectors, showing preliminary results from a first
irradiation with the 24 GeV/c proton beam of the CERN PS (Proton Synchrotron), at which I have worked
from July to November 2009.
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Chapter 1 – Introduction
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CHAPTER 2
PHYSICS OF SEMICONDUCTOR DETECTORS
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Chapter 2 – Physics of Semiconductor Detectors
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Chapter 2 – Physics of Semiconductor Detectors
T
his chapter is meant to describe the physics behind interaction of radiation with matter, its
consequences and the principles applied in semiconductor silicon detector technology. Particles and
electromagnetic radiation are detected through their interaction with matter, with different
interaction processes for photons, charged particles and neutral particles. In semiconductor detectors
mainly interactions that create free charge carriers are of relevance, because they produce signals that can
be collected by appropriate electronics.
2.1 – Ionizing radiation
Referring to the way in which it ionizes a material, radiation can be distinguished in directly and indirectly
ionizing. All charged particles that lose their energy by directly exciting or ionizing atoms and molecules of
the traversed material by electromagnetic processes belong to the first category, while the second class
groups neutral particles (neutrons) and electromagnetic radiation (photons), because they interact with
matter generating secondary particles that can lead to excitation and ionization. Moreover, a particle
travelling through matter can lose energy gradually (losing energy nearly continuously through interactions
with the surrounding material), or catastrophically (moving through with no interaction until losing all its
energy in a single collision). Gradual energy loss is typical of charged particles, whereas photon interactions
are of the "all-or-nothing" kind.
2.2 - Interaction of electromagnetic radiation with matter
Depending on their energy and on the nature of the material, photons interact with matter in three main
ways: with the Photoelectric Effect (or Photoelectric Absorption), the Compton scattering and the Pair
Production. It is also important to mention the Rayleigh Scattering, which consists in the diffusion of the
photons over the electrons of atoms, without ionization or excitation of the atoms.
The absorption of a beam of photons, all with the same energy and all travelling in the same direction, is
described by an exponential law:
𝑁 𝑥 = 𝑁0 𝑒 −µ 𝐿 𝑥
that accounts for the exponential decrease of the number of particles N(x) at x given depth into the
material starting from the initial number 𝑁0 , where µL is the linear absorption coefficient1 given by:
𝜇𝐿 =
𝜍𝑁𝐴 𝜌
𝐴
with ς cross-section, NA Avogadro’s constant, ρ the density of the material, A the molecular weight. The
average distance travelled by a photon before being absorbed is given by λ, the attenuation length or mean
free path, that is the inverse of the linear absorption coefficient:
𝜆=
1
µ𝐿
The absorption of photons depends on the total amount of material in the beam path, and not on how it is
distributed, because the probability for a photon to interact somewhere within the matter depends on the
total amount of atoms ahead of its path (since they interact only with a single atom). Therefore, it is useful
1
It gives a measure of how fast the original photons are removed from the beam (if of high values the original photons
are removed after travelling only small distances)
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Chapter 2 – Physics of Semiconductor Detectors
to describe the absorption process factorizing the dependence on the density of the material from the type
of material. This is obtained by introducing the mass absorption coefficient μm, which relates the linear
absorption coefficient to the density of the material ρ:
µ𝐿 = µ𝑚 𝜌
This means, for example, that the mass absorption coefficient is the same for ice, liquid water and steam,
whereas the linear absorption coefficients differs greatly. The total attenuation effect of a given material
slab can be described by quoting the mass attenuation coefficient, which depends on the material's
chemical composition and the photon energy, together with the material's density and thickness. The
product ρx, the areal density, is often quoted instead of the geometrical thickness x. If an absorber is made
of a composite material, the mass absorption coefficient is readily calculated by summing the products of
the mass absorption coefficients and the mass proportions (α) each element present in the material:
µ𝑚 𝑇𝑂𝑇𝐴𝐿 =
(𝛼 µ𝑚 )
If the radiation changes, degrades in energy, it is not completely absorbed or if secondary particles are
produced, then the effective absorption may decrease, and so the radiation penetrates more deeply into
matter. It is also possible to have an increasing number of particles with depth in the material: this process
is called build-up, and has to be taken into account when evaluating the effect of radiation shielding, for
example.
The total interaction probability of the photons is given by the sum of the single effect cross-sections, which
are summarized in Figure 2.1 for silicon:
𝜍 = 𝜍𝑃𝑕𝑜𝑡𝑜𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐 + 𝜍𝐶𝑜𝑚𝑝𝑡𝑜𝑛 + 𝜍𝑃𝑎𝑖𝑟
Figure 2.1 – Probability of photon absorption for 300 µm silicon as function of the photon energy, indicating the
contribution for different processes and a comparison with total probability for 300 µm CdTe [2-1]
For silicon (Z=14), and for energies of photons under 100 keV, the dominant effect is the photoelectric one,
whereas for over 10 MeV it is the pair production. The absorption coefficient for a photon coming from the
decay of 241Am, which produces X-rays of 59.5 keV, is 0.3 cm2g-1, and the probability of detection in 300 µm
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Chapter 2 – Physics of Semiconductor Detectors
silicon is only of 2%. This because of the fact that cross-sections for photons are low, and consequently also
the probability of detection are low. Nevertheless, gamma sources are suited for calibrating silicon
detectors because the whole photon energy can be detected in the sensor with the assumption that
electrons from photoelectric effect do not escape from the detector. The exponential attenuation law does
not describe what happens to the energy carried by the photons removed from the beam, which possibly
may be carried through the medium by other particles, including some new photons.
2.2.1 - Photoelectric effect
This process consists in the absorption of a photon with consequent expulsion of an electron from the hit
atom. In order to remove a bound electron from an isolated atom, a threshold energy for the photon is
needed: it is the ionization potential, and it varies depending on the atomic shell the electron occupies. If
the energy of the photon, Eγ, exceeds the ionization potential (also called EB , binding energy2), an electron
will be emitted, carrying energy Ee given by the following formula:
𝐸𝑒 = 𝐸𝛾 − 𝐸𝐵
The ionization potential depends on the square of the nuclear charge Z of the atom (and so on the
dimension of the atom), and the cross-section for the photoelectric effect is also a strong function of Z:
𝜍𝑃𝑕𝑜𝑡𝑜 ∝ 𝑍 𝑛
with n varying between 4 and 5 depending on the photon energy [2-2]. This process is dominant at low
photon energies (in silicon below 100 keV); for this reason high-Z materials (e.g. Cadmium Telluride CdTe)
are preferred for X-ray detection. In this thesis the photoelectric effect has been used in order to calibrate
3D silicon detectors, trying to reproduce the photoelectric peaks of some known gamma radioactive
elements (241Am and 109Cd).
When other atoms are present, as in molecules and solids, the electronic energy levels and the
photoelectric cross sections will be very different. For solids, the threshold can be ≈ 1 eV and it depends on
the crystalline structure and on the nature of the surface. The ionization potential in this case is usually
called work function. Photon absorption efficiencies approach 100% in the visible and ultraviolet, but the
overall device efficiencies are limited by the electron escape probabilities. In a semiconductor, a photon
can be thought as ”ionizing” an atom, producing a ”free” electron which remains in the conduction band of
the lattice. Thresholds are of order 0.1–1 eV for intrinsic semiconductors and of order 0.01–0.1 eV for
extrinsic semiconductors. The latter photon energies correspond to infrared photons. In the end, the
escaping electron produces a redistribution of the atomic electrons, that can lead to Fluorescence (emission
of photons) or Auger Effect (emission of characteristic X-ray radiation).
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1≤EB≤100 KeV, depending on the shell and on the atom
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Chapter 2 – Physics of Semiconductor Detectors
2.2.2 - Compton scattering
Compton scattering takes place when a photon scatters off a free (or a quasi-free) electron, yielding a
scattered photon with a lower frequency and a new direction. For an unbound electron initially at rest, it is
possible to write the following equation:
𝑕𝜈 ′
𝑕𝜈
= 𝑕𝜈 1 +
(1 − cos 𝜃)
𝑚𝑒 𝑐 2
−1
with hν and hν’ initial and final energy, θ photon angle change, m e electron mass and c speed of light. The
Compton cross section is given by the Klein-Nishina formula [e.g. 2-1]. The absorption cross section is small
at low energies, rises to a peak for photon energies around 1 MeV and declines at higher energy.
2.2.3 - Pair production
Photons with energies in excess of 2mec2 produce electron-positron pairs, and interaction with a nucleus is
needed in order to balance momentum. The pair production cross section starts at 1.022 MeV and then
rises to an approximately constant value at high photon energy, in the gamma ray region of the spectrum
of electromagnetic radiation. Cross sections scale with the square of the atomic number, and complete
equations describing the cross-section are Bethe-Heitler equations [e.g. 2-3].
2.3 - Interactions of charged particles with matter
The most common way in which charged particles can interact with matter is the electromagnetic
interaction, that can involve inelastic collisions with electrons in the absorbing material or elastic collisions
with nuclei. Inelastic collisions lead to continuous loss of energy by incident particles. When atoms or
molecules are given energy by an incident particle that brings them at an excited state, the process is called
Excitation3; alternatively, when the released energy is enough to form electron-ion pairs, the process is
called Ionization. Emitted electrons can have higher kinetic energy than the material’s ionization potential,
so they can furthermore ionize the atom, creating secondary energetic electrons called δ rays. Elastic
collisions cause lateral diffusion of the incoming particle (Multiple Scattering), without noticeable loss of
energy. This effect is higher when the mass of the hitting particle is small, so it is particularly relevant for
light particles such as the electrons. When small masses are involved, other electromagnetic processes such
as Bremsstrahlung, Cerenkov Effect and Transition Radiation become relevant. So it is important with
charged particles to split light charged particles, such as electrons and positrons, from heavy charged
particles, such as pions, ions, protons and muons.
2.3.1 - Stopping power
The mean value of energy loss for ionization per path length is known as stopping power, Sl, also known as
dE/dx (where E is the particle energy and x is the distance travelled):
𝑆𝑙 = −
𝑑𝐸
𝑑𝑥
It is commonly measured in MeV∙m-1, and depends on the charged particle's energy, on the density of
electrons within the material, and hence on the atomic number of the atoms. A more fundamental way of
3
Energy is then lost with the emission of photons (Auger effect) or vibration or rotation
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Chapter 2 – Physics of Semiconductor Detectors
describing the rate of energy loss is to specify the rate in terms of the density-thickness, rather than the
geometrical length of the path, with the quantity called mass stopping power:
𝑆𝑚 = −
𝑑𝐸
1 𝑑𝐸
= −
𝑑(𝜌𝑥)
𝜌 𝑑𝑥
where ρ is the density of the material and ρx is the density-thickness.
2.3.2 - Energy loss by heavy charged particles
The mean energy loss of a charged particle through matter can be described by the Bethe-Bloch formula [21]:
𝑑𝐸
1 𝑑𝐸
1
𝑍 1
2𝑚𝑒 𝛾 2 𝛽2 𝑐 2
𝛿 𝐶
=
= 𝐷 2 𝑧 2 { ln
− 𝛽2 − − }
2
𝑑𝜉
𝜌 𝑑𝑥
𝛽
𝐴 2
𝐼
2 𝑍
𝐷 = 4𝜋𝑟02 𝑚𝑒 𝑐2 𝑁𝐴 = 0,307
𝑀𝑒𝑉 𝑐𝑚2
𝑔
with ρ the density of the material, x the depth into the material, β and γ the relativistic parameters of the
particle, z the charge of the particle, Z the atomic number of the material that is traversed, A the atomic
weight of the material, me the mass of the electron, c the speed of light, I average ionization energy of the
material, δ and C the relativistic corrections of the formula, r 0 the classical electron radius, NA Avogadro’s
constant.
Figure 2.2 - Energy loss of µ on Cu [2-4]
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Chapter 2 – Physics of Semiconductor Detectors
Figure 2.4 - Energy loss for heavy charged particles in
different materials [2-4]
Figure 2.3 - Energy loss for different particles [2-4]
Figure 2.2 shows the behaviour of energy loss for a µ particle as function of its momentum, while Figure 2.3
shows the same for different particles. Figure 2.4 shows the energy loss for heavy charged particles in
different materials, pointing out the fact that the minimum of the curve varies from 1.15 MeV for Pb to 2
MeV for He, with the exception of the H2. These graphs are plots of the energy-loss rate as a function of the
kinetic energy of the incident particle. It is important to notice that in Figure 2.4 the stopping power is
expressed using density-thickness units. As for photon interactions, it is found that when expressed as loss
rate per density-thickness, the curve is nearly the same for
most of the materials. To obtain the energy loss per path
length one needs to multiply the energy loss per densitythickness, shown in Figure 2.4, by the density of the
material. There is, however, a small systematic variation;
the energy loss is slightly lower in materials with larger
atomic numbers. At high incident energies there is also
some variation with density, because a higher density of
atomic electrons protects the more distant electrons from
interactions with the incident particle. This results in lower
energy loss rates for higher densities. Figure 2.5 shows the
silicon behaviour.
Figure 2.5 - Energy loss in silicon [2-4]
For low energies the stopping power varies approximately as the inverse of the particle's kinetic energy.
The rate of energy loss reaches a minimum, then starts to increase slowly with further grow in kinetic
energy. Minimum ionization occurs when the particle's kinetic energy is about 2.5 times its rest energy, and
its speed is about 96% of the speed of light in vacuum. At minimum ionization the energy loss is about 2
MeV cm2 g-1 (= 3 × 10-12 J∙m2∙kg-1 in SI units), which slightly decreases with the increasing atomic number of
the absorbing material. Given that the minimum of the curve is almost the same for all particles in all
materials, it is common to define this value as due to a Minimum Ionizing Particle (MIP), used to quantify
the minimum signal that can be expected as detector response without referring to a specific particle. For
silicon, the <dE/dx>min≈1.66 MeV cm2 g-1, as shown in Figure 2.6.
The probability distribution for the energy lost by a particle in a single hit follows a Landau curve, because
events with a high energy release can happen but are less probable. Experimentally, a Gauss curve is
obtained only when the thickness of the material allows to have many of hits with atomic electrons. For
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Chapter 2 – Physics of Semiconductor Detectors
thin depths, hits with atoms are not many, and hits with high energy loss can produce a tail in the
distribution through high energies.
A charged particle leaves a track in the material formed by ion-electron pairs and photons produced by deexcitation. For every material there exists an energy value for the production of pairs, independent of the
particle energy:
Δ𝐸
𝑊=
𝑛𝑇
with ∆E energy transferred by the incident particle, nT number of pairs created. In the definition of nT are
included the primary nP and secondary nS pairs as:
𝑛 𝑇 = 𝑛𝑃 + 𝑛𝑆
In silicon the mean energy loss of a MIP is 1.66 MeV cm 2 g-1, and the density is 2.33 g cm-3, which implies
that the energy loss is 390 eV/μm. Since to generate a hole-electron pair an energy of 3.6 eV is needed, it
follows that a MIP creates ~110 pairs per μm in silicon. For a thickness of 250 μm, a MIP creates about
20000 hole-electrons pairs, with 27000 as mean amount and 19400 as most probable value (MPV), that is
the peak of the Landau curve, as shown in Figure 2.6.
Figure 2.6 - Mean and Most Probable Value of energy loss of a MIP in 250 µm of silicon [2-4]
The loss of energy for a heavy charged particle as a function of the depth in the material follows a
characteristic behaviour: first the loss of energy is almost constant (or grows really slowly), and then, when
the particle’s speed is significantly reduced, there is a maximum peak (Bragg Peak) where most of the
particle’s energy is released before it stops. This allows to define the range of a particle in a material as the
distance travelled before being totally absorbed.
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Chapter 2 – Physics of Semiconductor Detectors
2.3.3 - Energy loss by light charged particles
Electrons lose energy in matter both with ionizing collisions with electrons and with radiative loss
(bremsstrahlung) due to accelerations in the electric field of the nuclei. The mean value of the energy is
given by the sum of the two contributions:
𝑑𝐸
𝑑𝐸
=
𝑑𝑥
𝑑𝑥
𝐵𝑟𝑒𝑚
+
𝑑𝐸
𝑑𝑥
𝐼𝑜𝑛
Since radiative loss is much stronger for lighter particles, it is much more important for beta particles
(electrons and positrons) than for protons, alpha particles, and heavier nuclei (but it happens also for
them). Bremsstrahlung starts to become important only at particle energies well above the minimum
ionization energy (for particle energies below about 1 MeV the energy loss due to radiation is very small
and can be neglected). The radiative energy loss is described by:
−
1 𝑑𝐸
𝜌 𝑑𝑥
𝐵𝑟𝑒𝑚
=
𝐸
𝑋0
with
1
4𝑍(𝑍 + 1)𝑁𝐴𝑉 2 183
=
𝑟0 ln 1
𝑋0
137𝐴
𝑍3
X0 is called radiation length, which is the distance over which the energy of an electron is reduced by a
factor e due to only radiation losses. At relativistic energies the ratio of energy loss by radiation to energy
loss by ionization is approximately proportional to the product of the particle's kinetic energy and the
atomic number of the absorber:
𝑑𝐸
1
𝑑𝑥 𝐵𝑟𝑒𝑚
=
𝑍𝐸
𝑑𝐸
580
𝑑𝑥 𝐼𝑜𝑛
where E is the energy and Z is the mean atomic number of the absorber. The kinetic energy at which the
energy loss by radiation equals the energy loss by collisions is called critical energy, Ec, and is approximately
𝐸𝑐 ≈
580 𝑀𝑒𝑉
𝑍
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Chapter 2 – Physics of Semiconductor Detectors
2.4 – Physics and behaviour of s emiconductors
From now on we will concentrate on semiconductors, and focus on the interaction of MIP particles with
silicon sensors to discuss the behaviour of silicon detectors for particle tracking. They can be used for
particle detection because they are materials with a little number of free charges, and particles passing
through them can easily produce a detectable quantity of electron-hole pairs. Semiconductor devices are
also widely used in electronics because of their specific electrical conductivity, σ, which is between that of
good conductors (>1020 cm-3 free electron density) and that of good insulators (<10 3 cm-3 free electron
density).
2.4.1 - Conduction in a solid
The structure of an isolated atom shows countable states of the electrons surrounding the nucleus,
characterized by a definite energy En4. In a solid the entire number of atoms that constitutes the lattice has
to be taken into account: the electron states become so dense to make them forming a continuous band of
allowed energy. These bands are separated by forbidden gaps that electrons cannot occupy (in Figure 2.7
the case of Silicon). Electrons fill the states starting from the lowest energy level available, filling the energy
bands up to a maximum energy.
Figure 2.7 – Band structure of Silicon
Qualitatively, there are two possible configurations: one with the last band partially filled, and the other
with the last band completely filled. The partially filled (or empty) band is called conduction band, while the
band below is referred to as valence band. In the case of a partially filled band, the solid is a conductor,
because when an electric field is applied the electrons can freely change state in the conduction band. In
the case of completely filled bands, the gap width between the valence and the conduction band can make
the solid an insulator (Φ ~10 eV) or a semiconductor (Φ ~1 eV). The conduction band can be accessed by
thermal excitation and in fact the thermal energy available at T ≈ 300 K is sufficient to bring some electrons
into the conduction band if the gap is of the order of 1 eV. To calculate the number of electrons with an
energy above a given value E0 , one must apply Boltzmann statistics, which gives the number n of electrons
having energy greater than E0. From this it follows:
𝑛 𝐸 > 𝐸0 = 𝑒
𝐸
− 0
𝑘𝐵 𝑇
where kB = 1.3807 ∙ 10−23 𝐽 ∙ 𝐾 −1 is the Boltzmann constant.
4
n is a set of integer numbers
25
Chapter 2 – Physics of Semiconductor Detectors
2.4.2 - Classification of Semiconductors
Although there is a large variety of semiconductor materials, there is one that stands out from the group:
Silicon. Its properties are well known, it is quite easy to find and to manage practically, and – last but not
least for the productive processes – inexpensive. Nevertheless, depending on the chemical composition,
each kind of semiconductor has different properties, and so is used for different applications. Elementary
semiconductors are located in the IV-A group of the Periodic Table of Elements (see Table 2.1), and they are
the Silicon (Si), the Germanium (Ge), the Grey Tin (α-Sn), and the Carbon (C), that can solidify in two
different structures (graphite and diamond, which is an insulator but with the same crystal structure as Si,
Ge and α-Sn).
Material
Diamond (C)
Silicon (Si)
Germanium (Ge)
Grey Tin (α-Sn)
White Tin (β-Sn)
a (nm)
0.357
0.543
0.566
0.649
0.583
0.318
EG (eV)
5.48
1.11
0.664
-
Structure
cubic
cubic
cubic
cubic
tetragonal
Table 2.1 - Lattice constant a, energy gap EG at 300 K and lattice structure of some group IV-A elements [2-5]
The main characteristic of the IV-A group elements is that they all have the outer shell of each atom exactly
half filled, and so by sharing the four electrons of the outer shell with other atoms it is possible to obtain a
three-dimensional crystal structure with no preferential direction (except for graphite), and it is also
possible to combine two IV-A group semiconductors in order to form useful compounds (such as SiC or
SiGe) with new properties (for example the SiC is a borderline compound between semiconductor and
insulator and can be useful for high temperature electronics). Also elements of group III (II) can be
combined with elements of group V (VI), with covalent bonds (but, in contrast with IV group ones, they
show also a certain degree ,~30%, of ionic bonds), to obtain semiconductors. Most of the III-V
semiconductors exist in the so-called zincblende structure (cubic lattice), and some in the wurtzite structure
(hexagonal lattice); GaAs and GaN are the most known and commonly used (for example for optical
applications, because they are direct gap semiconductors). It also exists a II-IV class of semiconductors,
characterized by an higher ionic bond percentage, ~60%, since the respective elements differ more in the
electron affinity due to their location in the Periodic Table of Elements, and a I-VII class, with larger energy
gap. There are other elementary semiconductors such as selenium and tellurium from group VI, the
chalcogenes, but only with two missing valence electrons to be shared with the neighboring atoms, so they
have the tendency to form chain structures. Finally, also some spare compounds can work as
semiconductors: they are the IV-VI (PbS, PbSe,PbTe), V-VI (B2Te3), II-V (Cd3As2, CdSb) compounds, a number
of amorphous semiconductors (the a-SI:H, amorphous hydrogenate silicon, for example, is a mixture of Si
and H), and the chalcogenide glasses (As2Te3, As2Se3, that can be used in xerography)[2-5].
26
Chapter 2 – Physics of Semiconductor Detectors
2.4.3 - Silicon
Silicon is used in detector technologies because only 3.6 eV are needed to create an electron-hole pair. It
has four valence electrons, so it can form covalent bonds with four nearby atoms. When the temperature
increases electrons in the covalent bond can become free, generating holes that can afterwards be filled by
other free electrons, so effectively there is a flow of charge carriers. The energy needed to break off an
electron from its covalent bond is given by Eg (gap energy). There exists an exponential relation between
the free-electron density ni and Eg, given by the formula:
𝑛𝑖 = 2(
𝑚𝑒 𝑐 2 𝑘𝐵 3 −2𝑘𝐸𝑔 𝑇 𝑒𝑙𝑒𝑐𝑡𝑟𝑜𝑛𝑠
𝑇)2 𝑒 𝐵 [
]
2𝜋(ℏ𝑐)2
𝑐𝑚3
For example, at T=300 K ni = 1.45 x 1010 electrons/cm3, and at T=600 K ni = 1.54 x 1015 electrons/cm3[2-6].
These electrons determine an intrinsic current in the silicon material when a voltage is applied. In pure
silicon, so called intrinsic, at equilibrium the number of electrons is equal to the number of holes. Electronhole pairs are continually generated by thermal ionization, and in order to preserve equilibrium
continuously recombine. The intrinsic carrier concentrations ni are equal for electrons and holes, small and
highly dependent on temperature. Holes and electrons both contribute to conduction, although holes have
smaller mobility due to the covalent bonding.
2.4. 4 – Doping of silicon
In order to produce either a silicon detector or a power-switching silicon device, it is necessary to greatly
increase the free hole or electron population. This is achieved by deliberately doping the silicon, adding
specific impurities called dopants. The doped silicon is called extrinsic and as the concentration of dopant
increases its resistivity ρ decreases. Pure silicon electrical properties can be changed by doping it with
group V elements of the periodic table, such as phosphourous (P), which create electrons (n-type silicon
doping, with free negative charges), or with group III elements, such as boron (B), which leave free holes (ptype silicon doping, with free positive charges), as shown in Figure 2.8. A group V dopant is called a donor,
since it makes available an electron for conduction. The resulting electron impurity concentration is
denoted by ND (donor concentration). If the silicon is doped with group III atoms, such as B, Al, Ga or In,
which have three valence electrons, the covalent
bonds in the silicon involving the dopant will
have one covalent-bonded electron missing. The
dopant is thus called an acceptor, which is
ionized with a net positive charge. The resultant
hole impurity concentration is denoted by NA
(acceptor concentration).
Figure 2.8- Doping of silicon [2-7]
27
Chapter 2 – Physics of Semiconductor Detectors
2.4. 5 – Generation and recombination of charge carriers
In thermal equilibrium the concentration of positive (p) and negative (n) charge carriers is constant in time
and obeys the mass action law due to the balance of generation and recombination of charge carriers:
𝑛𝑝 = 𝑛𝑖2
Electrons in n-type and holes in p-type silicon are called majority carriers, while holes in n-type and
electrons in p-type silicon are called minority carriers. Noticeable is the fact that the product of electron
and holes densities (n and p) is always equal to the square of the intrinsic electron density, regardless of
doping levels, as expressed by the mass action law. The carrier concentration equilibrium can be
significantly changed by the application of an electric field, by heat or by irradiation with particles. Such
carrier injection mechanisms create excess carriers.
The thermal generation rate, Gth, of charge carriers is:
𝐺𝑡𝑕 =
𝑛𝑖
𝜏𝑔
with τg being the generation lifetime. The recombination rate is proportional to the product of the charge
carrier concentrations, np. When the majority carrier concentration is practically unchanged, the
recombination is in fact limited by the concentration of the minority carriers, leading to:
𝑅=
𝑅=
𝑝
𝜏𝑟 ,𝑛
𝑛
𝜏𝑟,𝑝
𝑓𝑜𝑟 𝑛 − 𝑡𝑦𝑝𝑒 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙
𝑓𝑜𝑟 𝑝 − 𝑡𝑦𝑝𝑒 𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙
with τr,n/p the recombination lifetime in n- and p-type semiconductors, respectively. The numerical values of
τg and τr can differ significantly. In the presence of excess carriers the product of the electron and hole
concentration exceeds the value given in the mass action law. These excess carriers might be introduced by
injection or radiation, as explained in Chapter 5 of this thesis. After injection or radiation has stopped, a
thermal equilibrium is reached again by enhanced recombination proportional to the concentration of the
minority excess carriers. This leads to an exponential decay with the characteristic time τr. In case of
removal of the carriers the product of the carrier concentrations will fall below 𝑛𝑖2 and the generation,
which is unaffected by this change, dominates as the recombination rate will be very low. Generation
increases the carrier concentration and therefore also the recombination rate. This also leads to an
exponential return to the equilibrium condition but with time constant τg. If the generated carriers are
continuously removed, like in a reversely biased diode, the carrier concentration product will stay
permanently below 𝑛𝑖2 and the equilibrium state is never reached. The result is a steady generation current
of the drained carriers.
28
Chapter 2 – Physics of Semiconductor Detectors
2.4.6 - Charge transportation
A first mechanism of charge transportation in semiconductors is identified under the name of drift
mechanism: it simply consists in the application of an electric field at the extremity of the semiconductor,
so that charge particles will move at velocities (vh, ve) proportional to the electric field E:
𝑣 𝑕 = µ𝑃 𝐸
𝑣𝑒 = −µ𝑛 𝐸
where µP, µn are constants of proportionality called mobility. In silicon, at room temperature, typical values
of mobility are µn = 1450 cm2/(V∙s) for the electrons and µP = 450 cm2/(V∙s) for the holes. The total current
is the sum of the currents given by holes and electrons:
𝐽𝑇𝑂𝑇 = µ𝑛 𝐸 𝑛 𝑞 + µ𝑝 𝐸 𝑝 𝑞 = µ𝑛 𝑛 + µ𝑝 𝑝 𝐸 𝑞
It is important to note that the velocity does not increase linearly with the electric field, but saturates at a
critical value.
A second charge transportation mechanism is diffusion, that is due to the fact that charged particles move
from a region of high concentration to a region of low concentration.
Figure 2.9 - Diffusion in a semiconductor [2-7]
The diffusion current is proportional to the gradient of charge along the direction of flow, as shown in the
following equation:
𝑑𝑛
𝑑𝑥
𝐽𝑛 = 𝑞 𝐷𝑛
𝐽𝑝 = −𝑞 𝐷𝑝
𝐽𝑇𝑂𝑇 = 𝑞 (𝐷𝑛
𝑑𝑝
𝑑𝑥
𝑑𝑛
𝑑𝑝
− 𝐷𝑝
)
𝑑𝑥
𝑑𝑥
It is important to say that a linear charge density profile means constant diffusion current, whereas a
nonlinear charge density profile means varying diffusion current.
𝐿𝑖𝑛𝑒𝑎𝑟: 𝐽𝑛 = 𝑞 𝐷𝑛
𝑁𝑜𝑛 − 𝐿𝑖𝑛𝑒𝑎𝑟: 𝐽𝑛 = 𝑞 𝐷𝑛
29
𝑑𝑛
𝑁
= −𝑞𝐷𝑛
𝑑𝑥
𝐿
𝑑𝑛 −𝑞𝐷𝑛 𝑁 −𝐿𝑥
=
𝑒 𝑑
𝑑𝑥
𝐿𝑑
Chapter 2 – Physics of Semiconductor Detectors
There exists a relation between the drift and diffusion currents, although they are totally different. It is
Einstein’s relation, which connects diffusion constant and mobility constant to the absolute temperature:
𝐷
𝑘𝑇
=
µ
𝑞
2.4.7 - PN junctions
Electrons and holes are discrete charge carriers, and the current generated by their drift and diffusion is
affected by a noise proportional to the current itself. The amplitude of this intrinsic noise depends on the
resistance of the semiconductor used (230 kΩ∙cm for silicon), and it can unfortunately be of the same order
of the signal generated by a particle passing through the semiconductor material. It follows that
semiconductors as they are cannot be suitable for particle detection. A PN junction (shown in Figure 2.10)
can instead solve this problem.
A PN junction is the location in a doped semiconductor where the impurity changes from p to n while the
monocrystalline lattice continues undisturbed. A bipolar diode is thus created, which forms the basis of any
bipolar semiconductor device. In order to understand how a diode works, it is necessary to study its three
operation regions: equilibrium, with the depletion zone and the built-in potential, forward bias, with the I-V
characteristic curve, and reverse bias, with the junction capacitance.
Figure 2.10 - PN junction and electrical schematic [2-7]
2.4.8 - Diffusion across the junction
Each side of the junction contains an excess of holes or electrons compared to the other side, and this
situation induces large concentration gradients. Therefore, a diffusion current flows across the junction
from each side, as shown in Figure 2.11.
Figure 2.11 - Diffusion in a PN junction, with nn concentration of electrons on n side, pn concentration of
holes on n side, pp concentration of holes on p side, np concentration of electrons on p side [2-7]
As free electrons and holes diffuse across the junction, a region of fixed ions is left behind. This region is
known as the depletion region, and is particularly attractive for particle detection purposes, because
30
Chapter 2 – Physics of Semiconductor Detectors
charges created by a passing-through particle are going to be swept out by the electric field generated in
this zone (see Figure 2.12), and can be detected by electronics connected to the junction.
Figure 2.12 – Creation of the depletion zone [2-7]
The fixed ions in the depletion region create a build-in potential and an electric field that results in a drift
current; at equilibrium, the drift current flowing in one direction cancels out the diffusion current flowing in
the opposite direction, creating a net current of zero. The built-in potential depends on the dopant
concentration:
𝑉0 =
𝑘𝐵 𝑇 𝑁𝐴 𝑁𝐷
ln 2
𝑞
𝑛𝑖
This has to be added to the contact potential VC, that is the potential difference across the junction (for
silicon is about 0.7 V).
2.4.9 – Biasing the junction with forward bias
There are two ways for biasing the junction: one is the direct, the other is the reverse way. When the ntype region of a diode is at a potential lower than the p-type region, the diode is in forward bias, as shown
in Figure 2.13. This situation shortens the depletion width and decrease the built-in potential. Under this
condition minority carriers in each region increase, and diffusion currents also increase to supply them.
Recombination of the minority carriers with the majority carriers accounts for the dropping of minority
carriers as they go deep into the p or n region.
Figure 2.13 - Forward biasing [2-7]
31
Chapter 2 – Physics of Semiconductor Detectors
2.4.10 – Biasing the junction with reverse biasing
Opposite to the previous situation, when the n-type region of a diode is connected to a potential higher
than the p-type region, the diode is under reverse bias, which results in a wider depletion region and a
larger built-in potential across the junction, as shown in Figure
2.14. This is important for creating a depleted zone as wide as
possible in order to increase the sensitive zone useful for particles
detection. Varying the value of the applied bias V R it is possible to
vary the width of the depletion zone W, according to the
formula[2-1]:
𝑊 = 𝑥𝑛 + 𝑥𝑝 =
2𝜀0 𝜀𝑆𝑖 1
1
+
𝑒
𝑁𝐴 𝑁𝐷
𝑉0 + 𝑉𝑅
where xn and xp are the widths of the depletion zone on the n and
p side, respectively, and ε0 and εSi are the absolute and relative
dielectric constants (εr = 12 for Silicon). In silicon sensors the
junction is usually realized by a shallow and highly doped p+ (NA>
Figure 2.14 - Reverse biasing [2-7]
1018 cm-3) implant in a low-doped n (ND≈1012 cm-3) bulk material;
therefore the term 1/NA can be neglected, meaning that the depleted zone extends much deeper into the
lower doped side of the junction. Moreover, also the built-in voltage can be neglected because it is small
compared to typical operation voltages (0.5 V compared to 50 V). This leads to:
𝑊 ≈ 𝑥𝑛 ≈
2𝜀0 𝜀𝑆𝑖
𝑉 =
𝑒𝑁𝐷 𝑅
2𝜀0 𝜀𝑆𝑖 𝑉𝑅 µ𝜌
where the second part of the equation is obtained introducing the resistivity ρ. This is an important
parameter to characterize doped silicon:
𝜌=
1
𝑒𝑁𝐷 µ
and it depends on the dopant density ND and on the majority carrier mobility µ (e elementary charge of the
electron).
The width of the depletion zone increases with the applied voltage, and reaches a maximum at which the
junction breaks down and becomes conductive (breakdown zone). This is also the point at which the
electric field reaches its maximum value:
𝐸𝑚𝑎𝑥 =
2𝑉𝑅
≈
𝑊
2𝑒𝑁𝐷
𝑉
𝜀0 𝜀𝑆𝑖 𝑅
A PN junction can also be thought as a voltage dependent capacitor with its capacitance described by the
following equation:
𝐶𝑗0
𝐶𝑗 =
1+
32
𝑉𝑅
𝑉0
Chapter 2 – Physics of Semiconductor Detectors
with 𝐶𝑗0 =
𝜀 𝑆𝑖 𝑞 𝑁𝐴 𝑁𝐷
2 𝑁𝐴 + 𝑁𝐷 𝑉0
.
2.4.11 – I-V characteristic curve of a PN junction
The current vs voltage relationship of a PN junction is exponential in the forward bias region, and relatively
constant in the reverse bias region:
𝑉𝐷
𝐼𝐷 = 𝐼𝑆 (𝑒 𝑉𝑇 − 1)
Figure 2.15 – I-V characteristic curve [2-7]
Junction currents are proportional to the junction’s cross-section area; so two PN junctions put in parallel
are effectively one PN junction with twice the cross-section area, and hence twice the current. When a
large reverse bias voltage is applied, breakdown occurs and a huge current flows through the junction (see
Figure 2.15).
There exist two kinds of reverse breakdown: Zener and Avalanche breakdown.
33
Chapter 2 – Physics of Semiconductor Detectors
2.5 – Semiconductor silicon detectors
In principle a semiconductor detector behaves like a ionization chamber, with a simple configuration made
by an absorbing medium, the semiconductor in PN junction configuration, with two highly doped p+ and n+
electrodes on the opposite side (see Figure 2.16). The electrodes are themselves connected to an external
reverse bias supply, which creates the electric field in the PN junction and the depleted zone empty of free
charges. When a particle passes through the material and generates charged carriers this electric field
makes the charges drift to the respective electrodes, holes to p+ and electrons to n+ , producing the signal.
Electron-hole pair production energy for silicon is 3.6 eV [2-8], and is much lower than the one for ionizing a
gas, ~30 eV, with the advantage of producing bigger signals, directly proportional to the released energy.
Figure 2.16 - Example of silicon detector geometry
The full depletion voltage Vdepl is the voltage needed to extend the depletion zone W (defined in 2.4.10)
over the whole thickness d of the substrate:
𝑉𝑑𝑒𝑝𝑙 =
𝑒𝑁𝐷 𝑑 2
2𝜀0 𝜀𝑆𝑖
and depends on the substrate thickness and the substrate doping concentration ND. There exist different
doping configurations and electrode geometries of silicon detectors, which will be discussed in the next
chapter, focusing on the new architecture of 3D pixel sensors.
2.5.1 - Capacitance
By applying a reverse bias charges are built up on both sides of the detector and therefore the depletion
zone can be seen as a charged capacitor of value C per unit area:
𝐶 𝑉𝑅 =
𝑒𝜀0 𝜀𝑆𝑖
𝑁𝐷
𝑉𝑅
𝜀0 𝜀𝑆𝑖
𝑑
𝑓𝑜𝑟 𝑉𝑅 < 𝑉𝑑𝑒𝑝𝑙
𝑓𝑜𝑟 𝑉𝑅 > 𝑉𝑑𝑒𝑝𝑙
which implies that the increase of the reverse bias voltage increases the thickness of the depletion zone
and reduces the capacitance of the sensing element, and both these effects increase the signal-to-noise
34
Chapter 2 – Physics of Semiconductor Detectors
ratio (S/N), as will be shown in Chapter 4 of this thesis. Fully depleted detectors (with depletion zone
extending to the whole thickness of the silicon layer) gives the best S/N.
2.5.2 – Substrate and electrodes type
There are various ways to obtain a functional silicon detector. Table 2.2 is a summary of all the possible
configurations of substrate and electrode types:
Readout electrode
Substrate
p-type
n-type
p+
Double-sided process
(expensive). No
advantage over p+-in-n
Typical single-sided
processed sensor for
most applications
n+
Single-sided process.
May be a replacement
of n+-in-n in future
Double-sided process
necessary. Present
"standard-device" if
radiation hardness is
required
Table 2.2 - All possible combinations of substrate and electrode types [2-1]
2.5.3 – Signal development
Silicon detectors act as independent diodes: if reversely polarized they allow very little current passing
through them. There remains a small current generated by temperature, called “thermal background
current”. If a particle passes through the detector it creates charged carriers, which, if generated in the
depletion zone lead to a detectable current signal since higher than the thermal background current. Under
conditions of thermodynamic equilibrium at a temperature T, the uncertainty in the stored charge (the
charge fluctuation at fixed voltage) is given by:
< 𝜍𝑄 >2 = 𝑘𝐵 𝑇𝐶
This is known as kBTC noise.
Relativistic particles lose energy through collisions with the electrons of the crystal and generate ~110 e --h
pairs per micrometer of path in a few micrometer wide cylinder around its main trajectory. These charges
drift under the action of the external electric field at a speed which depends on the electric field. During the
drift the charges do not exactly follow the electric field lines, but also diffuse as a consequence of the
random thermal motion in the crystal lattice. Spread of the arrival position of the charge due to this effect
can be described as a Gaussian distribution with standard deviation
σ=
2Dt
which results in a spread of a few micrometers at the collecting electrode. The diffusion constant is higher
for electrons than for holes, as it scales with the mobility.
A magnetic field can be used to measure the momenta of the charged particles through the deflection of
their trajectories according to the Lorentz force. The magnetic field acts on all charged particles and
35
Chapter 2 – Physics of Semiconductor Detectors
therefore also on the electrons and holes drifting inside the silicon, which deviate from the electric field
lines by the Lorentz angle θL:
𝑡𝑎𝑛𝜃𝐿 = µ𝐻 𝐵⊥ ≈ µ𝐵⊥
where B⊥ is the magnetic field component perpendicular to the electric field, μH is the Hall mobility, and μ is
the carrier mobility. Typical Lorentz angles range from a few to 20°.
2.5.4 - Photon detection
A photon interacts with a semiconductor and creates charge when its energy is higher than the silicon
energy gap of (1.11 eV), which corresponds to a λ of 1.12 μm (infrared region). If a photon has a
wavelength longer than 1.12 μm, it will cross the silicon sensor without being absorbed. For indirect band
gap semiconductor, such as germanium and silicon, the absorption of a photon is possible only involving a
phonon, which gives the additional momentum necessary to the electron to jump to the conduction band.
Indirect band gap semiconductors are characterized by an absorption coefficient growing gradually with the
photon energy; when the photon energy is high enough to allow the direct transition from the valence to
the conduction band, phonons are no longer required for the excitation, and the absorption coefficient
saturates. For direct band gap semiconductors, such as GaAs, the coefficient grows for energies close to the
energy gap value, and the transition does not require an extra particle like the phonon in order to conserve
momentum.
In a silicon detector, photons can be absorbed within the depletion region, electron-hole pairs are
produced, and the electrostatic field within the depletion region drifts the electrons to the n+ side and the
holes to the p+ side, decreasing the amount of stored charge.
2.5.5 – Charged Particle detection
The mean energy transferred per unit path length by charged particle passing through matter follows the
Bethe-Bloch formula. For high energy particles, the mean energy transferred to matter reaches a minimum,
which is nearly the same for protons, electrons and pions and grows slowly for higher energies; particles
having energies high enough to reach this minimum are knows as Minimum Ionizing Particle (MIP). The
typical energy spectrum of a MIP crossing a semiconductor material follows a Landau distribution,
characterized by an evident asymmetric shape given by the long tail for high energy losses which is due to
high energy recoil electrons (δ rays). Due to the asymmetry, the Most Probable Value (MPV) of the energy
loss, corresponding to the peak, differs from the mean energy loss, which is shifted at higher energies.
2.5.6 - Functionality of silicon detectors
Holes and electrons created by the passage of a MIP through the depleted zone move respectively towards
p+ and n+ sides, driven by the electric field. The depth reached by a charge carrier as function of time is
calculated as:
𝑥𝑒,𝑕 =
𝑑 (𝑉 + 𝑉𝑑𝑒𝑝𝑙 )
𝑑(𝑉 + 𝑉𝑑𝑒𝑝𝑙 ) ∓2𝜇 𝑛 ,𝑝 2𝑉𝑑𝑒𝑝𝑙 𝑡
𝑑
+ 𝑥0 −
𝑒
2𝑉𝑑𝑒𝑝𝑙
2𝑉𝑑𝑒𝑝𝑙
with x0 the position at t=0. The corresponding velocities can be calculated with:
2𝑉𝑑𝑒𝑝𝑙 𝑥0 𝑉 + 𝑉𝑑𝑒𝑝𝑙 ∓2𝜇 𝑛 ,𝑝 2𝑉𝑑𝑒𝑝𝑙 𝑡
𝑑𝑥𝑒,𝑕
𝑑
= ±𝜇𝑛 ,𝑝
−
𝑒
𝑑𝑡
𝑑2
𝑑
36
Chapter 2 – Physics of Semiconductor Detectors
The electron is stopped at xe(te)=d, and the hole at xh(th)=0, having drift times of:
𝑡𝑒 =
𝑉 + 𝑉𝑑𝑒𝑝𝑙
𝑑2
𝑥0 2𝑉𝑑𝑒𝑝𝑙
𝑙𝑛
(1 −
)
2𝜇𝑛 𝑉𝑑𝑒𝑝𝑙
𝑉 − 𝑉𝑑𝑒𝑝𝑙
𝑑 𝑉 + 𝑉𝑑𝑒𝑝𝑙
𝑡𝑕 =
𝑑2
𝑥0 2𝑉𝑑𝑒𝑝𝑙
𝑙𝑛(1 −
)
2𝜇𝑝 𝑉𝑑𝑒𝑝𝑙
𝑑 𝑉 + 𝑉𝑑𝑒𝑝𝑙
The current induced by a moving charge q, which can be measured by a charge sensitive preamplifier, is:
𝑖 𝑡 =
=
𝑞 𝑑𝑥 𝑞
𝑑𝑥𝑒 𝑑𝑥𝑕
=
−
+
=
𝑑 𝑑𝑡 𝑑
𝑑𝑡
𝑑𝑡
−2𝜇 𝑛 𝑉𝑑𝑒𝑝𝑙 𝑡 0 (𝑡 𝑒 −𝑡)
−2𝜇 𝑝 𝑉𝑑𝑒𝑝𝑙 𝑡 0 (𝑡 𝑕 −𝑡)
𝑞
𝑥0
𝑑2
𝑑2
2𝑉
−
(𝑉
+
𝑉
)
𝜇
𝑒
+
𝜇
𝑒
𝑑𝑒𝑝
𝑙
𝑑𝑒𝑝𝑙
𝑛
𝑝
𝑑2
𝑑
2.5.7 - Signal readout
In order to collect and read the signals produced by the charges created inside the depletion zone of a
silicon sensor, an appropriate readout system has to be designed and connected to the sensor. There are
many ways to create this kind of system, but the most used is to connect via wire or bump bonds the
sensors to a Front-End (FE) electronics chip able to read out the currents coming from the electrodes of the
connected sensor. A silicon sensor cannot be useful without a readout, so the two parts together form the
silicon detector concept. Various sensor geometries and detector concepts together with the ATLAS FrontEnd electronics are going to be fully explained in the next chapter.
37
38
CHAPTER 3
SILICON PIXEL DETECTORS
39
Chapter 3 – Silicon Pixel Detectors
40
Chapter 3 – Silicon Pixel Detectors
T
he aim of this chapter is to describe the silicon sensors in use or under investigation for tracking
detectors in High Energy Physics (HEP) Experiments; principally they are characterized by pixel
layouts with planar or 3D structures, built to be radiation hard and to cope with the forthcoming
higher fluences of particles. Present detectors, mainly for vertex reconstruction, use planar pixel sensors
but the 3D architecture looks very promising.
The 3D silicon detector concept has been first proposed in 1997 by S. Parker, as a promising new solid state
radiation detector architecture, consisting in an array of columnar electrodes of both doping types,
oriented perpendicularly to the wafer surface and penetrating through the entire substrate thickness [3-1].
The innovation and main advantage of this geometry is the decoupling of the substrate thickness from the
electrode distance, resulting in short inter-electrode distances in the sensor that allow to have low
depletion voltages, short collection distances, charge sharing reduction and the possibility of operating
active edge solutions, terminating the sensor with heavily doped trenches. With this last solution the
insensitive edge region can be reduced to a few μm, in order to facilitate the overall detector layout and to
reduce the material budget, since no sensor overlap is needed within the same layer [3-2]. Moreover, all
these properties make 3D sensors very high radiation tolerant, and can effectively reduce charge trapping
effects due to high levels of radiation, but at the expense of a more complicated fabrication process. As a
consequence, the fabrication time, the complexity and the costs of a 3D structure are significantly higher if
compared to the traditional planar technology. Electrodes possible configurations can form pads, strips or
pixels, depending on the application.
3.1 – Strip detectors
Silicon detectors can be obtained with different electrode shapes or different doping configurations,
according to the performance, efficiency and resolution wanted. A strip detector, commonly used in
various tracking devices, is obtained by creating one electrode segmented in thin parallel strips, and this is
usually called a “single-sided microstrip detector” *2-1]. Ion implantation and photolithographic techniques
are used to selectively dope the surfaces of the semiconductor wafer, of typically 300 μm thickness, and to
deposit the metallization patterns necessary to extract the signals, as shown in Figure 3.1:
Figure 3.1 - Strip detector typical pattern [3-3]
A more complex pattern can be obtained by making rear contacts with thin strips tilted with respect to the
strips implanted on the front side; this configuration is useful to detect two coordinates. The inconvenient
of this pattern is the presence of “ghost hits”, in case of more than one hit, as shown in Figure 3.2:
41
Chapter 3 – Silicon Pixel Detectors
Figure 3.2 – Ambiguity problem of strip detectors [3-3]
The ambiguity problem of multiple hit events is frequent with high particle fluxes. With reference to Figure
3.2, if n = 2 or more particles hit the same sensor without the possibility to separate the strip signals in time
and strips of each strip direction show a hit, p = n! hit allocations (represented by different colors in Figure
3.2) are possible. So it is not possible to distinguish between the n real and the p-n ghost hits. If pulse
height information is provided by the readout electronics systems, with equal amplification for each strip,
the ambiguity for small hit numbers n can be resolved by comparing the pulse heights. The crossings of
equal pulse heights represent the realized hit allocation (black circles for n = 2 case in Figure 3.2) [2-1].
3.2 – Pixel detectors
Away to obtain two dimensional information for high particle fluxes is to segment one of the electrodes in
both directions: it’s the pixel detector concept. In fact, to obtain both coordinates from the same microstrip
detector, both sides have to be segmented; pixel detectors, in contrast, measure both spatial coordinates
on the same side of the sensor, and segmentation is therefore necessary only on one side of the sensor.
The differences between the two configurations are shown in Figure 3.3. With these detectors the number
of electronic channels does not increases with only one of the detector dimensions, like for strip detectors,
but with the area of the detector. Moreover, the pixels have to be connected to the front-end chip at the
segmented electrode side of the sensor, by means of the bump-bonding technique. This layout is called
hybrid pixel detector, and is going to be explained in Section 3.4.2. Another possibility is to integrate parts
or the entire front-end electronics in the sensor, obtaining the so-called monolithic pixel detector.
The main differences between microstrip and pixel detectors are the following:



Implants with higher segmentation
Connection of the front-end electronics directly to each pixel and not on the sensor periphery
Low capacitance, that allows fast signal shaping with very low noise
Figure 3.3 - Comparison between strip and pixel detector layouts [3-3]
42
Chapter 3 – Silicon Pixel Detectors
3.2.1 – Pixel capacitance
The total capacitance of each pixel determines the noise of the preamplifier of the front-end electronics [21], which is discussed in detail from Section 3.4.5. In addition, the capacitance between a pixel and its next
neighbour cell determines the cross talk between pixels. The total capacitance is made of [2-1]:




𝐴
Capacitance to the backside, that can be calculated with the classical formula 𝐶 = 𝜀0 𝜀𝑆𝑖 , with A
𝑑
area of the pixel and d thickness of the sensor (~8.5 fF for cells of 50 x 400 µm 2 and 250 µm thick)
Sum of the capacitances to the neighbour pixels, that is the largest contribution to the total
capacitance, and is approximately proportional to the perimeter of the pixel (this is why squareshaped pixel are advantageous)
Capacitance to the ground plane of the (closely spaced) readout chip
Other (small) contributions, like the capacitance of the bumps
A total pixel capacitance of ≤100 fF for square pixels of about 125 × 125 μm2 (close to the choice of the CMS
experiment) and ≤200 fF for long and narrow pixels of 50 × 400 μm 2 (choice of the ATLAS experiment) is
expected.
3.2.2 – Cross talk, spatial resolution and charge sharing in pixel detectors
A signal charge deposited in one pixel can, via capacitive coupling, induce a signal on its neighbours: it is the
so-called cross talk, that has to be kept as low as possible.
Spatial resolution of a pixel detector can immediately be established knowing the pitch p of the detector:
𝜍𝑝𝑜𝑠𝑖𝑡𝑖𝑜𝑛 =
𝑝
12
Another characteristic of a pixel detector is the charge sharing: two (or more) pixels can be triggered by the
same particle if the signal charge is shared between the pixels (a group of pixels showing a signal from the
same particle is called cluster). Charge sharing is mostly determined by the position and angle of the track
with respect to the sensor surface, as shown in Figure 3.4a–c, and can be also produced by a magnetic field
surrounding the sensor, as shown in Figure 3.4d-e. Experiments try to get advantage from charge sharing
mounting the detectors with a tilted angle, since charge sharing allows a better reconstruction of the hit
position by weighting the various pixels of a cluster with the charge (basically by taking in account the
centroid of the cluster).
Figure 3.4 - Charge sharing effect [3-3]
43
Chapter 3 – Silicon Pixel Detectors
A possibility of improving the spatial resolution in one of the directions without changing the pixel size is to
arrange the pixels in a bricked pattern as shown in Figure 3.5b. This is especially useful when the pixel
shape is not squared but rectangular with a high aspect ratio. If two pixels from different rows are triggered
in the same cluster, the effective pitch along the horizontal axis is halved. At the pixel corners only three
pixel cells join, reducing the probability for four-pixel clusters. Further advantage of such a pattern is that
the capacitance to the next neighbour responsible for cross talk is halved in one direction, which is, in the
case sketched, the more critical direction. However, the bricked pattern is not easily compatible with a
mirrored bump pad geometry favored by most readout chips.
Figure 3.5 - Pixel patterns [3-3]
3.3 –Plan ar and 3D pixel detectors
Silicon pixel sensors built using planar technology have the electrode structures parallel to the surface and
restricted to be within a few microns of the wafer’s top and bottom surfaces. In contrast, the threedimensional (3D) architecture have electrodes perpendicular to the wafer’s surface, extend partially or
completely through the volume of the wafer5. A schematic view of a full 3D sensor is shown in Figure 3.6,
with the front surface in the drawing cut through the middle of three n-type electrodes that penetrate all
the way from the top surface to the bottom. Both planar and 3D silicon sensors are reversely biased, with
the difference that in the planar sensors the electric field is largely perpendicular to the surfaces, while in
3D sensors it is parallel.
Figure 3.6 – 3D detector showing electrode layout [3-2]
The 3D architecture has several advantages with respect to the planar one; among them are the following
[3-4]:
1) In a planar sensor the depleted region proceeds vertically and the full depletion voltage depends on the
substrate thickness, while in a 3D detector the depletion region proceeds laterally in between columnar
electrodes of different type. Charged carriers created by passing-through particles move to the electrodes
following parallel directions, and reach them nearly at the same time; combined with the short interelectrode distance, this charge produces a large pulse with a fast rise-time. Full depletion depends only on
the electrode distance, that for 3D sensors can be one order of magnitude smaller than the detector
thickness. Since it decreases with the square of the electrode distance, a 3D detector with, for example, an
5
Details on how these devices were first proposed as well as simulations can be found in [3-1]
44
Chapter 3 – Silicon Pixel Detectors
inter-electrode distance of 30 μm has a full depletion voltage 100 times lower than a 300 μm thick planar
silicon detector.
2) 3D structures have very small collecting distance and short collection time. In a planar sensor a ionizing
particle generates charges at different electrode distances determining different collection times for
carriers; in a 3D detector the carriers have all the same electrode distance and the arrival time spread is
extremely reduced (see Figure 3.7).
3) The use of a 3D architecture reduces the drift path of the signal carriers and hence produce higher signalto-noise ratio for materials with significant charge trapping and hence poor charge collection efficiency
(such as GaAs [3-5] and diamond).
4) 3D detectors show superior radiation hardness than planar sensors, since the small collection distance
reduces the trapping probability at high fluences 6. Irradiation of the silicon with high fluences of interacting
particles produces damage centers that, in depleted silicon, are charged, increasing the voltage required to
fully deplete a silicon detector [3-6]. With respect to standard planar sensors, 3D sensors can be still fully
depleted after irradiation with higher fluences because the distance between electrodes of opposite sign is
smaller [3-7]. Radiation hardness of silicon detectors will be discussed in Chapter 5 of this thesis.
5) The possibility to add active edges [3-8] in 3D sensors allows to have detectors with negligible dead
volume at the edges, as it is not usually the case with guard rings in planar sensors.
6) 3D sensors have lower charge sharing thanks to an electrode configuration that provides high shielding
effect7.
Figure 3.7 compares the way in which charges are collected by a 3D and a standard planar device. For a 3D
detector, the distance between electrodes is limited only by the electrode dimensions (or “aspect ratio”),
and can be made as little as few tens of microns, allowing for very fast charge collection and low bias
voltages [3-9]. The new generation of Deep Reaction Ion Etchers [3-8], used to fabricate deep column
electrodes and active edges, allows to reach aspect ratios of ~25:1, that means an electrode diameter of
~10 microns [3-10].
Figure 3.7 - Differences between 3D and planar segmented sensors in geometry and charge collection
6
7
as those expected at sHLC
appealing for X-ray imaging
45
Chapter 3 – Silicon Pixel Detectors
The advantages come at the expense of a more complicated fabrication technology, with more steps, that
requires Micro-machining steps such as Deep Reaction Ion Etching (DRIE) for the hole drilling, Chemical
Mechanical Polishing (CMP) for the removal of the poly-silicon in excess on the surface after the hole filling,
and the need of the support wafer because holes pass from side to side.
Column electrodes can be considered as low efficiency detector regions, so the response uniformity to
particles becomes a critical issue. For tracking purposing a simple tilt of a few degrees can be a valid
solution, as test beams on detectors have shown, as will be explained in Chapter 4 of this thesis.
The induced noise on the readout chip is higher in 3D than in a planar silicon structure, due to the small
electrode distance that increases the capacitance of the single sensitive element (pixel or microstrip)8.
3.3.1 - Active edges
3D technology is very interesting for the possibility of obtaining the so-called Active Edges. Exploiting the
DRIE process, “wall” electrodes can be realized at the sensor borders to reduce the dead area to a few
microns while closing the electric field lines [3-11]. Planar detectors need multiple guard ring structures at
the cutting edge of the silicon in order to prevent high leakage currents coming from the edge of the sensor
flowing into the active area, to smooth electric field from the active region to the edge and for the
confinement of the depleted region (sensitive area). Guard ring structures should be at least as wide as the
detector thickness to be effective,
so the dead zone is on average a few
hundred microns9. 3D sensors can
be diced by etching trenches with
the DRIE process. The trenches are
doped and filled with poly-silicon to
act as p+ or n+ electrodes. This
technique produces 3D detectors
with only a thin dead zone, as
represented in Fig. 3.8. Active edges
allow new designs for large area and
low mass devices, and the full
sensitivity of such detectors can be
of great advantage for applications
where several detectors have to be
stacked together to cover large
Figure 3.8 - Comparison between no active edge and active edge detectors
area. Large amount of material can
be saved since there is no need of
an overlapping region between one detector and the other [3-11]. Active edges can be also realized on
planar segmented detectors if the 3D architecture is not necessary, but saving material is a concern.
8
Nevertheless, in case of a thinned planar silicon sensor, the total capacitance can be comparable to that of a 3D
detector
9
The present pixel sensors of ATLAS, for example, have an active region which is only 85% of the total area.
46
Chapter 3 – Silicon Pixel Detectors
3.3.2 - 3D detector concepts
The first 3D sensor concept has been the Full-3D detector with active edges fabricated at the Stanford Nano
Fabrication Facility, California, U.S.A [3-12]. It is referred to as the standard 3D detector and is considered
as the state-of-the-art in this field. Detectors with this sensor concept have been fully tested in the past
years, confirming their radiation tolerance [3-13] and hit efficiency, measured in a 100 GeV pion beam at
CERN SPS [3-14]. The concept of Stanford 3D active-edge silicon sensors is shown in Figure 3.9; they are
built with different electrode configurations (the smallest inter-electrode spacing is 56 µm) and substrate
thickness of about 200 µm. Figure 3.9 presents a 3E detector, characterized by three junction electrodes
per pixel, with an inter-electrode distance of 71 µm and active edges.
Figure 3.9 – (a) Full 3D silicon detectors layout, (b) 3E electrodes configuration [3-15]
Signal development in these sensors can be calculated by Ramo’s theorem, that includes the effect of
charge trapping caused by irradiation damages in the sensor [3-10]. Because of the radiation hardness, full3D sensors are within the promising candidates for applications at the LHC, such as the very forward
detectors at ATLAS and CMS, the ATLAS IBL10 and the general pixel upgrade. Moreover they could play a
role in applications where high speed and high resolution detectors are required, such as the vertex
locators at the proposed Compact Linear Collider (CLIC) at CERN, responding to the requirements of
present and future trackers at colliding beam experiments. Full-3D sensors are being now produced also by
SINTEF, Oslo [3-16], and development of passing-through column detectors is ongoing at FBK-irst.
Besides standard 3D detectors, other modified 3D detectors have so far been proposed by other research
groups in the world. The proposed 3D architectures are shown in Fig. 3.10 [3-17].
10
Insertable B-Layer, 4th low-mass pixel layer, planned to be inserted in the present ATLAS Inner Tracker
47
Chapter 3 – Silicon Pixel Detectors
Figure 3.10 - 3D detector proposed until nowadays
Besides the already mentioned Stanford Full-3D sensors (a) and the FBK-3D DDTC sensors (b), that will be
described in the next section, the other main types are:
•
•
•
Semi-3D detector approach (c), featuring columns of only one doping type, penetrating not all the
way through the wafer with a blank implantation on the back for the ohmic contact. These
detectors have been proposed by FBK-Trento [3-18], and VTT-Finland [3-19], in 2004 and
independently developed. The sensors fabricated at VTT have been electrically tested, before and
after 6×1015 cm−2 proton irradiation [3-20]. Semi-3D pixel detectors were also characterized with
the MEDIPIX2 readout chip, showing a higher energy resolution with respect to planar sensors [321]. The development of semi-3D sensors ended in 2005. At the moment VTT has kept on
developing 3D technologies with the aim of fabricating and testing edgeless microstrip detectors on
six inch silicon wafers [3-22]. More results about the same approach can be found in [3-23],
concerning the developments at FBK-Trento
Semi-3D detectors with columnar electrodes of only one type, etched from the top, with the other
electrode type also implanted from the top (f) have been proposed by BrookHaven National
Laboratory BNL at the end of 2005 [3-24]. 3D detectors with both p + and n+ columnar electrodes,
etched on the same side and not penetrating all the way through the substrate (d) have also been
proposed by BNL. 3D-TCAD simulations have been performed to simulate the full depletion voltage
and the charge collection after irradiation.
Double-sided 3D detectors have been proposed by CNM (e) [3-25] and FBK [3-23] (b)
independently, with few differences in the fabrication process. The columns are etched from
opposite sides of the wafer for each electrode type and do not pass through the entire thickness so
that no support wafer is needed. CNM has initially fabricated detectors on four inch in n-type
wafers (with p+ readout). The columns are 250 μm deep on a 300 μm thick substrate. The first
layout included MEDIPIX2 pixel detectors and microstrip sensors suitable to be read out with the
LHCb chip; capacitance measurements have shown a lateral depletion on only 2 V and a total
depletion of 9 V [3-26]. Functional characterization with the MEDIPIX2 chip has shown a reduced
charge sharing with respect to planar sensors, thanks to the 3D electrode configuration [3-27]. A
microstrip detector has been irradiated up to 5×1015cm−2 neutron equivalent and at a bias of 200
V the chip have recorded a most probable charge of 12800 electrons from a MIP particle,
comparable with the results obtained by the Stanford group [3-28]. CNM have also finished the
48
Chapter 3 – Silicon Pixel Detectors
fabrication of new 3D double side sensors, including ATLAS pixel and long strips, on p-type
substrate with n+ readout.
3.4 – Devices under test
Here follows a description of the sensors tested for this thesis.
3.4.1 –FBK-3D sensors
A particular 3D detector concept is the so-called 3D-DDTC (Double-Side Double-Type Column), where the
electrodes are etched perpendicularly to the surface but without penetrating for the entire substrate
thickness, stopping at a few tens of micrometers from the opposite surface, that makes the support wafer
(wafer bonging) not necessary. The etching is made in sequence on both surfaces and the number of
process steps is highly reduced if compared to a standard 3D process. Columns are not filled with polysilicon, so that the related deposition and final chemical mechanical polishing steps are not required.
Sensors using this technology [3-29] have been fabricated at FBK-irst11 MT-Lab, in Trento (Italy), in
collaboration with INFN12. They are built on Float Zone, p-type substrate, high resistivity silicon wafers.
Columnar electrodes of different doping types are etched from opposite wafer sides, using the nonpassing-through columns technique with junction columns from the front side and ohmic columns from the
back side, stopping at a short distance13 from the opposite surface. The key process for the realization of a
3D detector is the Deep Reaction Ion Etching (DRIE), a strong anisotropic process that allows holes to be
made with a width/depth ratio of 20-25. The process is an iteration of a two step sequence: a plasma
etching based on SF6 (fluorine) is used to etch in a vertical direction rather than laterally; then fluorine is
pumped out and a chemical inert passivation C 4F8 covers the corners. The sequence starts again, with the
plasma etching digging the bottom of the hole, and so on.
The read-out columns are the junction columns, n+ doped, and they are connected by a surface n+ diffusion
and a metal strip that arranges them in the pixel configuration, while ohmic columns, p+ doped, are all
connected together by a uniform surface p+ diffusion and metallization on the back side of the sensor (see
Figure 3.11). All columns have a nominal diameter of 10 μm and are not filled with poly-silicon [3-30].
Figure 3.11 – (a) layout of two adjacent pixels , (b) schematic cross-section of the sensor [3-30]
11
Fondazione Bruno Kessler (FBK-irst), Via Sommarive 18, 38100 Povo di Trento, Italy
Istituto Nazionale di Fisica Nucleare
13
ideally not exceeding a few tens of micrometers
12
49
Chapter 3 – Silicon Pixel Detectors
Surface insulation in-between n+ electrodes is achieved by combined p-spray/p-stop implants [3-31]. The
fabrication technology is similar to that described in [3-29] for 3D-DDTC detectors made on n-type
substrates, except for: (i) the substrate type, (ii) the inverted doping of the columns and related surfaces,
and (iii) the additional steps for p-spray/p-stop implantation on the front side. In the high-field region of the
sensor where the columns overlap, the charge collection is fast, while only in regions with low electric field,
like at the bottom of the wafer close to the ohmic columns where full depletion is not easy to achieve,
there is a slower tail due to diffusion. This explains the fast charge collection (just a few ns), in spite of the
non-optimized junction column depth, so that good charge collection efficiency is expected using fast readout electronics (like that used for ATLAS pixels). The peculiar shape of the present ATLAS pixels (50 μm ×
400 μm) can lead to different choices in terms of number of columns per pixel, and consequently of pitch
between the columns (schematically represented in Figure 3.12). Three different inter-electrode distances
have been implemented, with 2, 3 or 4 electrodes per pixel. The high number of columns per pixel shortens
the collection distance, making the detector fast and more robust to radiation; on the other hand, this is
obtained at the expense of an increased capacitance, and thus an increased noise. The inter-electrode
distances for the three configurations are summarized in Table 3.1:
Sensor type
2E
3E
4E
Distance
(µm)
103.0
71.2
56.0
Table 3.1 – Inter-electrode distances
Figure 3.12 - Inter-electrode distances for 2E, 3E, 4E configuration
Two batches have been fabricated by FBK-irst using the non-passing-through column technique. Table 3.2
summarizes the main parameters of detectors from the two batches (the first one called DTC2 and the
second one DTC2b). The wafer thickness values are the nominal ones. The column thickness values have
been extracted from the C-V curves of test structures.
Value
Parameter
3D-DTC2
200 µm
100 - 110 µm
180 – 190 µm
90 - 100 µm
1 X 1012 cm-3
Substrate (p-type) thickness
Junction column (n+) thickness
Ohmic column (p+) thickness
Column overlap
Dopant concentration in the substrate
3D-DTC2b
200 µm
140 - 170 µm
180 - 190 µm
110 - 150 µm
7 X 1011 cm-3
Table 3.2 - Main parameters of FBK-3D DDTC detectors tested in this thesis [3-30]
50
Chapter 3 – Silicon Pixel Detectors
3.4.2 – Hybrid Pixel Detectors
The two-dimensional high-density connectivity is the key characteristic of a hybrid pixel detector (see
Figure 3.13), and it determines the need of a vertical connection between sensor and electronics, with
matching between the size of the pixel and the size of the front-end electronics channel. Moreover, the
readout chip must be very close (10-20 µm) to the sensor. To deplete the sensor a sufficiently high bias
voltage must be applied on the backside plane while all the pixels are grounded. A pixel sensor can hardly
be tested before being connected to the electronics with the bump bonding technique [3-32]. The readout
chip has the logic functions needed to extract, organize and transmit the signal out. Each pixel covers a very
small area (≈10-4 cm2) over a thin layer (≈300 µm) of silicon, so another aspect to be considered is the very
low capacitance (≈0.2-0.4 pF), dominated by the coupling to the neighboring pixels rather than to the
backside plane which has to be kept to a minimum with a proper sensor design to avoid cross talk between
pixels. This low capacitance allows to obtain fast signals with low noise. It is common to have noise figures
of ≈200 e− for electronics operating at 40MHz and therefore a S/N ratio exceeding 100 for fully depleted
300-μm-thick sensors. This is a very comfortable situation as it allows operation in absence of spurious
noise hits [2-1]. A detection threshold set at, e.g., 10ςnoise gives, in fact, full efficiency and very low
probability that a noise fluctuation exceeds the threshold. Another way of taking advantage of the excellent
S/N ratio is to consider that the detector is robust enough to tolerate even a considerable signal loss. So
also sensors that have poor charge collection or limited active thickness can be used, such as diamonds and
GaAs, or sensors damaged by high radiation flux. In summary, a hybrid pixel detector is the ideal detector
to work close to the interaction region of a particle accelerator because:
•
•
It provides non-ambiguous three-dimensional measurements with good time resolution (i.e. it can
operate in high instantaneous particle flux).
It provides the space resolution which is needed to measure short-lived particles.
Figure 3.13 - Hybrid pixel detector schematic [3-3]
51
Chapter 3 – Silicon Pixel Detectors
3.4.3 – Single Chip Assembly (SCA)
Pixel sensors studied in this thesis are bump-bonded on the current ATLAS Pixel read-out chip, called FE-I3
[3-33]. The bump-bonding process is based on Indium and it has been carried out at SELEX SI [3-34]. Figure
3.14 shows a snapshot of a single detector board, that is called Single-Chip Assembly (SCA).
Figure 3.14 - (a) Schematic of a SCA, (b) front view of a 3D FBK SCA, (c) back view of a 3D FBK SCA
The FE-I3 chip consists of 2880 cells of 50 × 400 μm2 size, arranged in a matrix of 160 × 18, matching the
geometrical characteristics of the sensor pixels. In each cell, the corresponding pixel charge signal is
amplified and compared to a programmable threshold by a discriminator. The digital readout provides
information on the hit pixel address, the hit time stamp and the digitized amplitude, expressed in terms of
Time over Threshold (ToT), which is the time measurement of the signal length above the discriminator
threshold. The ToT of a hit is determined by the width of the injected pulse and depends on the deposited
charge, on the discriminator threshold and on the feedback current. To measure the charge of a hit, the
discriminator output pulse is recorded in units of the LHC 40 MHz crossing clock [3-33]. FBK-irst has been
developing 3D detector technologies mainly oriented to the upgrade of the ATLAS Pixel Detector, and the
3D-DDTC approach is currently considered a possible alternative to standard 3D design for ATLAS-3D
Collaboration [3-15]. SCA characterized in this thesis are the ones produced at FBK-irst, with the 3D-DDTC
architecture which has been presented in the previous section. For this thesis extensive functional
characterization has been made on 3D FBK detectors compatible with the ATLAS readout chip, featuring a
pixel size of 50 μm x 400 μm with three types of columnar electrodes per pixel (2E, 3E, 4E configuration).
The detector characterizations and the results of β and γ source tests are the subject of the next chapter.
3.4. 4 - Cu rrent ATLAS Silicon Pixel detectors
ATLAS pixel sensors were developed to meet geometrical constraints concerning thickness and granularity
and to have a high charge collection efficiency, while sustaining a massive amount of ionizing and nonionizing particle radiation damage [3-35]. This is reflected in the selection of a high resistivity n-type bulk
material and on pixel structure design. The sensor is made by implanting high positive (p+) and negative (n+)
doped regions on each side of a wafer. An asymmetric depletion region at the p+/n junction operates in
reverse bias and extends over the whole sensor bulk volume (see Figure 3.15). The sensor design
guarantees single pixel isolation, minimizes leakage current and makes the sensor tolerant to a radiation
damage up to ≤ 1015 neq/cm2.
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Chapter 3 – Silicon Pixel Detectors
Figure 3.15 - Layout and depletion zone in n+-in-n pixel sensor [3-35]
The substrate has n+ implants on the read-out side and the p +-n junction on the back side. The ATLAS-like
planar sensors tested for this thesis have the same pitch (corresponding to 50 × 400 µm2) of 3D detectors,
but the bulk is thicker, (256 ± 3) µm. The main problem of this kind of sensor is that, aside from increased
leakage current, radiation damage will invert the sensor bulk and then gradually increase the depletion
voltage after some year of irradiation. For unirradiated sensors, the depletion starts at the back p-side,
where the pixels are not isolated from each other until full depletion of the bulk. Irradiation of the bulk
leads to a change in the effective doping concentration N eff (see Chapter 5). At type inversion, the junction
moves to the front n-side, isolating the pixels and enabling operation even if the bulk cannot be fully
depleted. Maximum achievable depletion is desirable to maximize the signal. Oxygen impurities have been
introduced in the bulk to increase tolerance of the silicon against bulk damage caused by charged hadrons
[3-40, 3-41]. In addition to the continuous irradiation of the sensors affecting the induced doping
concentration, Neff also evolves due to thermal effects. By choosing an appropriate temperature profile (i.e.
operation at 0 °C, short periods of +20 °C during ATLAS detector access, and cooling down to −20 °C during
longer operational breaks in the experiment), one tries to keep sensors near the lowest possible Neff and
avoid reverse annealing, so as to derive benefit from the lowest possible depletion voltage. The building
processes for this kind of sensor allow for a segmented n+ implantation used for the definition of pixel cells
and a guard ring structure on the p+ implanted wafer side, locating the main voltage drop on the sensor
surface opposite to the bump connections [3-38, 3-39]. The sensors can be fully depleted before type
inversion with bias voltages below 100 V. After type inversion the depletion zone grows primarily from the
segmented n+ implant when the region of highest electric field in the bulk now converts to p-type. On the
sensor front side, pixel structures are arranged and isolated by moderated p-spray [3-39, 3-40] implants,
which have proven to be radiation tolerant with respect to surface damages induced by ionizing charged
particles for doses up to 500 kGy in silicon. The sensor allows for a connection to each channel using a
bump-bond technique to front-end electronics FE-I3. In this thesis, current ATLAS planar detectors are used
as comparison for the characterization of new 3D detectors.
53
Chapter 3 – Silicon Pixel Detectors
3.4.5 – Front-End Electronics Description
After the discussion of the various kind of sensors, it is useful to describe the front-end electronics used for
ATLAS oriented pixel detectors, in order to have a complete portrait of the 3D devices under test. The
present front-end chip is the FE-I3 chip, and a new version of it, the FE-I4 chip, is currently being developed
and tested. Front-end chips have a few million transistors per square centimeter and a typical chip size
cannot, today, sensibly exceed 1 cm2 if a high enough yield (>50%) is desired [2-1].
The FE-I3 chip is implemented in a 0.25 µm CMOS technology using radiation tolerant layout rules, in order
to resist up to a total dose of 50 Mrad. The chip has an active dimension of 7.2 x 10.8 mm2, and contains
about 3.5M transistors. The chip has 2880 channels of charge sensitive amplifiers attached to a fast
digital readout, and it is designed for use in a pixilated tracker detector [3-41]. To reduce the multiple
scattering, the chip is thinned to a thickness of 180 µm. It digitalizes and buffers the pixel hit information
responding to the global ATLAS trigger system: the digital part operates synchronously to the 40 MHz beam
clock. The active area of the chip consists of 2880 readout cells of size 50 x 400 µm2 (matching the sensor
pixels), arranged in a matrix of 160 rows x 18 columns. Each cell contains an analogue block, where the
sensor charge signal is amplified and compared to a programmable threshold by a discriminator, and a
digital readout part, which transfers the hit pixel address, a hit time stamp and the digitalized amplitude
information, the Time over Threshold (ToT), to buffers at the chip periphery. Figure 3.16 shows the FE-I3
chip layout.
Figure 3.16 - FE-I3 layout with zoom on a single channel and on a
hit buffer cell [3-41]
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Chapter 3 – Silicon Pixel Detectors
The connection pads are located on the lower edge of the chip. The homogeneously coloured region above
contains the end-of-column logic, which takes care of the hit buffering and read-out driving. The upper
region shows the pixel electronics, organized in 160 rows and 9 double columns. Taking a closer look, the
blue lines can be identified as the individual pixel connection pads. The FE-I3 uses two power supplies: an
analogue supply VDDA, grounded to AGND, with a nominal value of 1.6 V, and a digital supply VDD,
grounded to DGND, with a range from about 1.4 V to 2.5 V and a nominal value of 2.0 V. Moreover, a
VDDREF is used to provide power only to the preamplifiers, and it works as reference for the preamplifier
inputs. It is connected to VDDA outside the FE. Current is roughly 75 mA on VDDA and 35 mA on VDD.
AGND and DGND are connected together outside the module. The logic for the pixel readout, located at the
bottom of the chip, consists of two stages. The first stage continuously scans the pixel cells for hits, and the
identified hits are copied to the end of column (EOC) buffers. Two columns (320 pixels) share a common
buffer with a depth of 64 hits. While a pixel is waiting for the transfer of its hit information it is insensitive.
If no buffer space is left, a hit is lost. Consequently the number of hits detectable in parallel, but also in
sequence, is limited. The second stage consists in empting the EOC buffers. In ATLAS the trigger to readout
a specific event arrives with a fixed delay (latency). At the arrival of the trigger the current bunch crossing
ID is taken, the latency is subtracted and the hits corresponding to the resulting bunch crossing ID are
marked for readout. The marked hits are serialized and clocked out in turn at the 40MHz speed of the
system clock. If the latency time has passed, hits for which no trigger has arrived are discarded. One
consequence of this two staged readout is that a hit is only visible if its ToT is smaller than the trigger
latency, as otherwise the hit has not yet been transferred to the buffers by the first stage [3-42].
While the trigger is usually supplied from outside, the chip is also equipped with a self trigger for testing
purposes. The self trigger uses the signal of all discriminator outputs linked by an OR and additional logic.
The functionality of the FE-chip can further be checked at several stages of the readout chain. First of all the
basic communication with the FE-chip can be verified by reading back the values written to the different
chip and pixel registers. The digital part of the hit detection and the readout stage can be tested with the
help of an externally applied strobe signal. The strobe signal can be used to overwrite the discriminator
output of selected pixel cells and thus for simulating hit detections. To check the pixel amplifier and
discriminator, each pixel cell contains a charge injection circuit. If enabled, the strobe signal is used to vary
the voltage applied to a capacity connected to the amplifier input. The voltage is switched between the
analog supply voltage (VDDA) and a calibration voltage V CAL. The resulting voltage step injects a charge
pulse into the amplifier input. Each chopper has two selectable capacitors with nominal values of C low = 7.5
fF and Chigh = 43 fF. The amount of injected charge is equal to:
𝑄𝑖𝑛𝑗 = 𝐶𝑙𝑜𝑤 /𝑕𝑖𝑔 𝑕 ∙ ∆𝑉
The charge is usually measured in units of the elementary charge e. The voltage V CAL can be generated
inside the chip with the help of a 10-bit digital-to-analogue converter (VCAL-DAC). Typically, the resulting
slope for ΔV is 0.9 mV/DAC. This corresponds to an injected charge of about 42 e - per VCAL-DAC step in the
case of Clow and of 240 e- for Chigh. The exact capacitor values of the individual FE-chips are measured during
the tests following the wafer production. The dispersion of the capacitor values between the different pixel
cells of a chip has been found to be in the order of 1.5% for C low and 2.3% for Chigh [3-43]. In addition, the
characteristics of the VCAL-DAC are measured during the test. The linearity of the DAC is measured to be
within one DAC value. The injection of a known amount of charge is used for the adjustment of the
threshold settings, the feedback currents and for the calibration of the ToT values . More details on the chip
electronics and further test possibilities are given in [3-33], [3-41], and more detailed figures and
schematics can be found in Appendix 1 of this thesis.
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Chapter 3 – Silicon Pixel Detectors
3.4.6 – Single channel
Single cells are also called channels, or simply pixels, and they fit the size of a single sensor pixel (50 x 400
µm2) of the SCA. A schematic view of a single channel is shown in Figure 3.17:
Figure 3.17 - Single channel schematic [3-33]
The analogue part copes with signal amplification and discrimination, with its behaviour controlled with
DACs, while the digital part collects the time stamps, measures consequently the ToT and transports the
measurements to the EOC logic.
As it is shown in Figure 3.17, the analogue part is mainly composed by:







an injector circuit, which injects charge from the outside using a V cal and two capacitors, Clow (8 fF)
and Chigh (32 fF), usable for testing or calibration purposes;
the bump pad to sensor, which connects the sensor to the read out circuit;
a preamplifier, with a feedback capacitor of 5 fF, which incorporates a DC feedback scheme able to
compensate DC leakage currents at the amplifier input of more than 100 µA;
a Feedback DAC (FDAC), a Trim IF and an IF DAC, which set the feedback current value;
a second stage amplifier followed by a discriminator, which set the threshold of a detectable signal
over the electronics noise;
a Global DAC (GDAC), which set the threshold level of the preamplifier globally over the whole chip;
a Trim DAC (TDAC), which set the threshold level of the preamplifier channel per channel.
The charge signal enters the FE from the sensor (or the injector circuit) and encounters the preamplifier,
which collects the charge in the 5 fF capacitor, which in turn is discharged by an adjustable constant current
source [3-42]. The preamplifier is designed for a silicon sensor of 250 µm thickness. A typical input signal of
about 20 ke-, equal to 3.5 fC, returns to baseline within about a micro second. Each amplifier can be
disabled to prevent noisy sensor pixels from continuously generating hit detections in the subsequent
stages, otherwise buffer overflows would result in losses of real hits. Then the signal passes through a DCpaird second amplifier and a differential discriminator. The threshold of the discriminator can be adjusted
in the range from 2000 e- to 5000 e- and even wider, if higher noise levels and/or higher pixel to pixel
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Chapter 3 – Silicon Pixel Detectors
deviations of the thresholds are acceptable. By design, the output signal of the amplifier peaks always after
the same time, independently of the amount of injected charge. The time constant of the exponential rise
function depends on the sensor capacitance and the transconductance of the preamplifier. The limit is thus
set by the tolerated chip power consumption. The finite rise time implies that a hit with a small charge
deposition crosses the threshold later than one with a larger charge deposition. Hits with small charge
deposition thus might show up in the next event as the discriminator output is sampled every 25 ns,
corresponding to the 40 MHz bunch crossing frequency of the LHC. This effect is usually referred to as time
walk. Due to the constant discharge current, the time between the leading and the trailing edge of the
discriminator signal, the Time over Threshold (ToT), is a direct measure of the deposited charge in a sensor
pixel.
3.4.7 – FE-I3 calibration
The FE-I3 chip has to be calibrated be correctly match the behaviour of the bump bonded sensor and the
tracking requirements: a wanted discriminator threshold can be obtained varying the GDAC and the TDAC,
a correct ToT can be tuned varying the IF, TRIMIF and the FDAC values. In this way every single channel of
the chip will have a similar response to detection of signals. In Figure 3.18 the relation between the
threshold and GDAC is shown.
Figure 3.18 - Discriminator threshold vs GDAC
It is clear that growing the GDAC value increases the discriminator threshold value. By applying a TDAC
calibration to the wanted threshold value, and so choosing the correspondent GDAC values, one can then
decrease the threshold sigma value.
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Chapter 3 – Silicon Pixel Detectors
In Figure 3.19 the relation between ToT and IF is shown, from which it is also clear that in order to decrease
the ToT value it is necessary to increase the IF value:
Figure 3.19 - ToT vs IF
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CHAPTER 4
CHARACTERIZATION AND TEST OF FBK-3D
PIXEL SILICON SENSORS
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T
he purpose of this chapter is to provide a detailed description of the electrical tests performed on
FBK-irst Double side Double Type Column (DDTC) silicon pixel detectors, in the configuration with 2,
3 and 4 electrodes per pixel developed for the ATLAS upgrade, in comparison with an ATLAS planar
n-in-n detector. The modules are usually called Single Chip Assembly (SCA) and consist of the PCB board
with one single sensor mounted onto it, matched to one ATLAS FE-I3 read-out chip and a LVDS chip for
digital communication [4-1]. The fabrication technology for DDTC sensors is simpler than that required for
full 3D detectors with active edge, but the detector efficiency and radiation hardness critically depend on
the columnar electrode overlap and should be carefully evaluated. Selected results from the electrical and
functional characterization with radioactive sources are also discussed.
4.1 - Sensor properties and performance tests
The following tests are aimed at analysing the specific sensor properties:


Leakage current distribution
Noise as a function of the bias voltage
The remaining tests are aimed at analysing the performance of the detectors:



Threshold and noise tuning (at 3200 e- threshold)
Time over Threshold (ToT) tuning (for one MIP at 60 ToT)
Source tests with gamma and beta sources (109Cd, 241Am, 90Sr)
Tests have been performed at room temperature (23-24 ̊ C), and also using a climate chamber (Vötsch
Industrietechnik VC 2020) in order to make measurements with temperature and humidity control.
4.2 – TurboDAQ s etup
The experimental setup used for the characterization of the detectors is the so-called TurboDAQ setup,
developed at the LBNL14. It has also been used to perform automated electrical test of ATLAS Pixel Detector
Modules during the production phase. It runs under Windows and is based on National Instruments
LabWindows development suite [4-2].
For completeness a layout of the system is given in order to easily refer to specific equipment in the test
description:
Hardware components:
 PC equipped with Pentium 4 processor or higher with at least 512 MB RAM
 National Instruments GPIB control card [4-3]
 National Instrument PCI-MXI2-VME kit [4-4]
 VME (Versa Modular Eurocard) crate [4-5]
 ATLAS Turbo Pixel Low Level card (TPLL) [4-6]
 ATLAS Turbo Pixel Control Card (TPCC) [4-6]
 Up to 4 Flex Read Out Card per TPCC for flex module characterization and/or custom made probe
card for bare module testing
14
Lawrence Berkeley National Lab, California, USA
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Chapter 4 – Characterization and Test of FBK-3D Pixel Silicon Sensors
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

Two LV power supplies with two channel each for TPCC and flex module front-end bias with at least
±5V and 2A rating (Agilent E3631A GPIB controlled)
Keithley 2410 Source Meter for I-V characterization and sensor bias voltage [4-7]
Software components:
 Windows 2000 or Windows XP operating system
 Visual Studio 6.0 or above
 National Instruments Measurement Studio 6.0 or above
 ATLAS Pixel TurboDAQ software [4-8]
 Cern Root software vrs. 5.20.00 [4-9] to be used together with the Pixel Module Analysis framework
in order to analyze data from the TurboDAQ more easily [4-10]
The 3D TurboDAQ standard measurement system is built as shown in Figure 4.1, and can be either mobile
or fixed:
Figure 4.1 - TurboDAQ setup
The measurements are performed by TurboDAQ software parametric scans. The scans are standardized
and their parameters are stored in configuration files (.cfg). For each kind of measurement a specific scan is
selectable from the software [Appendix 2]. Data for each modules are stored in a directory tree with the
top level identified by the module specific serial number (S.N.) for the specific detector module,
automatically generated the first time a new module is connected to the TurboDAQ by writing the S.N. in
the Configuration Console of the software [Appendix 2]. For data integrity it is essential that entering the
S.N. is the first operation which is done after connecting a module to the system. If a module has already
been tested (even in a different laboratory), a configuration file containing module information should be
available and must be loaded into the software. If not, a new configuration must be created. It should
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Chapter 4 – Characterization and Test of FBK-3D Pixel Silicon Sensors
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contain the measured values of the capacitances used for charge injection (Chigh and Clow) and the measured
slope of the VCAL DAC used for internal injection.
Within the above mentioned directory tree all measurement data files will have standard names, with a
test name for each test. The names are set from the TurboDAQ Data Control panel [Appendix 2], and for
our purposes they have been of the kind YEAR_MONTH_DAY_MEASUREMENT, to which the TurboDAQ
adds proper suffixes and extensions according to the measurement chosen (e.g. 2009-03-10-iv.iv for an I-V
scan measurement).
4.2.1 - Hardware description
The hardware setup allows the communication between the board under test and the test system. This is
routed by the VME controller board, while the TPLL board is used for clock generation and synchronization,
data FIFO, trigger FIFO, 16 Mbytes board SRAM support module level histogramming, and FPGA (see Figure
4.2).
Figure 4.2 – On the left, hardware mobile setup at CERN Lab161; on the right the TPCC and module board
A flat cable is used to connect the module board to the TPCC, and also this latter to the TPLL board: this
bridge transfers data coming from the detector under test to the TPLL, which converts them to be
transmitted on the VME bus to the PC. The TPCC card, shown in Figure 4.3, receives from two LV power
supplies four different values of voltage, to respectively supply itself (with +5 V for the analog part and -5 V
for the digital part) and the FE electronics on the module board (with +1.6 V for the analogical part and +2 V
for the digital part).
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Chapter 4 – Characterization and Test of FBK-3D Pixel Silicon Sensors
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Figure 4.3 - TPCC board
The leds on the left of the board serve as a control of the correct communication start between the TPCC
and the TurboDAQ software: if green, the communication has been set correctly, while if red initialization
problems have occurred. Moreover, an orange led lights in correspondence of the initialized channel, right
to the connector for the module board in use. Figure 4.4 shows in detail a SCA (or Detector Under Test,
DUT): it is, as an example, the module 2EM2, i.e. an FBK-3D pixel silicon sensor with two electrodes per
pixel bump bonded to the FE-I3 read-out electronics (in the centre of the card). The high voltage cable
supplies the bias voltage to deplete the sensor (negative voltage values).
Figure 4.4 - A SCA
4.2.2 - Software description
TurboDAQ runs under Windows, and is based on National Instruments's LabWindows developement suite.
TurboDAQ communicates to the SCAs via a combination of custom electronics (TPCC, TPLL) and a standard
PC-to-VME interface. This software allows to pilot the data acquisition and to display the data read out
from the pixel detector. It is written in CVI language, which is why the software LabWindows CVI from
National Instrument is needed. An introduction on how it works and on how it performs scans and
measurements is given in the Appendix 2 of this thesis.
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4.2.3 - Fixed setup at CERN Lab 161
Figure 4.5 shows a snapshot of CERN ATLAS Pixel Sensors R&D setup (Bld. 161-1-24) [4-11]. The main
feature with respect to the mobile setup is the climate chamber, operative in a range between -25°C and
100°C.
Figure 4.5 - Fixed setup at CERN Lab 161
The experimental setup used for the characterizations and the source tests shown in Figure 4.6 was housed
inside the climate chamber:
Figure 4.6 - Setup for beta source test
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The fixed setup is composed of:





The climate chamber, in which a custom made plexiglas base has been mounted to fix the boards
during the measurements and to assure the reproducibility of tests. With this structure it has been
possible to put the sources straight onto the sensor, in correspondence with a scintillator placed
under the base, in order to give trigger signals out when recognizing a particle passing through, and
so passing also through the detector (see Figure 4.6). A brass collimator has been used to create a
straight fluence for the β particles coming out from the 90Sr source;
A three logic unit crate for the β source tests, composed of a discriminator, which receives from the
scintillator the trigger signals (in NIM15 logic) over threshold, a level adapter to convert NIM logic
signals into TTL16 (TTL is the standard used by the VME), and a counter, which shows the rate of
particles hitting the scintillator and so useful to set the discriminator threshold (see Figure 4.7);
The TurboDAQ software installed on a PC;
An oscilloscope used to check the signals coming out from the scintillator;
A voltmeter connected with the amplifier used for the amplification of the signals coming out from
the scintillator (as a check for the amplifier set).
Figure 4.7 – On the left a picture of the logic modules for the scintillator; on the right the beta source setup scheme
15
16
Nuclear Instrumentation Module, with true logic signal of -2V
Transistor-Transistor Logic, with true logic signal of +5V
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4.3 – The SCAs and their characterization
For each test a detailed description is given in the next sections. Here follows a list of the main
measurements and tests done and a table with reference to the SCA on which they have been done (Table
4.1).
1.
2.
3.
4.
5.
6.
7.
Leakage current
Threshold and noise
Noise vs bias voltage
ToT self-calibration
109
Cd source test
241
Am source test
90
Sr source test
Table 4.1 - Names of SCAs and tests performed on them
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4.4 – I-V measurements
When a reverse bias is applied to a silicon sensor, a leakage (or dark) current of free recombining intrinsic
charges is created by the contribution of:
1. Volume generation current, generated by the charge flow due to the bias (current increases
proportional to the square root of the bias)
2. Surface generation, additional small contribution
3. Avalanche breakdown, at very high voltages
Figure 4.8 - Typical shape of a silicon sensor’s I-V curve with indication of
the origin of different current contributions [2-1]
After full depletion the I-V curve displays a plateau region where the current increase is very small, before
the electrical breakdown occurs at very high voltages, as shown in Figure 4.8. The sensor has always to be
operated at voltages well below hard breakdown values, in order not to damage or even break it.
Considered as a very powerful tool for sensor testing, I-V curves are used to check for sensor damages after
dicing and chip flipping, and also give the information about the correct bias voltage to be applied for
working in fully depletion condition. This measurement is somehow uncorrelated to the other scans, and its
only requirement is to undergo thermal stability. Measurements of sensor characteristic I-V curves have
been performed from 0 to -70 V (-80 V being the value where breakdown starts) with 1.5 V steps for the 3D
sensors, and from 0 to -600 V at 10 V steps for the planar sensor. After each voltage step a 10 s settling
time is needed before starting the measurement of the current, and the measurement is repeated until
two consecutive readings differ by less than 1%. The source meter (Keithley 2410) is set with a current
limitation of 100 (200) μA. The measurement can be done over the entire sensor also for the 3D pixel
configuration because all the p+ columns on the back side are connected with a metallization to which the
voltage values are applied. A leakage current in the 0.1-0.2 μA range at -35 V depletion voltage and an
avalanche breakdown over -70 V for FBK-3D sensors are acceptable. For planar sensors, these values are in
the 1 μA range at -150 V depletion voltage with an avalanche breakdown over -400 V. Problems may be
expected if the leakage current is one order of magnitude higher. Earlier breakdown or not monotonic
pattern of the leakage current could determine a rejection of the SCA. Concerning the leakage current of a
single pixel, it has been found to be quite large as compared to predictions based on measurements
performed on test diodes, but it still remains at an acceptable level (~100 pA/pixel) [3-30].
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4.4.1 - Measurement results on FBK -3D and planar sensors
Figure 4.9 provides an overview of the I-V curves of all FBK-3D DTC2 sensors available in the laboratory.
Leakage currents and breakdown voltages, which are technology-dependent parameters, show very similar
behaviours, evidence of the good reproducibility of the DDTC process. Possible problems in the sensor
production process lead to a deviation of the curve from the expected shape. The breakdown voltage is
normally over -70 V, a value that is determined by the n+/p-spray junction at the top surface. Two samples
show breakdown before than expected, probably due to some damage during the assembly of the sensors
with the readout chips, and they have not been considered for further tests. The plateau zones go from -10
V to -40 ÷ -50 V, and a good compromise for having all the SCAs tested under the same condition is to bias
the sensors at -35 V, with a leakage current in the 0.1-0.4 µA range.
Figure 4.9 – I-V measurements of FBK-3D DTC2 detectors
Figure 4.10 focuses on a comparison between FBK-3D DTC2 2E, 3E and 4E sensors. The leakage current is
characteristic of how the sensor has been built, and globally does not “really” depend on the distance
between electrodes. To study temperature and humidity effects during measurements, comparison plots of
I-V measurements with a scan performed inside the climate chamber (21 °C and 20% of humidity) and
outside it (24 °C, no humidity check) are shown. It is important to stress that the changes in the leakage
current are mainly due to humidity, while temperature does not have a noticeable impact given the small
difference between the two values.
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Chapter 4 – Characterization and Test of FBK-3D Pixel Silicon Sensors
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Figure 4.10 – I-V measurements with temperature and humidity check for FBK-3D DTC2
sensors
Figure 4.11 shows the different behaviour of the I-V curve of a sensor coming from the second batch of
FBK-3D DDTC (DTC2b), where a sharp increase of the current occurs already at low voltage. The four
sensors so far tested that were produced in this batch have all shown the same behaviour (only 3E sensors
have been initially considered in view of their use in a beam test at CERN). Such an early breakdown is
supposed to be related to the presence of local defects and indeed from maps of the pixel leakage current
at different voltages it has been noticed that a few pixels start exhibiting a high leakage current already at
low voltages [3-30]. Nevertheless, this sensor has been tested during the May Test Beam at CERN
(described at the end of this chapter), and shows correct working responses [4-12] when kept at -8 V bias
voltage.
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Figure 4.11 - I-V for a FBK-3D DTC2b sensor (3E7)
For comparison with the new FBK-3D DDTC sensors, Figure 4.12 shows the I-V curve of an ATLAS n-in-n
planar single-chip module. The major difference is that the same small values of leakage current are
obtained with consistently higher values of bias voltage. Usually a good compromise for a satisfactory low
level of leakage current is to apply a Vbias of -150 V to these sensors.
Figure 4.12 - ATLAS n-in-n planar sensor I-V curve
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4.4.2 - Leakage current from Monleak Scan
The TurboDAQ provides a useful extra feature: the Monleak Scan. It is a measurement of the combined
feedback and leakage current from the feedback circuit, as described by the following relation:
𝐼𝑚𝑜𝑛𝑙𝑒𝑎𝑘 = 𝐼𝑙𝑒𝑎𝑘 + 𝐼𝑓𝑒𝑒𝑑𝑏𝑎𝑐𝑘
where Ifeedback is defined by the IF and TDAC parameters (each of them divided by some correction factors
and then summed together) of the feedback current of the front-end preamplifier and Ileak is the sensor
leakage current per pixel [4-10+. This measurement is made possible by a “monleak” ADC: the pixel to be
measured is selected with the hitbus mask bit of the FE-I3 and its I monleak is digitized to a precision of 0.125
nA in a range up to 128 nA [3-38]. This procedure is designed to read the leakage current pixel by pixel, and
because of the relation between leakage current and radiation damage, it provides a useful monitoring and
diagnostic tool, even if the FE is not able to obtain precise values. With this capability the defective pixels
can be clearly identified as they have a leakage current well outside the dynamic range of the inbuilt
measurement circuit.
Figure 4.13 – On the left, the map of the raw Monleak readings; on the right, the map of the leakage current values
Figure 4.13 shows the results of the monleak scan of an FBK-3D sensor (4EM9) taken as example. The sum
of the currents over all pixels is specified in the text above the plots. The plots on the top show the
behaviour over the entire chip, the plots in the middle show the mean value and the sigma of the
measurements over the single pixel, and the plots on the bottom show the values channel by channel, for
Monleak readings on the left and leakage current on the right, respectively. The TurboDAQ log file of the
Monleak scan is used to determine Ifeedback (if no logfile is found, a default of I feedback=2 nA is assumed). The
absolute accuracy of the measurement is very limited due to FE-I3 chip capabilities in performing them [337]. Various measurements show a mean leakage current of ~1 nA for a good pixel in an FBK-3D detector.
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4.5 - Threshold and noise
The purpose of this test is to measure the threshold and noise of each pixel, where only pixels with a charge
deposit above a set threshold are taken into account for readout by the front-end electronics. Signals are
induced in each pixel by means of on-chip charge injectors (an on-chip chopper generates a VCAL to be
injected into Clow or Chigh capacitors of each pixel, and the input of the preamplifier sees a charge signal
equivalent to VCAL x Clow/high), and the number of collected hits versus the injected charge is recorded. Ideally
a step function with an immediate transition of the detection efficiency from 0 to 100 % at the threshold
could be expected, but in practice, because of the pixel noise, some injected charges below the threshold
are detected while some others are not (as shown in Figure 4.14). The error function, which is a convolution
of the ideal step function with the Gaussian pixel noise distribution, is the best candidate to describe the
discriminator output:
t
2
1
f error ( x) 
e x dx

2 0
This function, the so-called S-curve, is used to fit the threshold scan results of each pixel.
Figure 4.14 - Threshold curve [3-4]
The exact procedure of the scan is:
1. 100 digital injections per pixel are made
2. A charge between 0 and 9000 e- in 45 e- steps is injected
3. The collected hit number for each pixel and each injected charge is recorded
The probability of detecting a charge is given by the following formula:
𝑃𝑕𝑖𝑡 𝑄 =
1
𝑄𝑡𝑕𝑟𝑒𝑠 𝑕 − 𝑄
1
𝐸𝑟𝑓𝑐
=
2
𝜋
2𝜍𝑛𝑜𝑖𝑠𝑒
73
∞
exp
0
𝑄 − 𝑄𝑡𝑕𝑟𝑒𝑠 𝑕
2𝜍𝑛𝑜𝑖𝑠𝑒
𝑑𝑄
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The 50% hit efficiency on the S-curve defines the threshold value of a pixel, as shown in Figure 4.15. The
noise of a pixel is inversely proportional to the steepness of the transition from no detected hits to full
efficiency, and is calculated between the 70% and the 30% points:
𝜍=
−1
𝑓𝑒𝑟𝑟𝑜𝑟
𝑄70% − 𝑄30%
−1
(70%) − 𝑓𝑒𝑟𝑟𝑜𝑟
(30%)
The threshold calibration is obtained by first setting the correct value of GDAC (global setting - see section
3.4.6), then by applying the TDAC tuning (pixel setting) file, obtained from a TDAC tuning scan. Scans are
repeated to reduce the threshold dispersion by adjusting the TDAC parameter individually for each channel
[3-20, 4-1].
For the FE-I3 chip this test can be performed in the so-called “auto-tune” mode, where a fixed charge,
corresponding to the desired threshold, is continuously injected into each pixel and an internal counter
checks for which TDAC value its count rate is 50%. This tuning procedure is extremely fast, even if it may
show some systematic patterns. The threshold dependence of each pixel on the TDAC is fitted to these data
using the parameterization:
𝑇𝑕𝑟𝑒𝑠𝑕𝑜𝑙𝑑 𝑇𝐷𝐴𝐶 = 𝐴 + 𝐵
log 𝑇𝐷𝐴𝐶
128 − 𝑇𝐷𝐴𝐶
This relationship is used to determine, for each pixel, the TDAC value closest to the target threshold, which
is set to 3200 e- [4-1,4-13].
4.5.1 – Measurements results on FBK -3D and planar sensors
Setting the correct threshold value is the first step to calibrate the front-end with a suitable configuration
to recognize particles, and it has been performed on all those sensors not affected by early breakdown
problems. The results of the threshold scan and the bias voltage for the sensors tested at CERN Lab 161 are
summarized in Table 4.2:
Table 4.2 - Threshold and noise results
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As an example, Figure 4.15 shows a threshold measurement and a noise distribution for a FBK-3D DTC2
sensor with 2E configuration (2EM2), with the entire chip map and the mean value with correspondent
sigma over all channels for both measurements, and the threshold values channel per channel.
Figure 4.15 – On the left, threshold for FBK-3D DTC2 (2EM2); on the right, noise for FBK-3D DTC2 (2EM2)
Concerning the noise values obtained, one can see from Table 4.2 that the noise increases with the number
of electrodes per pixel, as it will be better demonstrated by the next measurement (and that the noise of
the planar sensor is lower than those for 3D sensors) .
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4.5.2 - Noise versus bias voltage of the sensor
To measure how the noise depends on the bias voltage given to the sensor, a threshold scan over various
bias voltages, from 0 V to -80 V with 5 V steps, has been performed and the threshold and noise have been
determined, using the same configuration file for each bias voltage value (same TDAC/FDAC settings).
Figure 4.16 shows the noise vs voltage of FBK-3D DTC2 detectors with 2E, 3E and 4E configuration.
Figure 4.16 - Noise vs Bias voltage for FBK-DTC2
The measurements confirm that having more electrodes per pixel increases the noise (under the same
operating conditions). The reason is that this situation is equivalent to having more capacitors connected in
parallel, which increases the total capacitance and consequently the total noise because there is more
charge involved (C2E < C3E < C4E). The plot also shows that the noise is higher for low voltage values than for
high values. Since the noise is determined from threshold scans with the same TDAC settings, it is useful to
check the dependence of the threshold on the bias voltage. The threshold should be almost independent of
the bias voltage because the threshold scan is fitting an S-curve which is a convolution of a Gaussian and a
step function, as already explained. The value of the step function is the threshold and should thus not be
affected by changing the width of the Gaussian which is overlaid. This is verified with the measurements of
the threshold as a function of the bias voltage, as shown in Figure 4.17.
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Figure 4.17 - Threshold vs bias voltage
Also the width of the threshold and of the noise are plotted as a function of the bias voltage (Figure 4.18),
showing no evidence of any dependence:
Figure 4.18 - On the left, noise width as a function of the bias voltage; on the right, threshold width as a function of the bias
voltage
Using the information given by the I-V curves and the noise versus bias voltage plots, and knowing the
theoretical full depletion value for this kind of sensors (-10 V), a depletion voltage of -35 V has been chosen
for these sensors during all the test, in order to have full depletion and to minimize the noise. The same
behaviour of the noise with respect to the bias voltage has been measured for the planar detector, with
one order of magnitude higher bias and lower noise values than FBK-3D SCAs; results of this measurement
are reported in Figure 4.19.
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Figure 4.19 - Noise vs bias voltage for the planar sensor
4.6 – Time over Thres hold (ToT) measurements and internal calibration of the
detector
In silicon, the mean energy loss of a MIP is 1.66 MeV g-1cm2, while the density is 2.33 g cm-3, so the mean
loss of energy is 390 eV/μm. Since to generate a hole-electron pair an energy of 3.6 eV is needed, this
means that an average MIP creates ~110 pairs per μm in the silicon. With a thickness sensor of 250 μm,
this results in a most probable value of the Landau curve for a MIP of about 20000 hole-electrons pairs [335].
The ToT (Time over Threshold) is used to measure the deposited charge of a hit: it is the length of the
discriminator signal in units of the 40 MHz LHC bunch crossing clock (25 ns), and depends on the deposited
charge itself, on the discriminator threshold and on the preamplifier feedback current.
Figure 4.20 - ToT dependences [3-4]
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The on-chip injection circuit of the FE-I3 is used to calibrate the ToT response of a signal back into charge
(see Figure 4.20). The standard tuning aims to a ToT of 60 units for a charge of 20000 e-, so given a standard
threshold of 3200 e- this corresponds to a charge of about 250-350 e- per ToT unit. The ToT calibration
consists of injections of various charges above threshold and then subsequent measurement of the average
ToT. The feedback current, and thereby the ToT, is determined by a global DAC current per FE chip (IF) and
a DAC for each pixel (FDAC). The tuning fixes the feedback current to the desired response of 60 ToT for a
MIP of 20000 e-. The purpose of a ToT scan is to tune the ToT response to a MIP for each pixel in order to
have a uniform signal of the collected charge in a time acceptable for the operation of the detectors (such
as ATLAS or CMS), and to calibrate the relationship between the measured ToT and the collected charge.
The pixel detector gives an indirect pulse height information using the Time over Threshold (ToT)
technique: the pulse shape is approximately triangular and the time that the preamplifier output stays over
the threshold is approximately proportional to the pulse height (see section 3.4.6). Then the descending
slope to baseline of the triangular pulse is determined by the feedback current of the preamplifier, which
can be tuned at the chip level by changing the IF DAC register and at the pixel level by using the 3-bit FDAC
pixel register. The ToT tuning consists of two parts. At first, the ToT response of all pixels to the charge
deposited by a MIP is made uniform by proper setting of the IF and FDACs: this is done by injecting a fixed
charge of 20000 e-, corresponding to the most probable energy loss in a 250 μm thick silicon sensor, and
choosing the above mentioned DACs in order to have an average ToT response of 60 clock cycles. The 60
clock cycles allow to keep full efficiency up to deposited charges of 4 MIPs. The subsequent step is to inject
different charges, compute the average ToT observed for each pixel and each charge, and fit a calibration
function to these data:
𝑃2
𝑇𝑜𝑇 = 𝑃1 +
𝑃3 + 𝑄𝑖𝑛𝑗
This is performed using both the Clow inject capacitance, which allows a fine granularity measurement of the
ToT-charge relationships in the region of charge up to 1 MIP, and the Chigh inject capacitance to cover the
region of higher charges. These calibrations will be used to translate ToT to charge when collecting data
with real particles. Since changing the feedback current also slightly affects the threshold, the threshold
tuning needs to be re-done after the IF and FDAC tuning.
The procedure of the tuning begins with setting to 20000 e- the ToT reference charge in the TurboDAQ, and
then going through an FDAC scan. Then the average ToT value of each chip can be moved toward the
desired average ToT response of 60 by changing the IF DACs. This scan is repeated until all chips have a
matching average ToT response. After this tuning is finished a full FDAC tuning scan has to be performed
(FDAC Tune Internal-Cal): the results of the FDAC determination are put in files ##_fdacs_#.out, which are
moved from the data folder in the module directory tree to the FDACs. Then these files are loaded in the
module configuration file and saved. Finally the ToT calibration has to be performed, which consists of two
scans (TOT Calibration Internal-Cal. CLow Concurrent, TOT Calibration Internal-Cal. CHigh Concurrent). The Clow
capacitance is best to fit low values of charge, while Chigh capacitance is used for high values, as shown in
Figure 4.21.
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ToT
Figure 4.21 - ToT vs charge using the two injection capacitances
4.6.1 – Measurements results on FBK-3D and planar sensors
The aim is to obtain calibrated SCAs ready to be used to recognize MIPs passing through the sensor. Figure
4.22 shows the ToT value obtained for a FBK-3D DTC2 (4EM9), while Table 4.3 is a summary of the results
of all the calibrated SCAs. For the complete set of plots, see Appendix 3 of the thesis.
Figure 4.22 - ToT value obtained from calibrated FBK-3D DTC2 4EM9
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Table 4.3 - ToT values obtained after SCAs calibration
4.7 – Gamma source measurements with
2 4 1 Am
and
1 0 9 Cd
241
Am and 109Cd gamma sources have been chosen to calibrate the detectors. The source tests have also
been used to identify dead or noisy pixels. The main point of this test is to obtain the characteristic
photoelectric peaks of 241Am and 109Cd, thereby having a proof of the correct working condition and
calibration of the detectors. 241Am (109Cd) gamma source emits 60 keV (22 keV) photons, which can
convert anywhere in the bulk to a 60 keV (22 keV) primary electron. If ionization takes place in the
substrate region where columns overlap, a signal of 16.5 ke - (6.1 ke-) is expected. On the other hand, if a
photon converts in a high doping region or close to the surfaces, a fraction of the charge could be lost.
Thus, in the charge distribution, a high end peak at 16.5 ke- (6.1 ke-) and a tail towards smaller values are
expected.
4.7.1 –Measurements results on FBK-3D and planar sensors
Figure 4.23 shows the spectra for 241Am and 109Cd, as reconstructed from the ToT values with the 60 ToT
calibration discussed in the previous section, and with a sensor bias voltage of -35 V. In both cases, the
position of the main peak agrees with expectation within the uncertainty due to the calibration process,
which has been estimated to be of the order of 10-15% [4-15]. To perform the measurement, the standard
TurboDAQ Source Test Self Trigger has been used, which collects data with the self capability of the FE-I3 to
send out signal only when a gamma particle has hit a pixel (one hit-one trigger mode) and with the
possibility to create mask files to cover noisy pixels. Figure 4.23 refers to a 2E detector; on the left the
241
Am spectrum obtained is shown, while on the right the 109Cd spectrum is shown.
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Figure 4.23 - On the left the
241
Am spectrum obtained with FBK-3D DTC2 2EM2; on the right the
obtained with the same detector
109
Cd spectrum
Similar plots have been obtained for SCAs with 4E configuration (all plots in Appendix 3). This is not
surprising, since no appreciable difference in the charge collection process is expected between the
different layouts. A more interesting point is to see that the measurement remains almost the same when
varying the bias voltage of the sensor: Figure 4.24 shows this result for the same 2E detector biased at -15 V
(on the left) and at -55 V (on the right).
Figure 4.24 - On the left the
241
Am spectrum obtained with FBK-3D DTC2 2EM2 biased at -15 V; on the right the
obtained with FBK-3D DTC2 2EM2 biased at -55 V
241
Am spectrum
At -15 V a peak around 3200 e- appears: it is the noise effect over the threshold, that causes an higher peak
because the sensor is biased at a voltage near the nominal depletion voltage value (-10 V). Table 4.4 is a
summary of the values obtained from the gamma photoelectric peak of 241Am with different set of bias
voltages (-15 V, -35 V, -55 V) for the FBK-3D DTC2 2EM2 module.
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Table 4.4 -
241
Vbias (V)
Charge (e-)
-15
-35
-55
14440.0 ± 822.7
14490.0 ± 784.3
14590.0 ± 707.2
Am photoelectric peak values in charge obtained at three different bias voltage values with FBK-3D DTC2 2EM2
Results obtained with 3D sensors agree with those from measurements on the planar reference detector
[see also 4-14,4-16] using the same setup and biasing it at -150 V, as shown in Figure 4.25 for 241Am and in
Figure 4.26 for 109Cd, for which also the behaviour of a single pixel is shown. It is important to notice that
not only the mean values of the peak but also the shapes of the spectra are very similar between the two
sensors, so plots are shown without the fit line. Table 4.5 summarizes the peak charge values obtained
from this comparison.
FBK-3D DTC2 2EM2
Planar n-in-n
Figure 4.25 –
241
Am spectrum obtained with an FBK-3D DTC2 2E (top) compared with the same spectrum from the reference planar
detector (bottom)
FBK-3D DTC2 2EM2
FBK-3D DTC2 2EM2
Planar n-in-n
Planar n-in-n
Figure 4.26 –
109
Cd spectrum obtained with an FBK-3D DTC2 2E (top) compared with the same spectrum from the reference planar
detector (bottom), over the entire sensor (left) and on a single pixel (right)
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Source
241
Am
Cd
109
Table 4.5 -
241
Am and
109
3D-DTC2 2EM2 (e-)
Planar (e-)
14490.0 ± 784.3
5858.0 ± 484.7
14400.0 ± 664.9
5753.0 ± 551.8
Cd photoelectric peak values in charge obtained with the reference planar sensor
This is the first demonstration of the correct 3D detector calibration when used for the measurement of
real particles.
4.8 – Beta source measurements with
9 0 Sr
A β source test consists of MIPs passing through the sensor and creating free charges by ionization.
Ionization is subject to statistical fluctuations and the value of energy loss returned by the Bethe-Bloch
formula (see Chapter 2) is only the average value of a Landau distribution. If a particle is not stopped in the
sensor, its response varies around the peak of the distribution with a significant probability of high signals,
and due to this tail of high signals the average value is higher than the most probable value (MPV) of the
distribution. The fluctuation around the maximum of this distribution becomes higher for thin sensors. The
main reason for the Landau fluctuation is the rare but measurable occurrence of the so-called δ-electrons
(or knock-on electrons), which obtain enough energy in the interaction to become ionizing particles
themselves, as explained in Chapter 2. They have typically a direction perpendicular to the direction of the
incoming particle which leads to irregular charge clouds and degrades the spatial resolution.
4.8.1 - Measurements results on FBK -3D and planar sensors
The single chip module on the PCB frame is mounted with a hole under the sensor, especially designed for
this kind of tests, which allows the β particles to pass through. The TurboDAQ, with the scintillator set up
described in section 4.2.3, uses the Source Test External Trigger capability of the FE-I3 to collect data from
the detector only when the incoming particle is also seen by the scintillator, giving the acquisition trigger.
Results have been found using a brass collimator which kept the distance between source and detector to
20 mm (the shape of the hole of the collimator can be seen in Figure 4.27). Before going through the
description of the β source test, the trigger delay of the setup has to be considered, which is given by the
latency of the FE to read out the event (stored locally and discarded after this time) and the external delay,
which is set to catch 16 consecutive “bunch crossings” around the one that contains the actual trigger
(since particles hit the scintillator and the sensor almost at the same time and we are only interested in the
"bunch crossings" associates with the trigger).
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Figure 4.27 - Map of hits from ToT measurement without (left) and with (right) collimation
Figure 4.28 shows the pulse height spectrum in response to a 90Sr β-source in a FBK-3D DTC2 3EM5 biased
at - 35 V. The distributions have been fitted with the expected Landau curve. The plots have been obtained
by applying a clusterization to the data: it contains an algorithm which recognizes and collects the charge
due to a single events hitting more than one pixel, making a better interpretation of the source test and so
producing Landau curves representing also the high energetic δ rays. This kind of clusterization is called
“Digital Clusterization”: it recognizes ToTs belonging to the same events with a specific algorithm, and
attributes the correct ToT to the event either by taking the highest ToT value between near hit pixels
(cluster size1), or the highest plus the second (cluster size2). For the FBK-3D DTC2 3EM5 the most probable
charge value is 13.580 ke- with a sigma of 1.150 ke- (cluster size1) and 14.880 ke- with a sigma of 1.345 ke(cluster size2), where the charge is obtained from the ToT using the calibration curve described in section
4.6. The front-end electronics have been tuned to 60 ToT at 20.000 ke-, suitable for ATLAS sensors of 250
µm, but in this case the sensor thickness is 200 µm, as measured at FBK with C-V measurements on planar
diodes coming from the same wafer of DTC2 sensors [4-12]. To evaluate the expected MPV one should then
consider the measured values for the planar sensor; the two curves corresponding to cluster size1 and 2
are shown in Figure 4.30. Rescaling the measured MPV for the 250 µm planar to 200 µm, the expected MPV
is 14.128 ke-, with the observed difference between expected and measured value attributed to the
uncertainty due to the calibration process (about 10-15%, propagated from the known value of the FE
capacitor Clow and Chigh, as already mentioned for γ source tests). For all sensors available the pulse height
spectrum has been measured in response to a 90Sr source. All the plots are shown in Appendix 3. The
various behaviours as function of the electrode configuration and the bias voltages are under investigation.
Preliminary results are summarized in Table 4.6.
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-
Figure 4.28 –On the left, measurement results for a FBK-3D DTC2 3E with cluster size1 (charge values in excess of 12 ke have
been fitted with a Landau function); on the right, measurement results for the same FBK-3D DTC2 3E with cluster size2 and
same fit
2EM2
MPV with Cluster Size1 (ke )
12.94 ± 1.28
13.59 ± 1.35
13.52 ± 1.31
3EM7
MPV with Cluster Size1 (ke )
-
Vbias (V)
-15
-35
-55
Vbias (V)
-15
-35
-55
13.12 ± 1.28
13.35 ± 1.28
13.40 ± 1.28
MPV with Cluster Size2 (ke-)
14.93 ± 1.50
14.89 ± 1.47
14.95 ± 1.46
4EM9
MPV with Cluster Size1 (ke )
12.73 ± 1.26
12.92 ± 1.33
12.97 ± 1.30
-
Vbias (V)
-15
-35
-55
MPV with Cluster Size2 (ke-)
14.93 ± 1.57
15.02 ± 1.52
14.90 ± 1.53
MPV with Cluster Size2 (ke-)
14.52 ± 1.55
14.49 ± 1.53
14.47 ± 1.52
90
Table 4.6 - Sr MPV preliminary results for FBK-3D DTC2 2EM2, 3EM7, 4EM9 at -15, -35, -55 V of bias voltage and with cluster
size1 and 2
The reference planar detector has been built with a golden layer on the bottom of its board, from which
beta particles can pass through re-creating the layer shape in the measurement results, as shown in Figure
4.29:
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Figure 4.29 – On the left, map of hits from ToT measurement with collimation; on the right, shape of the golden layer behind
the planar detector
-
Figure 4.30 - On the left, measurement results for a planar sensor with cluster size 1 (charge values in excess of 15 ke have been
fitted with a Landau function); on the right, measurement results for a planar sensor with cluster size 2 (charge values in excess
of 15 ke have been fitted with a Landau function)
4.9 - Tes t Beam
3D detectors are still under investigation. They are usually tested in test beams together with some well
known planar devices, before and after irradiation. The first test beam analysis on full-3D detectors with
active edges fabricated at Stanford has been published in 2008 [3-17]: 3 different pixel configuration,
connected to the ATLAS readout FE-I3 chip, have been investigated in a 100 GeV pion beam at the CERN
SPS17. A similar test has been done at the CERN SPS on a FBK-3D DTC2 (3EM5) and a FBK-3D DTC2b (3E7),
together with a Full-3D Stanford sensor and a planar sensor, during the May 2009 Test Beam, to which I
contributed for the data taking. Its main goal has been to test the 3D sensors within a large magnetic field
17
Super Proton Synchrotron
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at different angles (0° and 15°), analyzing the signal response, hit efficiency, charge sharing and the in-time
efficiency of the detectors.
4.9.1 - The experimental setup
The test beam has been carried out at the CERN site of Prevessin (North Area), in H8 beam line, using the
180 GeV secondary π+ coming from CERN SPS. The experimental setup was mounted inside the bore (1.6 m
diameter) of the “Morpurgo”-magnet, a superconducting dipole magnet that was recommissioned for the
purpose of these measurements. The dipole provided a vertical magnetic field of about 1.6 T at the nominal
current of 5 kA. Two overlapping scintillators in front of the tracking system were used to provide a
coincidence trigger; in the rear a large 150 x 150 mm2 paddle scintillator with a 15 mm hole was used in
anti-coincidence mode, allowing efficient suppression of showers and multiple-scatter events. The veto was
implemented purely for data-taking efficiency reasons, and only successfully reconstructed tracks from
clean events have been used for the final analysis [4-16]. Figure 4.31 shows the experimental setup in the
beamline, while Figure 4.32 and 4.33 show the position of the SCAs in the cooling box (previewed but not
used) with a respective schematic.
Figure 4.31 - Experimental setup for the test beam
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Figure 4.32 - Cooling box for the SCAs
I have calibrated all the SCAs used in the test beam in Lab 161 before sending them to the test beam area.
In the test beam setup, each SCA was connected to its own read-out chain (Sensor-TPCC-TPLL-TurboDAQ).
Starting from the last one with respect to the direction of the incoming beam (see Figure 4.33), they were
four:
1.
2.
3.
4.
an FBK-3D DTC2 (3EM5), with bias voltage of -35 V
an FBK-3D DTC2b (3E7), with bias voltage of -8 V
a Full-3D Stanford (3E), with bias voltage of -35 V
an ATLAS planar n-in-n used as reference, ), with bias voltage of -150 V.
Figure 4.33 - Position of the SCAs inside the cooling box
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Track reconstruction was provided by three planes (BATs in Figure 4.33), the Bonn ATLAS Telescope [4-17].
The telescope consists of double-sided silicon micro-strip detectors with 50 μm pitch on both sides rotated
by 90° with respect to each other, each plane therefore providing X and Y measurements. The telescope
planes were mounted on a precision table together with the SCAs as illustrated in Figure 4.33, with a single
plane in front separated by about 900 mm from a pair of planes in the back, with BAT 2 and 3 mounted 60
mm apart. A Hall probe was positioned on the table in order to measure the intensity of the magnetic field.
The sensors were installed in such a way that the pixel long direction (400 µm) was in the vertical position.
Data were taken with beam at normal incidence and with a 15° degree angle. This angle simulates the tilt
angle in the ATLAS barrel detector. Tilt angle, beam and B field directions are sketched in Figure 4.34.
Figure 4.34 - Tilt angle, beam and B field directions
4.9.2 - Selected events
After masking noisy strips, events with exactly one hit in each telescope plane were selected for the
reconstruction. The resulting beam shape is a convolution of the trigger and tracking efficiencies [4-16].
Tracks were fitted to a constant curvature helix, essentially treating all particles as having identical
momenta, and the magnetic field as being uniform. Any model error arising from the actual field nonuniformity was absorbed in the transverse alignment, which was done independently of runs with and
without magnetic field. Excess extrapolation errors arising from a finite spectral width are expected to give
a limited contribution to the tracking error. The spatial resolution of the telescope was estimated by
comparing hits in one of the doublet planes to tracks extrapolated from the two remaining planes. The
distribution of unbiased residuals is compatible with the results of a toy Monte-Carlo model which assumes
a spatial resolution of 5 μm. The same model predicts the error of the extrapolated track position in the
Device-under-Test planes to be of order 3 μm, which has been considered a lower bound on the total track
resolution [4-17]. For preliminary results of the test beam the reader can refer to [4-16],[4-12],[4-18],[419].
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IRRADIATION
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T
his chapter is meant to describe the physics that stands behind the radiation damage of silicon, and
analyze the behaviour of FBK-3D detectors after irradiation. This has been done at the PS18 facility of
CERN in the period September-November 2009. One of the aims of this study is to demonstrate that
3D-DDTC pixels would be a feasible alternative to the planar pixel sensors now installed in the ATLAS
experiment, proving their radiation hardness.
5.1 – Radiation-induced effects on silicon
Radiation-induced damage is usually divided into bulk and surface damage. The former is caused by the
displacement of crystal atoms while the latter include all effects in the surrounding dielectric layers. The
most important surface effect is the charge density increase in the oxide passivation layer, which saturates
after some kGy to values of about 1012 cm−2 [2-1]. At higher hadron fluence, bulk damage becomes
important. The main effects are:
•
•
•
Increase of the leakage current
Change of the space charge in the depleted region and subsequent increase of the full-depletion
voltage
Charge trapping
5.1.1 – Bulk damage
Properties of silicon change with radiation because of its crystal nature. High energy particles do not
interact exclusively with the electrons of the silicon sensor producing ionization, but also interact with the
nuclei, often displacing them out of the lattice position: this produces crystal imperfections which may be
electrically active and hence change the electric properties of the material, causing the so-called bulk
damage [2-1]. In contrast to ionization such interactions are not reversible in most cases. To remove a
silicon atom from its lattice position a minimum recoil energy of about 25 eV is required [5-1]. Electrons
need an energy of at least 260 keV in order to provide such a recoil energy in a collision, while protons and
neutrons, because of their higher mass, require 190 eV only. If the recoiling silicon atom gets enough
energy through the collision, it can cause further defects. In case this energy exceeds about 2 keV a cluster
of defects is created and most of the energy is released in a very localized area. According to simulations
these clusters are believed to have an inner diameter of about 10 nm surrounded by an about 200-nm wide
volume with a lower defect density [5-2].
In order to compare the damage caused by different types of particles with different energies, radiation
damage is scaled using the non-ionizing energy loss (NIEL) conversion [5-3],[5-4],[5-5]. This is based on the
hypothesis that the damage only depends on the energy deposited in the crystal which is not related to the
fully reversible process of ionization but only to non-ionizing interactions. Fluences are normalized to that
of neutrons of 1 MeV, used as reference, through the following relation:
𝜙𝑒𝑞 = 𝜅𝜙𝑝𝑕𝑦𝑠
The energy-dependent hardness factor κ of a certain type of particle, which converts the “physical” fluence
Φphys into the neutron equivalent fluence Φeq able to produce the same NIEL, can be calculated according to
[5-3]. The experimental determination of the hardness factors is done via the normalization of the leakage
current [5-6]. For the most frequently used irradiation facilities measured values are available, and in
18
Proton Synchrotron
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Chapter 5 - Irradiation
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particular the hardness factor κ of the 24 GeV protons provided by the CERN-PS is 0.62 [5-7]. In general
there exists a factor of ~2 between a flux of neutrons and protons.
Primary defects caused by irradiation, mainly silicon vacancies and interstitials, are not stable, i.e. they can
move through the crystal. This movement can lead to annealing if defects meet during their migration. But
secondary point defects, together with other defects already present in the crystal, might be stable and
display different electrical properties. Point defects can in general determine new energy levels in the gap
band whose positions can be measured by different spectroscopic methods. Depending on the energy, they
can have an impact on the space charge in the depletion zone [2-1].
5.1.2 – Leakage current and annealing
The energy levels in the band gap caused by crystal defects act as generation–recombination centers. They
lead to a decrease of the generation lifetime, τg, proportional to the fluence Φ [2-1]:
1
1
=
+ 𝑘𝜏 𝜙
𝜏𝑔
𝜏𝑔,𝜙=0
with kτ being the lifetime-related damage rate, and to an increase of the volume generation current, Ivol:
𝐼𝑣𝑜𝑙 ,𝜙=0
𝐼𝑣𝑜𝑙
=
+ 𝛼𝜙
𝑣𝑜𝑙
𝑣𝑜𝑙
with vol being the depleted volume and α the current-related damage rate. Because of the relation
between generation lifetime and volume generation current expressed in :
𝐼𝑣𝑜𝑙 ≈ −𝑒
𝑛𝑖
𝑛𝑖
𝑊 ≈ −𝑒
𝜏𝑔
𝜏𝑔
2𝜀0 𝜀𝑆𝑖
𝑉
𝑒𝑁𝐷 𝑅
the two damage constants are also related:
𝛼 = 𝑒𝑛𝑖 𝑘𝜏
The lifetime-related damage rate kτ is more fundamental than the current-related damage rate α, as it does
not depend on the intrinsic charge carrier concentration, and therefore not on the temperature at which
the measurement is performed. However, α is usually quoted as the parameter directly determined from
the current–voltage measurements. The damage constant α is independent of the initial resistivity of the
silicon, the concentration of other dopants like oxygen or carbon, and the production process of the sensor
[5-8]. Figure 5.1 shows the dependence of the leakage current, normalized to the depleted volume V, for
several types of silicon semiconductor detectors [5-4]. From these data but also from many other
measurements made on p-type, n-type, FZ or CZ irradiated materials the current damage rate tends to α =
(3.99 ± 0.03) × 10−17A/cm. Due to the strong dependence of the leakage current on the temperature, the
data measurements have to be normalized to the same reference temperature (i.e. TR = 20 °C) for doing a
meaningful comparison between different data set.
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Chapter 5 - Irradiation
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Figure 5.1 - Induced leakage current increase for several detector materials as function of the fluence. Current
has been measured after an annealing step at 60 °C for 80 min [5-4].
After irradiation the leakage current anneals with time as shown in Figure 5.2, through the α dependence
on time. This strongly temperature-dependent annealing behaviour was fitted in the past to a sum of
exponential functions with different “decay” times and could be interpreted as several defects which
anneal with different time constants [5-9]. Such a parameterization describes the measured data for
annealing times at room temperature of less than one year. For longer annealing times or higher annealing
temperatures no saturation of the annealing has been observed and therefore the time evolution of the
current-related damage rate has been described using an additional logarithmic term [5-4]:
𝛼 𝑡 = 𝛼𝑖 𝑒
𝑡
−
𝜏𝑖
𝑡
𝑡0
+ 𝛼0 − 𝛽 ln
with t0 arbitrary set to 1 min. The dependence on the annealing temperature Ta is hidden in
𝐸
1
− 𝑖
= 𝑘0,𝑖 𝑒 𝑘𝐵 𝑇𝑎
𝜏𝑖
and in α0. The fitted parameters were determined to be:
𝐴
𝑐𝑚
𝛼𝑖 = 1.26 ± 0.06 × 10−17
13 −1
𝑘0,𝑖 = 1.2+5.3
−1.0 × 10 𝑠
𝐸𝑖 = 1.11 ± 0.05 𝑒𝑉
𝛽 = (3.07 ± 0.18) × 10−18
𝛼0 = − 8.9 ± 1.3 × 10−17
𝐴
𝑐𝑚
𝐴
𝐴𝐾 1
+ 4.6 ± 0.4 × 10−14
×
𝑐𝑚
𝑐𝑚 𝑇𝑎
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Chapter 5 - Irradiation
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Figure 5.2 - Current-related damage rate α as function of the cumulated annealing time [5-4]
5.1.3 – Effective doping and fluence dependence
If several dopants and electrically active defects are present in a silicon sensor, the concentrations of
donors, ND, or acceptors, NA, have to be replaced by a quantity called net doping or effective doping, Neff ,
which is the difference between all donor-like states and all acceptor-like states, and can be determined
from the full-depletion voltage:
𝑁𝑒𝑓𝑓 =
2𝜀0 𝜀𝑆𝑖 𝑉𝑑𝑒𝑝𝑙
𝑒𝑑 2
with d the depleted layer width. Since the effective doping concentration is, according to the definition,
positive for n-material and negative for p-material, all formulas contain only its absolute value |Neff |.
The effective doping concentration changes with irradiation. Figure 5.3 shows the dependence of the
effective doping and the full-depletion voltage on the equivalent fluence.
Figure 5.3 - Change of the full-depletion voltage of a 300-µm-thick silicon n-type
sensor and its absolute effective doping versus the normalized fluence,
immediately after irradiation [5-9]
In n-type silicon, Neff decreases up to a fluence of (2÷5) × 1012 cm−2 at which the space charge almost
vanishes. With further irradiation the absolute effective doping concentration increases again, dominated
by acceptor-like defects with a negative space charge, and the material becomes a p-doped one. As a
96
Chapter 5 - Irradiation
s
consequence of this type inversion, or more correctly space charge sign inversion, the PN-junction moves
from the p+-side of the sensor to the n +-side, causing problems to the charge collection at the readout
electrodes. This behaviour has been proven using short-range α-particles [5-9]. Contrary to n-type, p-type
substrates do not undergo type-inversion for fluences up to the ones foreseen for sLHC [5-10] Due to the
mobility of the defects the net doping concentration changes after the end of the irradiation. The time
evolution of the effective space charge at temperature of 60 ˚C is shown in Figure 5.4. As the defects and
their behaviour are not yet understood in detail, a phenomenological parameterization is performed. The
most accepted description is the so-called Hamburg model [5-4]:
𝑁𝑒𝑓𝑓 = 𝑁𝑒𝑓𝑓 ,𝜙=0 − [𝑁𝑐 𝜙 + 𝑁𝑎 𝜙, 𝑇𝑎 , 𝑡 + 𝑁𝑌 𝜙, 𝑇𝑎 , 𝑡 ]
with 𝑁𝑐 𝜙 + 𝑁𝑎 𝜙, 𝑇𝑎 , 𝑡 + 𝑁𝑌 𝜙, 𝑇𝑎 , 𝑡
= Δ𝑁𝑒𝑓𝑓 𝜙, 𝑇𝑎 , 𝑡 .
Figure 5.4 - Typical annealing behaviour of the irradiation-induced changes
of the effective doping concentration ∆Neff at a temperature of 60 °C after
13
-2
irradiation with a fluence of 1.4 x 10 cm [5-11]
In the equation NC(Φ) describes the fluence dependence of the effective doping and contains only the
fluence Φ as parameter. The other two terms describe the change of the effective doping after the
irradiation and are therefore also dependent on the temperature Ta. In particular, the first term NC(Φ)
describes the stable damage, combining the deactivation of the initial donor states with the creation of
acceptor-like defects:
𝑁𝐶 𝜙 = 𝑁𝐶,0 1 − 𝑒 −𝑐𝜙 + 𝑔𝑐 𝜙
with c = (1-3) x 10-13 cm2, called removal constant [5-4]. The second term of the Hamburg Model, Na,
specifies the short-term or beneficial annealing, while the third, NY, is the so-called reverse annealing term,
which describes the increase of the full depletion voltage after some weeks at room temperature [see 5-4
for various parameterizations]. It is also important to mention that irradiation-induced space charge sign
inversion influences the electric field inside the sensor: it is the so-called double junction model, which
describes the presence of a new electric field in the undepleted region of the sensor [5-12,5-13].
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Chapter 5 - Irradiation
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5.1.4 – Charge trapping
Radiation-induced defects act as generation–recombination centers, which increase leakage current and
charged defects (with dramatic influence on the full-depletion voltage), but also create trapping centers.
Traps in the depletion region are mostly unoccupied due to the lack of free charge carriers, and can hold or
trap part of the signal charge for a time longer than the charge collection time and consequently reduce the
signal height. A parameter to describe trapping is the trapping time τt, which is inversely proportional to the
concentration of traps and therefore inversely proportional to the fluence Φ *5-9]:
1
1
=
+ 𝛾𝜙
𝜏𝑡 (𝜙)
𝜏𝑡,𝜙=0
The coefficient γ was measured to be 0.41 × 10 −6 cm2/s for electrons and 0.60 × 10−6 cm2/s for holes after
neutron irradiation. After irradiation with charged hadrons (protons and pions) this coefficient was found
to be significantly larger: 0.56 × 10−6 cm2/s for electrons and 0.77 × 10 −6 cm2/s for holes [5-14]. For most of
the tracking devices in use in particle physics this effect is less important than the other radiation-induced
effects previously discussed; after a fluence of 1014 neq/cm2 about 90% of the signal charge can be still
collected in a 300-μm-thick detector. However, this number decreases to about 50% for 1015 neq/cm2 and
trapping will eventually limit the use of silicon detectors for fluences beyond this number, as the sLHC ones
will be.
5.1.5 – Surface effects
In silicon also the surface region is sensitive to radiation. Surface damage summarizes all defects in the
overlaid dielectrics, like the silicon oxide passivation layer, and the interface between the silicon and the
dielectrics. Since the crystal structure of silicon oxide is highly irregular, displacements of single atoms due
to irradiation do not lead to macroscopic changes. Ionization in the oxide, however, is not fully reversible
and may cause steady changes of the interface properties. Electrons have high mobility in the oxide and if
created by radiation will be collected by any positively biased electrode close by. Holes have instead a very
low mobility in the oxide, because of the large number of shallow hole traps, and they move very slowly in
the direction of the electric field, hopping from one shallow trap into the next. If the holes arrive in the
transition region between silicon and oxide, where many deep hole traps exist, they may be kept there
permanently [5-15].
5.1.6 – Consequences of irradiation damage on sensor operation
The main consequence of the bulk damage on the operation of irradiated sensors consists basically in the
increase of leakage current and operation voltage; this leads to an increased power dissipation, which heats
the sensor, and higher temperature implies higher leakage current and therefore larger dissipated power.
The result is a feedback system that may quickly diverge (thermal runaway), unless prevented by proper
cooling. If a sensor (n-type) is irradiated above the fluence causing type inversion, the increase of the net
doping concentration leads to an increase of the full-depletion voltage, which can, in some applications,
exceed thousand volts after some years of operation. As it is unpractical to increase the operation voltage
up to this range, the alternative would be to work with partially depleted sensors. However, for a given
maximum operation voltage, the depth of the depletion zone and therefore the electrical signal will
decrease. The detector system has therefore to be designed in such a way that it can still work with
reduced signals, with a maximal operation voltage still high enough to provide sufficient signal.
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Chapter 5 - Irradiation
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3D detectors seem a good solution with respect to these problems since their architecture allows a starting
operation bias much smaller than for planar detectors, and at the same time provides higher radiation
hardness [5-16],[5-17]. Reverse annealing also turns out to be critical if the sensors are planned to be used
for several years. The full-depletion voltage increases significantly after some weeks at room temperature,
which means that a proper cooling should be foreseen without long interruptions.
5.2 – PS irradiation f acility overview
The irradiation work presented in this thesis has been done at the CERN Proton Synchrotron (PS) facility
from September to November 2009, using the Irrad 1 shuttle and Irrad 3 table for irradiation located in the
East Hall Area of the PS [5-18]. Figure 5.5 shows the PS ring in the contest of CERN Accelerator complex [519].
Figure 5.5 - CERN Accelerator Complex
The East Area for irradiation includes two facilities, one for proton irradiation (Irrad 1, Irrad 3, Irrad 5 and
Irrad 7) and the other for neutron irradiation (Irrad 2), which make use of the 24 GeV/c proton primary
beam of the CERN-PS (shown in Figure 5.6). The proton and the neutron bursts are delivered during the
14.4 s supercycle of the PS in 1-3 spills of about 400 ms [5-20].
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Chapter 5 - Irradiation
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Figure 5.6 - PS East Hall Area with beam characteristics
Both proton and neutron irradiation zones are equipped with a remote controlled shuttle to move small
dimension samples (maximum with a 5 cm2 area) from the counting room into the irradiation area. For
bigger size samples or for irradiations requiring cooling, fixed mechanical tables are positioned along the
beam line, as shown in Figure 5.7:
Figure 5.7 - Irrad 1 and Irrad 3, 5, 7 (inside tables) places at the PS
To control the status of the beam during irradiation, a Secondary Emission Chamber (SEC) provides a
measurement of the proton beam intensity (at about 10 meters from the Irrads), and a Beam Profile
Monitor BPM electronics board allows to have online all the information and shape of the beam. The value
of fluence taken by the irradiated samples is measured by activation of aluminum foils positioned near
them. This technique provides fluence measurements with an accuracy of ~7%, and is performed with a Gespectrometer for Na-22 (long irradiation) and Na-24 (short irradiation) decay analysis.
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Chapter 5 - Irradiation
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5.3 – Irradiation of FBK-3D and planar s ensors
3D detectors are being investigated to be possibly used for the ATLAS IBL-modules; so they need first to be
qualified for radiation doses of 300 Mrad or fluences of 5 × 1015 1MeV neutron equivalent per cm2, after
which they will be tested with beams to measure their performance as tracking detectors. The preliminary
results about the first step of such irradiation program are presented here. Irradiated sensors are bumpbonded with FE-I3 chips, which cannot go over 2 × 1015 n/cm2, or 4 × 1015 p/cm2 [3-20].
5.3.1 – Irradiation of FE-I3
Before irradiating the SCAs, the FE-I3 has been investigated to confirm till which fluences it can be properly
operated. A board with only a FE-I3 chip mounted on it has been used (shown in Figure 5.8), which has
been irradiated at room temperature (~27 °C) without clock and power. Irradiation has been performed at
the CERN PS with the 24 GeV/c proton beam, using the shuttle Irrad1, in three steps:
1. 1.07 × 1015 ±7.0%
2. 2.24 × 1015 ±7.3%
3. 3.78 × 1015 ±7.5%
𝑝
𝑐𝑚 2
𝑝
𝑐𝑚 2
𝑝
𝑐𝑚 2
After each step it has been re-calibrated in order to verify its functionality.
Figure 5.8 - FE-I3 chip board
The FE-I3 has been confirmed working after each step (Figures 5.9, 5.10 and 5.11 show results of the 3 rd
step of irradiation, while in Table 5.1 there is a complete summary of the results).
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Chapter 5 - Irradiation
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Figure 5.10 - Noise of calibrated FE-I3 irradiated at
15
2
3.78 x 10 p/cm
Figure 5.9 – Threshold of calibrated FE-I3 irradiated at
15
2
3.78 x 10 p/cm
15
2
Figure 5.11 - ToT of calibrated FE-I3 irradiated at 3.78 x 10 p/cm
Before Irradiation
Threshold (e)
Noise (e)
ToT (e)
3262.00 ± 37.33
101.8 ± 8.3
61.67 ± 1.84
1.07x1015 p/cm2
± 7.0%
3224.00 ± 47.07
103.3 ± 8.76
59.21 ± 2.32
2.24x1015 p/cm2
± 7.3%
3250.00 ± 42.53
101.90 ± 8.12
58.80 ± 2.34
Table 5.3 - Results of FE-I3 calibration before and after irradiation steps
102
3.78x1015 p/cm2
± 7.5%
3293.00 ± 57.03
105.50 ± 8.12
59.85 ± 2.42
Chapter 5 - Irradiation
s
5.3.2 – Irradiation of SCAs – Setup
The SCAs which have been irradiated are:



an FBK-3D DTC2 (3EM5), with bias voltage of -35 V;
an FBK-3D DTC2b (3E7), with bias voltage of -8 V;
an ATLAS planar n-in-n, used as a reference, with bias voltage of -150 V.
They have been irradiated all together inside a cooling system, to avoid thermal runaway, keeping the FE-I3
chip not clocked and not powered. During the irradiation the temperature has been kept in the range -14 to
-7 °C. The cooling was obtained with a vortex tube (produced by Meech manufactory [5-21]), shown in
Figure 5.12 and 5.13.
Figure 5.12 - Vortex Tube Meech schematic
Figure 5.13 - Cooling box on Irrad 3 with Meech Vortex Tube
The Vortex Tube (VT) cooler is a mechanical device to separate a compressed gas into hot and cold streams.
It has no moving parts, as can be seen from Figure 5.14.
Figure 5.14 - Separation of a compressed gas into a hot stream and a cold stream in the VT
The VT cooler is composed by one or more inlet nozzles, a vortex chamber, a cold-end orifice, a hot-end
control valve and a tube. Pressurized gas is injected tangentially into a swirl chamber via the inlet nozzles,
and accelerates to a high rate of rotation: a swirling flow is so created inside the vortex chamber. Due to
the conical nozzle at the end of the tube, only the outer shell of the compressed gas is allowed to escape at
that end. The remaining gas is forced to return into an inner vortex of reduced diameter within the outer
vortex, it swirls to the center of the chamber and is expanded and cooled. In the vortex chamber part of the
gas swirls to the hot end, and another part exits via the cold exhaust directly. Part of the gas in the vortex
tube reverses the axial component of the velocity and moves from the hot end to the cold end. At the hot
exhaust the gas escapes with a higher temperature, while at the cold exhaust the gas has a lower
temperature compared to the inlet temperature. There are different explanations for the effect and there
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Chapter 5 - Irradiation
s
is debate on which explanation is best or correct. What is usually agreed is that the air in the tube
experiences mostly "solid body rotation", which means that the rotation rate (angular velocity) of the inner
gas is the same as that of the outer gas. This is different from what is considered a standard vortex
behaviour, where inner fluid spins at a higher rate than outer fluid. The (mostly) solid body rotation is
probably due to the long time each parcel of air remains in the vortex, allowing friction between the inner
parcels and outer parcels to have a notable effect. It is also usually agreed upon that there is a slight effect
of hot air wanting to "rise" toward the center, but this effect is negligible — especially if turbulence is kept
to a minimum. One possible explanation is that the outer air is under higher pressure than the inner air,
because of centrifugal force. Therefore the temperature of the outer air is higher than that of the inner air.
Another explanation is that as both vortices rotate with the same angular velocity and direction, the inner
vortex loses angular momentum. The decrease of angular momentum is transferred as kinetic energy to the
outer vortex, resulting in separated flows of hot and cold gas. This is somehow analogous to a Peltier
device, which uses electrical voltage to move heat to one side of a dissimilar metal junction, causing the
other side to become cold. This principle was first discovered by Ranque in 1933 [5-22], and by Hilsch in
1947 [5-23]. In memory of their contribution, the VT is also known as Ranque Vortex Tube (RVT), Hilsch
Vortex Tube (HVT), and Ranque-Hilsch Vortex Tube (RHVT). A RHVT has the following advantages compared
to the normal commercial refrigeration devices: simple, no moving parts, no electricity or chemicals, small
and lightweight, low cost, maintenance free, instant cold air, durable (because of the stainless steel and
clean working media), adjustable temperature [5-24,5-25]. The counterpart for these advantages is its low
thermal efficiency, which is the limiting factor for its application, together with the noise and availability of
compressed gas. The research on vortex tubes generally concerns aspects of the compressible fluid
dynamics of turbulent and unsteady flows, thermodynamics and heat transfer. These aspects make the
research complicated and challenging [5-26]. Irradiation with this cooling device has also been a test for its
functionality in radioactive environment, in order to be adopted as mean of cooling for PS cooling box
upgrades. It performed well during the entire period of irradiation, maintaining temperatures between -15
and -7 °C without any problems.
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Chapter 5 - Irradiation
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5.3.3 – Irradiation of SCAs – Results
The irradiation of the sensors has been performed in two fluence steps:
1. 2.00 × 1015 ±7.0%
2. 3.50 × 1015 ±7.0%
𝑝
𝑐𝑚 2
𝑝
𝑐𝑚 2
During each day of irradiation the leakage current has been monitored (sensors have been kept with bias
on), and after every step the I-V behaviour has been investigated. Figure 5.15 shows the I leakage vs fluence:
it’s the global sensor leakage current (over 2880 pixels), and it has been measured with Keithley 2410, with
a precision of ±0.01 µA.
DTC2b (3E7) 200µm
DTC2 (3EM5) 200µm
Planar 250µm
60
55
50
45
40
35
30
25
20
15
10
5
0
y = 2E-14x - 3E-14
y = 7E-15x - 2E-14
4,00E+15
3,50E+15
3,00E+15
2,50E+15
2,00E+15
1,50E+15
1,00E+15
5,00E+14
y = 2E-15x - 2E-14
0,00E+00
Ileakage (µA)
Ileakage vs fluence
Fluence (p/cm2)
Figure 5.15 - Ileakage vs fluence for 3E7, 3EM5 and planar sensors
As predicted from the theory, there is a grow in the leakage current with the increasing of the fluence
received by the sensors, and the dependence is linear. From the fluence and the hardness factor κ = 0.62 of
the 24 GeV protons provided by the CERN-PS, which converts the “physical” fluence Φphys into the neutron
equivalent fluence Φeq, it is possible to calculate:
𝜙𝑒𝑞 = 𝜅𝜙𝑝𝑕𝑦𝑠 = 0.62𝜙𝑝𝑕𝑦𝑠 =
𝑛𝑒𝑞
𝑐𝑚2
𝑛𝑒𝑞
= 2.17 ∙ 1015
𝑐𝑚2
0.62 × 2 ∙ 1015 = 1.24 ∙ 1015
0.62 × 3.5 ∙ 1015
This allows to estimate the effective dopant concentration Neff:
𝑁𝑒𝑓𝑓 = 𝑁0 + 𝑔𝐶 𝜙𝑒𝑞
with (for the considered 3D silicon FZ p-type):
𝑁0 = 1012 𝑐𝑚−3
105
Chapter 5 - Irradiation
s
𝑔𝐶 = 0.01 𝑐𝑚−1
obtaining
𝑁𝑒𝑓𝑓 2 ∙ 1015 = 1012 𝑐𝑚−3 + 0.01 𝑐𝑚−1 × 1.24 ∙ 1015 𝑐𝑚−2 = 1.34 ∙ 1013 𝑐𝑚−3
𝑁𝑒𝑓𝑓 3.5 ∙ 1015 = 1012 𝑐𝑚−3 + 0.01 𝑐𝑚−1 × 2.17 ∙ 1015 𝑐𝑚−2 = 2.27 ∙ 1013 𝑐𝑚−3
From these values it is possible to calculate the depletion voltage after irradiation:
𝑁𝑒𝑓𝑓 =
2𝜀0 𝜀𝑆𝑖 𝑉𝑑𝑒𝑝𝑙
𝑒𝑑 2
With the previous values of N eff, knowing d = 71.2 µm for the distance between two electrodes in the 3E
configuration, the values obtained are:
𝑉𝑑𝑒𝑝𝑙 2 ∙ 1015 ≅ 51.2 𝑉
𝑉𝑑𝑒𝑝𝑙 3.5 ∙ 1015 ≅ 86.7 𝑉
Given these values, one should apply higher voltages to full deplete the sensor, in order to also deplete the
region under the n-columns.
The current-related damage rate α can be calculated as:
𝐼𝑣𝑜𝑙 ,𝜙=0
𝐼𝑣𝑜𝑙
=
+ 𝛼𝜙
𝑣𝑜𝑙
𝑣𝑜𝑙
With a volume of 15552 x 10-12 m3 for FBK-3D sensors and of 19440 x 10-12 m3 for the planar sensor, and
values of Vdepl chosen at -100 V and -150 V for both irradiations to 2 x 1015 and 3.5 x 1015 p/cm2 (using the
correspondent values of fluences in Φeq) for 3EM5, at -100 V and -150 V for irradiation to 3.5 x 10 15 p/cm2
for 3E7, and at -300 V for irradiation to 2 x 1015 and for 3.5 x 1015 p/cm2 for the planar sensor, one obtains
the values of α summarized in Table 5.2:
3EM5
Vbias [V]
-100
-150
-100
-150
Φeq [neq]
1.24 E 15
1.24 E 15
2.17 E 15
2.17 E 15
α [A/cm]
3.236 E-17
5.876 E-17
2.673 E-17
3.816 E-17
3E7
-100
-150
2.17 E 15
2.17 E 15
-300
-300
1.24 E 15
2.17 E 15
3.608 E-17
5.500 E-17
Planar
2.094 E-17
3.200 E-17
Table 5.4 – Values of α for the irradiated sensors
To compare with values obtained for other silicon detectors in literature (see section 5.1.2), the α values
are scaled using the room temperature correction given in [5-27], that accounts for the strong dependence
106
Chapter 5 - Irradiation
s
of the leakage current on the temperature (roughly a factor 2 every 7.5 °C). The agreement between the α
values of Table 5.2 and the generally accepted value of ~4 x 10-17 A/cm is good enough considering the
uncertainties in the irradiation fluence and in the temperature.
The results of the I-V measurements after the two steps of irradiation are shown in Figure 5.16 for both the
FBK-3D from first and second batch irradiated at 2 x 1015 p/cm2 with all the data taken before restarting the
irradiation.
3E - DTC2
3E - DTC2b
1,70E+02
1,60E+02
1,50E+02
1,40E+02
1,30E+02
1,20E+02
1,10E+02
1,00E+02
9,00E+01
8,00E+01
7,00E+01
6,00E+01
5,00E+01
4,00E+01
3,00E+01
2,00E+01
1,00E+01
0,00E+00
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
170
180
190
200
210
220
230
240
250
260
270
reverse Bias Current (uA)
FBK-3D DDTC (@ 2 x 1015 p/cm2)
reverse Bias (V)
15
2
Figure 5.16 - Preliminary I-V curves for irradiated FBK-3D sensors at 2 x 10 p/cm
Data for the DTC2b at this first step were not fully taken due to the restarting of the irradiation. The
behaviour of the DTC2 sensor reflects the same shape of an unirradiated sensor, but with bias voltages and
currents much higher than before due to irradiation damages. From the plot one could derive that at about
-100 V the irradiated sensor is fully depleted. The same considerations can be done on Figure 5.17, where
the same comparison has been done after 3.5 x 1015 p/cm2 irradiation (second step of irradiation). This
time, the full depletion voltage is at about -150 V for both sensors.
107
Chapter 5 - Irradiation
s
3E - DTC2
3E - DTC2b
5,60E+02
5,40E+02
5,20E+02
5,00E+02
4,80E+02
4,60E+02
4,40E+02
4,20E+02
4,00E+02
3,80E+02
3,60E+02
3,40E+02
3,20E+02
3,00E+02
2,80E+02
2,60E+02
2,40E+02
2,20E+02
2,00E+02
1,80E+02
1,60E+02
1,40E+02
1,20E+02
1,00E+02
8,00E+01
6,00E+01
4,00E+01
2,00E+01
0,00E+00
0
20
40
60
80
100
120
140
160
180
200
220
240
260
280
300
320
340
360
380
400
420
440
460
480
500
520
540
560
580
600
620
640
660
680
700
reverse Bias Current (uA)
FBK-3D DDTC (@ 3.5 x 1015 p/cm2)
reverse Bias (V)
15
2
Figure 5.17 - Preliminary I-V curves for irradiated FBK-3D sensors at 3.5 x 10 p/cm
108
Chapter 5 - Irradiation
s
In Figure 5.18 the behavior of the 3D DTC2 at the two different fluences of irradiation is shown, while in
Figure 5.19 the same thing is plotted for the reference planar sensor. Results clearly show the increasing
current values with the irradiation.
@ 3.5 E15 p/cm2
@ 2 E15 p/cm2
FBK-3D DTC2 - 3EM5
reverse Bias Current (uA)
1,80E+02
1,60E+02
1,40E+02
1,20E+02
1,00E+02
8,00E+01
6,00E+01
4,00E+01
2,00E+01
0,00E+00
0
50
100
150
200
250
300
reverse Bias (V)
15
2
15
Figure 5.18 – Comparison between preliminary I-V curves for irradiated FBK-3D DTC2 sensor (at 2 x 10 p/cm and 3.5 x 10
2
p/cm )
@ 3.5 E15 p/cm2
@ 2 E15 p/cm2
2,80E+02
2,60E+02
2,40E+02
2,20E+02
2,00E+02
1,80E+02
1,60E+02
1,40E+02
1,20E+02
1,00E+02
8,00E+01
6,00E+01
4,00E+01
2,00E+01
0,00E+00
0
25
50
75
100
125
150
175
200
225
250
275
300
325
350
375
400
425
450
475
500
525
550
575
600
625
650
675
700
725
750
reverse Bias Current (uA)
Planar n-in-n
reverse Bias (V)
15
2
15
2
Figure 5.19 - Comparison between preliminary I-V curves for irradiated planar sensor (at 2 x 10 p/cm and 3.5 x 10 p/cm )
109
Chapter 5 - Irradiation
s
110
CHAPTER 6
CONCLUSIONS
111
Chapter 6 - Conclusions
s
112
Chapter 6 - Conclusions
s
F
rom the first proposal in 1997 by S. Parker, the 3D detector concept for particle tracking has been
developed and investigated, with considerable success. Columnar electrodes have undergone
continuous modifications, penetrating in different ways through the substrate thickness, following
the development of the Micro Machining techniques. Sensors with very short inter-electrode distances
have been designed, leading to very low depletion voltages and short collection distances, properties which
make 3D sensors very high radiation tolerant; other important properties are charge sharing reduction and
the possibility of active edge solutions, at the expense of a more complicated fabrication process with
respect to traditional planar technology.
This thesis focused on the characterization of a particular type of 3D detector called 3D-DDTC (Double Side
Double Type Column), where the electrodes are etched perpendicularly to the surface but do not penetrate
the entire substrate thickness. The etching is made alternatively on both the surfaces and the number of
process steps is highly reduced compared to a standard 3D process.
Detectors from two batches of 3D-DDTC (DTC2 and DTC2b, with different columnar overlap) have been
characterized and calibrated for this thesis, studying their performance in comparison with a planar sensor.
Important results have been obtained from 241Am, 109Cd and 90Sr source tests, showing for 3D detectors a
behaviour similar to the planar one in detecting gamma and beta particles. Moreover, preliminary
irradiation tests show that detectors are still working correctly after irradiation fluences up to 4×1015 p/cm2,
proving good radiation hardness as expected.
In conclusion, 3D detectors are indeed one of the most promising technology for the LHC upgrades, where
a very high radiation hardness will be required. At the same time, because of their peculiar characteristics,
they are also presently considered for other possible applications like imaging and dosimetry in Biomedical
Physics.
113
Chapter 6 - Conclusions
s
114
APPENDIXES
115
Appendixes
116
Appendixes
Appendix 1 – FE-I3
FE-I3 detailed photo
Figure A1.1 - [3-4]
FE-I3 detailed schematic
Figure A1.2 - [3-4]
117
Appendixes
Appendix 2 - TurboDAQ
A2. 1 - Start-up
The program is launched with a double click on the icon “TurboDAQ.exe” wherever it has been put on the
PC (usually on the desktop). It appears the TurboDAQ main panel, as shown in Figure A2.1:
This is the
.exe starter
This is the
main panel
This is the status
of measurement
panel
Figure A2.1: Main TurboDAQ panel
In this first panel all the functions of the software are present. It has to be noticed that always after
switching on the VME crate of the custom system the application “Resman.exe” needs to be launched in
order to configure the VME bus, and only after that it is possible to correctly start the TurboDAQ. For
testing purposes only the following parts of the software have been used and are going to be explained:
1.
2.
3.
4.
5.
POWER CONSOLE
INITIALISATION
CONFIGURATION
DATA CONTROL (with DATA FITTING CONSOLE)
SCAN CONSOLE
118
Appendixes
A2. 2 - POWER CONSO LE
One mouse click on POWER CONSOLE allows the operator to switch on the power supplies from the
software interface itself (thanks to GPIB connection to the power supplies) as shown in Figure A2.2:
Figure A2.2: POWER SUPPLY
The voltage generators are activated by clicking on the “POWER ON” buttons.
119
Appendixes
Figure A2.3: Power supply values
When active, it appears the name of the power supply, as shown in Figure A2.3 (one is for the TPCC, a
second is for the FE and a third is to deplete the sensor). The values of voltage and current have to be set
(and read) from the panel. Nominal values for the low voltage meters are stored in the power configuration
files (shown on the panel).
A2. 3 - I NITIALISATION
The first operation to be done when beginning every test is to let the TPLL communicate with the TPCC, and
this is done by opening the INITIALISATION panel
and pushing the button “Initialise PLL&PCC” on it
(see Figure A2.4). If it is all working, the leds on
the TPCC are going to remain green. If not, the
ones shown on the left in Figure A2.4 are going to
turn into red. So, if the TPCC is not communicating
with the TPLL, there is a problem to cope with. It
could happen that the TPCC board, because of the
large dimensions, may move or being dilated by
overheating when kept operative for long times.
When the problem seems to be solved, the board
has to be reinitialized.
Figure A2.4 - INITIALIZATION
120
Appendixes
A2. 4 - CO NFI GURATION
This panel allows the operator to define the configuration parameters for the measurement desired:
Figure A2.5: STATIC CONFIGURATION CONSOLE
From the panel all the Front-End DACs of FE-I3 chips are manageable: GDAC values, IF and TRIMF values,
TDACs and FDACs tuned files (see Figure A2.5). Moreover, on the top right of the panel there is the place in
which the name of the module under test has to be inserted (which is going to be recognized by the system
during the entire measurement time and every time the same module is reconnected to the system). When
all wanted values are set or uploaded, in order to send them to the system the three buttons on the
bottom of the panel have to be clicked on. On the bottom left it is shown the operative temperature kept
during the test.
A2. 5 - DATA CONTRO L
This panel is used to give the path where the software will save
the data files and to set the name for each of them (see Figure
A2.6). The “Fitting Console” button at the bottom of the panel
opens the DATA FITTING CONSOLE, which cannot be opened
from the main panel of TurboDAQ directly, but only from this
panel.
Figure A2.6 - DATA CONTROL PANEL
121
Appendixes
A2. 6 - DATA FITTING CONSO LE
In this panel the target threshold for all pixels in units of electrons and the characteristic values of the FE
(the capacity Clow and Chigh) and the calibration voltage (VCAL) which are used to tune each pixel have to be
manually written. They are proper values given by the builder of the sensor, and are saved in the final
configuration file for the module. Here there is a need to be careful with the “Feedback TrimDAC” because
the value must stay at 20000 e- for the measurement, but sometimes, when tuning other parameters or
opening other panels, this value returns to the default value of 10 (see Figure A2.7).
Figure A2.7: DATA FITTING CONSOLE
A2. 7 - SCAN CONSOLE
Last (but not at all least!) there is the SCAN CONSOLE, which allows to choose the measurement or scan to
be performed on the detector under test. The blue square button next to “SCAN CONFIG” allows to choose
the type of test wanted. The “main
scan” zone set the number of data
to be taken, as shown in Figure A2.8.
Figure A2.8 - SCAN CONSOLE
122
Appendixes
Figure A2.8 shows the default setting for an I-V scan, with 61 points taken starting from 0 to -80 V. Another
important scan is the “threshold scan internal cal” (with internal calibration). The goal for this scan is to
obtain the same threshold for each pixel. When selecting
the threshold scan, the Scan Console panel is configured by
itself (see Figure A2.10). On the bottom right, in order not
to waste time for measuring the voltage supply, one can
just change the scan option by selecting “No LV/HV Supply
Measurement” (see Figure A2.9). Then the measurement
can be launched with the “Start scan” button.
Figure A2.9 - No LV/HV Supply Measurements
Figure A2.10 - Scan choosing
The I-V measurements, which involves only the sensor and not the electronics, can be immediately done
from SCAN CONSOLE after the power is on and data path and name are set.
123
Appendixes
When a measurement is finished, by clicking on “Online plot” the results can immediately be seen.
Threshold
value
Noise
Figure A2.11: On-line plot of a threshold scan
In Figure A2.11 it is shown an example of what comes out from a typical threshold scan.
124
Appendixes
Appendix 3 – Complete plots collection
A3. 1 - Thres hold
FBK-3D DTC2: 2EM2/3EM5/4EM9
125
Appendixes
FBK-3D DTC2b: 3E7 ; ATLAS planar n-in-n
126
Appendixes
A3. 2 - Noise
FBK-3D DTC2: 2EM2/3EM5/3EM7/4EM9 ; FBK-3D DTC2b: 3E7 ; ATLAS planar n-in-n
127
Appendixes
A3. 3 - ToT
FBK-3D DTC2: 2EM2/3EM5/4EM9
128
Appendixes
FBK-3D DTC2b: 3E7 ; ATLAS planar n-in-n
A3. 4 -
2 4 1 Am
FBK-3D DTC2: 2EM2/4EM9 @ -35 V
129
Appendixes
A3. 5 -
1 0 9 Cd
FBK-3D DTC2: 2EM2/4EM9
130
Appendixes
A3. 6 - 9 0 Sr with Clus ter Size1 and Clus ter Size 2, with collimator, at different bias
values (-15V, - 35V, -55V) – PRELIMI NARY ANALYSIS PLOTS
(2 cm distance from source to sensor surface, 1 cm of collimator included):
FBK-3D DTC2: 2EM2
131
Appendixes
FBK-3D DTC2: 3EM7
132
Appendixes
FBK-3D DTC2: 4EM9
133
Appendixes
134
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Acknowledgements
The work for this thesis has been done at CERN during almost a year. This has been a very important period
for myself and for my career. I had the opportunity to learn a lot of Physics in the most important center of
Physics in the world, surrounded by the excitement connected to the start of LHC, and I could learn how to
work applying my studies, being inserted in a competitive environment and being given responsibilities. I
have worked and cooperated with people coming at CERN from all over the world, and learn something
from each of them. I have spent an exciting period abroad, finding the CERN area really attractive and
pleasant to live in, and with all the mentioned above people could establish good friendships outside the
work time.
Coming to specific thanks, I would like to express my acknowledgement to Dr. Alessandro La Rosa (who has
been my CERN supervisor) for his guidance, support and continuous encouragement, and to Prof. Ada
Solano and Prof. Michele Arneodo (who have been my University advisors), who believed in me, giving me
the possibility to enter this project, and supporting me continuously from the very beginning. I would also
thank Prof. Gian-Franco Dalla Betta for his excellent suggestion during our brainstorming, and Jens
Weingarten for his hints in the TurboDAQ usage.
I also have to thank all the people involved in the ATLAS 3D Pixel project with which I collaborated, in
particular to Cinzia Da Vià, Håvard Gjersdal, Phillippe Grenier, Ole Rhøne, Per Ola Hansson, Sebastian
Grinstein, Dmitri Tsybychev, Jie Wen Tsung, Salvatore Fazio; it has been an excellent experience to work
and to learn from them.
I have also spent four months at CERN PS Irradiation Facility under the supervision of Maurice Glaser and I
would like to thank, first and foremost, Maurice and all the people I have worked with during my stage. In
particular, my thanks to Nicola Pacifico, Michael Moll, Gianluigi Casse and the RD50 Collaboration for
having involved me in their activity.
I want to also thank also my “brother in arms” Marcello, with whom I divided the first part of my
experience at CERN, and all the people I met during these months.
Finally, I want to thank my family and Sara, since they make leaving CERN not too sad!
I really enjoyed this experience. Thanks a lot to all who have been involved in!
…and good luck to the LHC!
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