Download Antiresonant Reflecting Optical Waveguide (ARROW

Efficient Computation methods
for 3D Microscopic Ellipsometry
Yia-Chung Chang
Research Center for Applied Sciences (RCAS)
Academia Sinica, Taipei, Taiwan, R.O.C.
Collaborators:
Huai-Yi Xie, Paul C.-H. Chien, Yu-Da Chen (RCAS, AS)
R. Moirangthem, Shih-Hsin Hsu
IWCSW, NTU, Oct. 17, 2013
1
Introduction
• Targeted drug delivery will be a key biotechnology for
treating cancers and other diseases.
• Non-invasive and label-free imaging technique will
be important for observing the interaction of cells and
drugs.
• 3D ellipsometric imaging can resolve not only the
tomography but also the optical content of the
biological structure, thus providing more information
than existing microscopy techniques.
• Spectral ellipsometry has been successfully used in
semiconductor industry for metrology of critical
dimension and it has also been shown to provide
improved biosensing capability at modest cost.
2
Current State of the Art for 3D imaging
• Non-interferometric wide-field optical profilometry
(NIWOP) has image resolution ~ 0.3μm [C.H.
Lee’s group, Physical Review Letters, 103, 238101
(2009)]
• A new Bessel beam plane illumination method can
improve the resolution to <0.3μm
[Betzig’s group, Nature methods, 8, 418 (2011)]
• With the aid of proper imaging optics an
ellipsometric image can be formed which resemble
the high vertical resolution of conventional
ellipsometry for each homogeneous patch of the
surface.
• The lateral resolution is on the order of 1-2 μm and
is given by the numerical aperture of the objective.
• A piezo translation stage can be used to scan the
image.
3
Bessel beam technique for 3D imaging of live-cell dynamics
[Planchon et. al., nature methods, 8, 418 (2011)]
Estrogen receptor in a live U2OS cell
Filopodia of a live HeLa cell
Bar = 5 μm
African green monkey kidney cell (COS-7)
Bar=10 μm
4
Optical Nanometrology
Optical nanometrology allows optical inspection of
the geometry of nanostructures down to 10nm scale.
It uses a best fit to the measured ellipsometric spectra
via theoretical simulation (with efficient software) to
determine the critical dimension.
If done correctly, one can reconstruct images of nm
resolution by using an optical instrument (with
wavelengths 100nm-1000nm).
It is noninvasive and capable of probing buried
structures and biological systems
5
Ellipsometry Basics
1. Known input polarization
E
p-plane
s-plane
3. Measure output polarization
p-plane
E
s-plane
plane of incidence
2. reflect off sample ...
In Jones Matrix representation, ellipsometry measures Ψ and Δ in:
  tan  ei 
~
rp rp i  p  s 
~ 
e
in
Es
rs
rs
in
E out
E
p
p
Esout
6
Characteristic Spectra
Air
Light is transmitted
and reflected or
refracted at each
interface. Amplitude,
phase & polarization
are changed by
multiple interactions
Film Stack
Grating
Each Attribute
(Thickness, Pitch,
CD, Profile)
Contributes to Unique
Ellipsometry Spectral
Amplitude of Four
Fourier Coefficients,
DC, Sin(2wt), Sin(4wt),
Cos(4wt))
vs Wavelength
(Data provided by Themawave Inc.)
Film Stack
Rigorous Coupled-Wave Analysis
• Most used method for rigorous analysis of optical
diffraction by periodic gratings.
• For multilayer system with definite periodicity
• EM fields in each layer are expanded in terms of a
finite number (N) of plane waves
• The coefficients are dertermined by matching
boundary conditions at all interfaces.
• The method is accurate (as long as enough plane
waves are used) by not necessarily efficient (scale
like N3)
8
A typical fitting to the data of the scatterometry
components of sin2w, sin4w, and cos4w
1.0
0.8
Amplitude
0.6
DC
0.4
0.2
Sin2w
0.0
-0.2
Sin4w
-0.4
-0.6
200 300 400 500 600 700 800
Wavelength (nm)
Cos4w
9
The RT/CDTM technology combines the standard Opti-Probe rotating compensator
spectroscopic ellipsometer (RCSE) 4 and a high performance (10 GHz) server. RCSE
spectra from samples with periodic line/space structures taken on the Opti-Probe
are sent to the server that performs the real-time regression analysis and returns
calculated CD profiles as well as underlying film thicknesses.
CD
jobfile
10
Height (A)
4000
3000
3000
2000
2000
1000
1000
0
Height (A)
Application 1
Poly-Si Gate Line at
Develop Inspect (DI) Stage
4000
0
4000
Sidewall angle
CD
Height (A)
3000
Pitch
2000
1000
Resist
ARC
Height (A)
4000
-100
-50
0
50
4000
100
3000
3000
2000
2000
1000
1000
0
0
-100
-50
0
50
100
-100
-50
0
50
100
CD (nm)
(Data provided by Themawave Inc.)
* This data is wafer dependent. Customer specific data must be gathered with customer wafers.
Height (A)
Poly-Si
Oxide
Si-substrate
0
Application 2
Shallow Trench Isolation
Sidewall angle
C
1CD
D
Pitch
Nitride
Oxide
EPI
Si-substrate
(Data provided by Themawave Inc.)
[J. Opsal, H. Chu, Y. Wen, Y.C. Chang and G. Li, Proceedings of SPIE 2002, Metrology,
Inspection and Process Control for Microlithography XVI, p. 163 (2002)]
Evolution of the real time regression fitting from beginning (top figures) to final solution (bottom
figures) illustrating how adding feature detail improves the quality of the fit.(Symbols: : DC, :
Sin(2wt), : Sin(4wt),:  Cos(4wt)) to measurement results (Lines)
500
0.8
400
0.4
300
200
0.0
100
-0.4
1.53 Sec
R=0.0928
0
500
-0.8
0.8
X Data
400
0.4
300
200
0.0
-0.4
2.05 Sec
R=0.0753
0
500
-0.8
0.8
400
0.4
300
200
0.0
100
-0.4
3.69 Sec
R=0.0400
0
500
-0.8
0.8
400
0.4
300
200
0.0
100
-0.4
8.93 Sec
R=0.0228
0
-0.8
-200 -150 -100 -50
0
50 100 150 200
CD (nm)
300
400
500
600
Wavelength (nm)
700
SE Fourior Coeff.
Height (nm)
100
-150
-200
-250
100
50-150-100 -50
0
0
200
-50
150
-100
100
-150
50
-200
Height (nm)
300
-50
50 100
150
250-150-100
0
X Data
0
-250
250
-50
-150-100 -50
200
150
0
50 100 -150-100
150
-50
50 100 -150-100
150
-50
X Data
0
-50
50 100 -150-100
150
0
50 100 150
0
50 100 150
Heighte (nm)
-100
Heighte (nm)
0
-50
Heighte (nm)
Heighte (nm)
50
Heighte (nm)
Single {CD1-4, tPR, tArc,} recipe for monitoring a DI wafer under
focus exposure matrix (FEM)
X Data
0
50 100 -150-100
150
-50
X Data
-150-100 -50
X Data
0
50 100 -150-100
150
-50
X Data
0
50 100 150
X Data
100
50
0
-50
-100
-150-100 -50
0
300
50 100 -150-100
150
-50
250
200
0
50 100 -150-100
150
-50
X Data
0
50 100 -150-100
150
-50
X Data
0
-50
50 100 -150-100
150
0
50 100 -150-100
150
-50
X Data
X Data
0
-50
50 100 -150-100
150
0
50 100 150
X Data
150
100
50
0
-50
-150-100 -50
0
50 100 -150-100
150
-50
0
50 100 -150-100
150
-50
X Data
-150-100 -50
0
50 100 -150-100
150
-50
0
0
50 100 -150-100
150
-50
X Data
50 100 -150-100
150
-50
0
0
50 100 -150-100
150
-50
0
50 100 150
X Data
50 100 -150-100
150
-50
0
50 100 150
CD (nm)
14
Comparison of various methods
method
complexity
scaling
best for
RCWA (rigorous coupled wave analysis):
1
10MN 3
straight grating
Finite-difference (transfer-matrix method):
1
MN3
any 2D grating
FDTD (finite-difference time domain)
2
T*6*Ng
G0 (multi-layer Green’s function):
3
G1,G2 (ideal grating Green’s function):
5
G3 (ideal cone Green’s function):
8
BIM (boundary-integral method):
8
BEM (boundary-element method):
10
time-dependent behavior
3KMNg ~ 3KMN2
2D/3D features
10N3+5kMN2 2D/3D features on grating
5kMN 2
3D objects near a cone
(2L+fN)(2L)2 isolated structure
K(2L+fN)(2L)
isolated structure
N=number of basis functions(coupled waves): 10-100 (1D), 100-10000 (2D)
M=number of slices : 1-100
T = time steps (>1000); Ng=number of real-space grids (>100d)
K=number of iterations (~ 100)
L=number of boundary elements
f=prefactor for evaluating GF ~ 20
15
Specialized Green’s function methods
(a) G0 (Multilayer GF)
(b) G1 or G2 (Grating GF) (c) G3 (Cone GF)
[Y. C. Chang et al., J. Opt. Soc. Am. A 23, 638 (2006)]
16
Perform finite-element integration
analytically
17
18
)
19
20
21
Scattering from 2D periodic array of contact holes
We solve the Lippmann-Schwinger equation,
both in k-space and r-space
23
24
Fit to measured data
(sample provided by TSMC)
p=1000nm, d=296.212nm, t=409.493nm
New efficient Method
•
We developed a Green function approach which
can model nanoparticle clusters embedded in a
random distribution of nanoparticles
RN
R3
R2
y
d
x
y
R1
d x
O
substrate
Ellipsometry measurements of Au
nanoparticles on a substrate
Motivation
 Au nanoparticles of definite size can be obtained commercially.
 They can be placed on insulating substrate and serve as a
mask for making nanostructures.
 It is desirable to have a characterizing tool that can detect the
density and uniformalty of the distribution of Au
nanoparticles on a substrate.
 Ellipsometry is an optical characterizing tool that is
noninvasivce, can penetrate deep into the material, and can be
used in-situ during growth.
 Here we try to explore the capability of elliposmetry for
characterizing nanoscale structures on surface or in burried
interface.
27
Nanorods Sample Preparation
(by Gong-Ru Lin, National Chiao-Tung University)
Developed pattern of Ni
particles on oxide on Si
Transfer oxide pattern
RIE etching
Remove oxide and Ni
SEM scan of Si nanorods
28
SEM of Au Nanoparticles of different sizes
d = 20nm
d = 40nm
d = 60nm
d = 80nm
29
VUV-VASE Specifications
(J. A. Woollam Co.)
 Rotating analyzer ellipsometer
configuration (RAE) with the
addition of AutoRetarder
 Dry nitrogen purge to eliminate
absorption from ambient water
vapor and oxygen
 Spectral range: 140nm ~ 1700nm
 Angle of incidence: 10° ~ 90°
30
Ellipsometry Results – Au NP@60o
o
o
Au NP, 60
Au NP, 60
18
80
70
16
60 nm
60
20 nm
12
80 nm
10
40 nm
8
50
 (degree)
 (degree)
14
40
30
10 nm
20 nm
40 nm
60 nm
80 nm
20
10
6
10 nm
0
4
1
2
3
4
5
6
Photon energy (eV)
7
8
1
2
3
4
5
6
7
8
Photon energy (eV)
31
Model fits
• Here we assume Au nannoparticles are sphere like
(with diameter d) and placed uniformly on a square
lattice with pitch p. The spheres are modeled by 15 to
100 slices of discs.
• We use fixed optical dielectric constants of bulk Au
and substrate.
• d=20, 40, 60, 80 nm
• picth varies between 40nm-1000nm
• Square lattice, hexagonal lattice, random structures
• Calculations performed by Green’s Function method
32
Optical Constants of Gold
Au (bulk)
20
18
0
16
1
14
-40
12
-60
10
-80
8
2
1
-20
-100
2
6
-120
4
-140
2
-160
1
2
3
4
Photon energy (eV)
5
0
6
source: Ioffe Institute (http://www.ioffe.ru/SVA/NSM/nk/),
data from E. D. Palik, Handbook of Optical Constants of Solids
33
Effects of Disorder
34
Simplified model for structure factor
S(g) = 1 + ∫rdr dφexp{i gr cosφ}/ Ac
L
= 1+ 2π ∫a rdr J0(gr) /Ac
= 1 + Nδk,k0 – 2π(a2/Ac)J1(ga) /ga,
N= total number of atoms considered,
g = k - k0
Ac = average cell volume
35
SE of randomly distributed
nanoparticles without clusters
16
o
Ψ
12
16
60
8
o
65
4
o
60
8
4
(b)
1
o
55
2 3 4 5 6 7 8
Photon energy (eV)
20
d=20nm
(a)
(c)
150
o
65
120
16
o
60
12
55
1
o
0
2 3 4 5 6 7 8
Photon energy (eV)
24
65
16
o
60
12
Δ
65
2 3 4 5 6 7 8
Photon energy (eV)
Ψ
o
1
o
20
o
60
30
o
60
o
65
2 3 4 5 6 7 8
Photon energy (eV)
8
o
4
(d)
1
55
2 3 4 5 6 7 8
Photon energy (eV)
d=60nm
o
55
30
4
55
90
60
o
55
90
60
o
8
150
120
d=40nm
24
Ψ
1
o
55
2 3 4 5 6 7 8
Photon energy (eV)
Δ
Ψ
12
Δ
o
Δ
65
180
150
120
90
60
30
0
1
o
60
o
1
180
150
120
90
60
30
0
1
65
2 3 4 5 6 7 8
Photon energy (eV)
d=80nm
o
o
55
60
o
65
2 3 4 5 6 7 8
Photon energy (eV)
36
Comparison of modeling based on
random and periodic distributions
Nanoparticle
diameter
D (nm)
Similarity
factor
f
Average
pitch
p (nm)
Fraction
of small
clusters, fc
Fraction
of
nanopart
icles in
patches,
fp
20
1.0
50
0
0
0.87 (9.89)
36
0.8
140
0.015
0.005
1.27 (11.44)
0.90 (9.68)
60
0.7
170
0.02
0.05
1.81 (12.36)
1.12 (9.87)
80
0.7
245
0.025
0.05
2.38 (13.84)
1.53 (10.79)
MSE
for ψ (Δ )
noncluster
model
MSE
For ψ (Δ )
cluster
model
37
Modeling clusters
V2
V3
V4
38
Comparison with the generalized
Mie scattering theory for isolated clusters
1.6
1.6
1.2
1.2
O
0.8


O
0.8
0.4
0.4
0.0
0.0
1
2 3 4 5 6 7
Photon energy (eV)
(a)
8
1
2 3 4 5 6 7
Photon energy (eV)
8
(b)
39
150
20
100
2
3 4 5 6 7 8
Photon energy (eV)
9

0
1
65
12
50
10
0
16
1
2
3 4 5 6 7 8
Photon energy (eV)
9
o
60
o

30


SE of randomly distributed nanoparticles with clusters
8
(a)
4
400
55
o
40

d=40nm
55
60
o
o
1
8
o
65
2 3 4 5 6 7
Photon energy (eV)
8
200
100
10
1
2
3 4 5 6 7 8
Photon energy (eV)
0
9
1
2
3 4 5 6 7 8
Photon energy (eV)
20
9
400
40
300

50


200
12
100
2
3 4 5 6 7 8
Photon energy (eV)
0
9
150
60
55
o
1
1
2
3 4 5 6 7 8
Photon energy (eV)
d=60nm
90
55
60
o
30
4
20
1
o
120
8
30
10
65
16
(b)
0
2 3 4 5 6 7
Photon energy (eV)


20
0
1
300
30
180
150
120
90
60
30
0
2 3 4 5 6 7
Photon energy (eV)
0
8
65
1
9
o
60
o
o
2 3 4 5 6 7
Photon energy (eV)
8
30
300
100
0
0
1
2
3 4 5 6 7 8
Photon energy (eV)
9
1
2
3 4 5 6 7 8
Photon energy (eV)
9
300
20
200


30
10
0
100
1
2
3 4 5 6 7 8
Photon energy (eV)
0
9
(e)
60
12
o
1
2
3 4 5 6 7 8
Photon energy (eV)
9
90
55
60
4
55
1
400
d=80nm
150
8
(d)
40
o
120
16
200
10
65
20

20
180
24

400


(c)
40
30
o
2 3 4 5 6 7
Photon energy (eV)
o
0
8
60
65
1
2 3 4 5 6 7
Photon energy (eV)
o
o
8
Comparison with experiment
[ Opt. Exp. 21, 3091(2013); J. Opt.
Soc. Am. B 30, 2215 (2013) ]
Multiskop setup
 original capabilities

single-wavelength measurement (l = 632.8 nm)

variable-angle ellipsometry/reflectance

imagine ellipsometry (spatial resolution:  10 mm)
 completed integration and upgrades

supercontinnum laser + monochromator  spectroscopic measurement
(l = 400 ~ 950 nm)

projected-field electromagnet  magneto-optic Kerr effect (MOKE)

in-house control software for automatic measurement and analysis
 scatterometry (scattering-type ellipsometry/reflectance)
 variable-angle spectroscopic ellipsometry/reflectance
 spectroscopic imaging ellipsometry (spatial resolution:  1 mm)
41
SEM of Au Nanoparticles (60 nm)
42
One Pot Synthesis ZnO Microspheres using
Hydrothermal Technique
Before growth
After growth
Whispering Gallery Mode Enhanced
Photoluminescence of ZnO Microsphere
PL spectra of a single ZnO microspheres place on the silicon
substrate with diameters (a) 2.7µm, (b) 2.5µm, (c) 2.19µm, and (d)
1.52µm respectively
Characterizing ZnO microspheres
Comparison with the Mie scattering theory for an
isolated ZnO sphere (diameter=0.2,0.5,1,2µm)
3
z
a  1
y
O R
2

1.0

 ZnO d  2R
R
SHGF method
Mie theory
1.2
1
0.8
0.6
450
500
550
600
wavelength (nm)
650
0
450
(a) d=0.2µm
x
500
550
600
wavelength (nm)
650
(b) d=0.5µm
5
4
4
3


3
2
1
1
inc
E
 z  e
ik0 z
ex
0
450
2
500
550
600
wavelength (nm)
(c) d=1µm
650
0
450
500
550
600
wavelength (nm)
(d) d=2µm
650
Calculated projeted ellipsometry parameters of a 1 μm
ZnO sphere on Au substrate (wavelength=450nm, an
angle of incidence=60o)
p
p
z 0
tan 
cos 
d=1µm
p=3.01µm
tan 
d=2µm
p=6.02µm
cos 
Calculated projected ellipsometry parameters of a 1 μm
ZnO sphere on Au substrate (wavelength=550nm, an
angle of incidence=60o)
tan 
cos 
tan 
cos 
d=1µm
p=3.01µm
d=2µm
p=6.02µm
Calculated projected ellipsometry parameters of a 1 μm
ZnO sphere on Au substrate (wavelength=650nm, an
angle of incidence=60o)
tan 
cos 
tan 
cos 
d=1µm
p=3.01µm
d=2µm
p=6.02µm
Calculated projected ellipsometry parameters of a 5 μm ZnO
sphere on Au substrate (wavelength=450nm, an angle of
incidence=60o) and compare with experimental data
tan 
cos 
Experiment
data
Modeling
p=15.05µm
tan 
cos 
tan(Ψ)
Microscopic ellipsometry of 7.8 μm single ZnO sphere
λ= 550nm
Cos(Δ)
λ= 450nm
51
tan(Ψ)
Microscopic ellipsometry of a 5 μm ZnO sphere on Au film
λ= 550nm
λ= 650nm
Cos(Δ)
λ= 450nm
52
Future directions
 Construct ray-tracing modeling based on geometric optics for
large-scale objects (D>>λ) and combine with wave optics
simulation for small scale objects (D< λ).
 Implement computer simulation suitable for micro ellipsometry
based on NIWOP or Bessel beam optics.
 Study micro ellipsometry spectra of various arrangements of
Au nanaoparticles and compare with computer simulation, and
build a library to recognize patterns quickly.
 Study biological objects and their interaction with Au
nanaoparticles.
53
Toward Computation-aided 3D Imaging
Ellipsometry for bioimaging
• Use microscopic ellipsometry to
measure ψ and Δ images at a few
angles and wavelengths (Fig. 1)
• Compute ε1 , ε2 and thickness for each
pixel (~1μm) to construct 3D
tomography (Fig. 2)
• Use efficient algorithm to compute
characteristic spectra for light
scattering from coupled Au
nanoparticles embedded in a
multilayer films to identify fine
details (~30nm) inside each pixel
• Use this technique for bioimaging to
learn something new
ψ
(Fig. 1)
(Fig. 2)
Δ
Exploring the Formation of Focal Adhesions on
Patterned Surfaces using Super-resolution Imaging
Chen et al, Small (2011)
Summary
Samples with different sizes of Gold nanoparticles immobilized on a
glass substrate are investigated by variable-angle spectroscopic
ellipsometry (VASE) in the UV to near IR region.
Both the Green’s function method and rigorous coupled-wave analysis
(RCWA) were used to model the ellipsometric spectra
GF method is 10 – 100 times more efficient than RCWA in most cases
for lattice model calculation.
For random scattering problem, only GF method is used, and it is
faster by another order of magnitude.
Our model calculations show reasonable agreement with the
ellipsometric measurements.
This demonstrates that the spectroscopic ellipsometry (SE) could be a
useful tool to provide information about the size and distribution of
nanoparticles deposited on insulating substrate.
The technique can be extended to 3D imaging SE to inspect
56
57
58
59
60
Ellipsoemtric spectra of isolated clusters for
specular (solid) & off-specular (dot-dashed) reflections
550
600
650
61
Modeling of Whispering Gallery Modes of ZnO
Microspheres
[R. S. Moirangthem et al., Optics Exp., 21, 3010–3020 (2013)]
Theoretically fitted ZnO microsphere diameters with series of resonance mode number m at (a) ∆n=0 and
(b) ∆n=0.1782.
(a) shows a schematic of a single ZnO microsphere under optical excitation, mode profile showing
total electric field distributions of the WGM modes at resonance peak position (λ═523.3nm) along (b)
x-y cross-section at z=R and (c) y-z cross-section at x═ 0.
Our Microscopic imaging ellipsometer
 original capabilities
(Multiskop)

single-wavelength measurement (l = 632.8 nm)

variable-angle ellipsometry/reflectance

imagine ellipsometry (spatial resolution:  10 mm)
 completed integration and upgrades

supercontinnum laser + monochromator  spectroscopic measurement
(l = 400 ~ 950 nm)

projected-field electromagnet  magneto-optic Kerr effect (MOKE)

in-house control software for automatic measurement and analysis
 scatterometry (scattering-type ellipsometry/reflectance)
 variable-angle spectroscopic ellipsometry/reflectance
 spectroscopic imaging ellipsometry (spatial resolution: 2 mm->10nm)
Pixel -> feature
63
Ellipsoemtric spectra of isolated clusters
for off-spectacular reflection
0.0015
0.015
0.015
0.010
0.005
0.015
0.010
Rp
0.0005
Rs
Rp
Rs
0.0010
0.020
0.005
2
3 4 5 6 7 8
Photon energy (eV)
0.000
1
Rp
Rs
0.0010
0.02
0.01
0.0005
0.00
1
2 3 4 5 6 7 8
Photon energy (eV)
0.0020
0.05
0.0015
0.04
Rp
Rs
0.000
1
(b)
2 3 4 5 6 7 8
Photon energy (eV)
0.04
0.04
0.03
0.03
0.02
0.01
0.00
1
0.0010
0.0005
0.0000
1
2 3 4 5 6 7 8
Photon energy (eV)
2 3 4 5 6 7 8
Photon energy (eV)
0.03
0.0015
0.0000
1
0.000
1
0.005
Rp
0.0020
(a)
2 3 4 5 6 7 8
Photon energy (eV)
Rs
0.0000
1
0.010
0.02
0.01
2 3 4 5 6 7 8
Photon energy (eV)
0.00
1
2 3 4 5 6 7 8
Photon energy (eV)
0.03
0.02
(c)
0.01
2
3 4 5 6 7 8
Photon energy (eV)
0.00
1
2
3 4 5 6 7 8
Photon energy (eV)
64
Optical nanometrology
Yia-Chung Chang
Height (A)
2000
1000
1000
0
Resist
4000
3000
Height (A)
ARC
Poly-Si
Oxide
Si-substrate
2000
1000
0
4000
-100
-50
0
50
4000
100
3000
3000
2000
2000
1000
1000
0
0
-100
-50
0
50
100
-100
-50
0
50
100
CD (nm)
 It is noninvasive and capable of probing
buried structures and biological systems
 Previous simulation is limited to 1D and
2D isolated or periodic structures
 We extend the technique to 3D and
random structures
p=1000nm, d=296.212nm,
Height (A)
 It uses a best fit to the measured
ellipsometric spectra via theoretical
simulation (with efficient software) to
determine the critical dimension.
3000
2000
0
Height (A)
 Optical nanometrology allows optical
inspection of the critical dimension of
nanostructures down to nanoscale.
Pitch
4000
3000
Height (A)
Sidewall angle
4000