Sensors and Control - University of California, San Diego

Feature-level Compensation & Control

Sensors and ControlSeptember 15, 2005

A UC Discovery Project

9/15/05 Sensors and Control

2

FLCC

Current Milestones• Integrated sensor platform development 2 (M26 YII.16)

Gather CMP and etching rate data and correlate with process variables.• Complete preliminary experimental study for CD non-uniformity

reducing across the litho-etch sequence (M27 YII.17)Assess predictive capability of mode, and build optimizing software to compute optimal changes in control parameters. Provide proof of concept test of CD non-uniformity reduction scheme based on direct CD metrology.

• Zero-footprint Optical Metrology Wafer (Milestone Added, YII.18) Evaluate and calibrate dielectric thickness monitoring (resolution, sensitivity, and stability). Metal etch endpoint and pre-endpoint (<50nm) detection and monitoring. Testing the prototype metrology wafer in vacuum environment.

• Using Spatial CD Correlation in IC Design (M30 Major Rev., YII.19)Initial experiments on test structures and measurement for extracting spatial correlation characteristics.

• Aerial Image Metrology (M31 YII.20)Integrate prototype transducer for use and deployment on a silicon wafer.


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FLCC

Zero-Footprint Optical Metrology Wafer

Prototype and develop methodology for in-situ process monitoring with zero-footprint metrology wafer.

Student(s): Vorrada Loryuenyong and ZhongSheng Luo*

PI. Professor Nathan Cheung

* Currently at KLA-Tencor


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FLCC

2005 Main Objectives

Evaluate and calibrate dielectric thickness monitoring (resolution, sensitivity, and stability). [Resolution and sensitivity analysis completed]

Testing the prototype metrology wafer in vacuum environment. [Completed]

Metal etch endpoint and pre-endpoint (<50nm) detection and monitoring. [In progress]


5

FLCC

3x3 pixel Zero-Footprint Metrology Wafer

Sketch of the cross-section of the prototype.

RPD PPDLED Detecting Window

Backside Contact ViaBottom Wafer

Top Wafer


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FLCC

Pixel-to-Point Transfer2. Release of the growth 2. Release of the growth substrate:Laser Liftoffsubstrate:Laser Liftoff1. Pick1. Pick--up of up of

the pixelthe pixel

Sapphire

Laser beam

3. Registration of the LED 3. Registration of the LED pixel to the target pixel to the target

substratesubstrate

Pick-up Rod

LED

Pd-In

Adhesive 1

Target Substrate

4. Selective 4. Selective removal of the removal of the

pickpick--up rodup rod


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FLCC

Methodology

Primary Photo-Detector (PPD)

LEDθi

Reference Photo-Detector (RPD)

Dielectric Window

RRRP

Film to be grown/etched

A new function F is defined to eliminate non-measurable constants:

Errors due to misalignment of optical components and

Variation in the detector circuits, photo-detectors, and light intensity

F function depends on incident angle, wavelength, refractive index and thickness.

0 20 40 60 80 100 1200

50

100

150

200

250

PP

D re

adin

g (a

.u.)

RPD reading (a.u.)

Air (Slope=1.901+0.002) Water (Slope=1.552+0.001) P.R. (Slope=1.417+0.001)

0

0

0

0

)V/V()V/V()V/V(

F

RRRF

RP

RPRP

P

PP

δδδδδδ −

=

−≡


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FLCC

Calibration of the Prototype with a Plasma Etch Process of Silicon Oxide

0 20 40 60 80 100 120 140 160 180 200

-0.8

-0.6

-0.4

-0.2

0.0

0.2

F(θ)

Oxide Thickness (nm)

Experimental Fitted

*D.L. Windt, IMD Software.

The good fit between experimental data and calculation demonstrated that the methodology worked as expected.

As expected, effective incident angle, detection window thickness and even effective incident wavelength can be determined by a calibration process.

•n.a.•(1.464,0)*•(nf, kf)

•n.a.•(2.054,0)*•(nw, kw)

•649•650 ±7•dw (nm)

•56•n.a.•θi (°)

•n.a.•463 (peak)•λ (nm)

•Extracted•Measured


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FLCC

F as a function of incident angle at different refractive index

0 10 20 30 40 50 60 70 80 90

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

1.2

n=2.5, k=0n=2.2, k=0

n=1.9, k=0n=1.6, k=0

n=1.3, k=0

n=1.0, k=0F(θ)

Incident Angle (Degree)

Simulation Condition:Vacuum ambient, infinity thickness for thin film, nitride window thickness 649nm, LED peak wavelength 463nm.

F is a function of refractive index and incident angle.The effective incident angle can be precisely determined by

using media with tunable refractive index.



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Dependence of F function on incident wavelength (λ) and window thickness

Both wavelength and detecting window thickness have similar effects on the F function

10 nm change in detecting window thickness = 5 nm change in incident wavelength

Simulation Condition:Vacuum ambient, and incident angle of 60°, nitride window thickness, LED peak wavelength 463nm.

0 50 100 150 200 250

-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

λ=463nmdw=639nm

λ=463nmdw=659nm

λ=468nmdw=649nm

λ=458nmdw=649nm

λ=463nmdw=649nm

F(θ)

Oxide Thicknesss (nm)



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FLCC

Metal CMP Endpoint Detection Setup

0 20 40 60 80 100 120 140

-0.5

0.0

0.5

1.0

1.5

2.0

80Deg

70Deg

60Deg

50Deg

40DegF(θ)

Cu Thickness (nm)

Simulation Condition:Vacuum ambient, nitride window

thickness 649nm, LED peak wavelength 463nm, the

refractive index of Cu*: n=1.16,k=2.43.


Metrology wafer

Detection WindowData Acquisition System

Metal layer e.g. Cu

Polishing fixture

SlurryPolishing pad


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FLCC

Work in Progress and Proposed Work

– Evaluate and calibrate the stability of dielectric thickness monitoring.

– Demonstrate Metal etch endpoint and pre-endpoint (<50nm) detection and monitoring.

– Model and demonstrate monitoring of thin-film thickness roughness.

– Prototyping of wireless data acquisition/transmission and evaluate performance with measurements taken in processing systems.


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FLCC

Student(s): Jing Xue

Faculty: Costas Spanos

Title: Integrated Aerial Image Sensor (IAIS)

2005 FLCC Workshop


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Motivation

Mask

light

Image system

Wafer

Defocus

Lens aberration

Partial Coherence

Magnification

CD Uniformity

Aerial image

Latent image

Resist imageSensor

on equipment

Aerial Image Sensor


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FLCC

2005 Main Objective• Complete design of transducer capable of nm-scale aerial image

resolution

• Integrate prototype transducer for use and deployment on a silicon wafer

• Complete the micro-assembly of the commercial CCD with the Si carrier wafer; Integrate the aperture mask and the CCD arrays

• Complete the IAIS working prototype with front-illu. CCD, and test IAIS in GCAWS/ASML stepper in Berkeley Micro-lab

• Complete the aerial image and detector image reconstruction; Complete the over-topography simulation of the aberration part


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FLCC

Integrated Aerial Image Sensor (IAIS) Concept

High spatial frequency aerial image

Aperture mask transmission

Low spatial frequency detector signal

x

xPnm ∆+⋅+ )(


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FLCC

IASI Design – Aperture Mask

1 0 2 0 3 0 4 0 5 0 6 0

0 . 0

0 . 5

1 . 0

1 . 5

2 . 0

2 . 5

3 . 0

3 . 5

4 . 0

9 0 n m

7 0 n m5 0 n m

3 0 n m

1 0 n m

w i d t h ( n m )

• Aperture mask thickness in the range of 70nm & aperture mask width in the range of 30nm

Max & min intensity vs. aperture thickness and width

0 1 0 2 0 3 0 4 0 5 0 6 0

0 . 4

0 . 6

0 . 8

1 . 0

9 0 n m7 0 n m6 0 n m

3 0 n m

1 0 m n

w i d t h ( n m )

1 0 2 0 3 0 4 0 5 0 6 0 7 0

0 . 9 0

0 . 9 5

1 . 0 0

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

2 5 0 0

d e t e c t o r n o i s e m i n c u r r e n t

m a x c u r r e n t

cont

rast

w i d t h ( n m )

phot

ocur

rent

(pA)

0 2 0 4 0 6 0 8 0 1 0 0 1 2 0 1 4 00 .0

0 .2

0 .4

0 .6

0 .8

1 .0

cont

rast

w i d t h ( n m )

CDIC vs. aperture thickness and width


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FLCC

Summary of Aperture Mask Design for 130nm Periodic AI (65nm nodes)

mlnmt

nmw a

µ2070

30

===

nmNmn

x 521307

154

=∆===

mwPmW

nmPW

md

axd

i

mp

µ

µ

015.40)1(

130

1.3

=−∆++=

==

≤mW

mW

t

g

µ

µ

62.1218

92.19

=

=

wa

t

lWi

Wd

Wg

Wt

α - Si


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FLCC

IAIS Modeling• Aerial Image and Detector Image Reconstruction:

Detector Image

88 coherence groups

Annular Illumination: σ = 0.89/0.59 NA=0.85, PSM, CD = 65nmAerial Image


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FLCC

IAIS Modeling• Defocus Testing:

Dipole Illumination: σ = 0.3, NA= 0.78, Attenuated PSM, CD =90nm (a) Illumination discretizing ( 2 points illustration); (b) Aerial image intensity with defocus(c) Detector Image intensity with defocus; (d) Integrated intensity of detector Image vs. defocus

TM

TE

TM

TE

(a) (c)

(b)(d)


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IAIS Modeling

- 4 - 2 0 2 4 6

0 . 0

0 . 1

0 . 2

0 . 3

0 . 4

0 . 5

0 . 6

0 . 7

0 . 8

0 . 9

1 . 0A e r i a l Im a g e C o n t r a s t v s . D e f o c u s

Imag

e C

ontra

st

D e f o c u s (µ m )- 4 - 3 - 2 - 1 0 1 2 3 4 5

0 . 0

0 . 2

0 . 4

0 . 6

0 . 8

1 . 0

D e t e c t o r I m a g e C o n t r a s t v s . D e f o c u s

Imag

e C

ontr

ast

D e f o c u s

C o n t r a s t

- 4 - 3 - 2 - 1 0 1 2 3 4 55 0 %

1 0 0 %

1 5 0 %

2 0 0 %

2 5 0 %

3 0 0 %

A e r i a l i m a g e c o n t r a s t

Con

tras

t Cha

nge

D e f o c u s ( µ m )

C o n t r a s t C h a n g e v s . D e f o c u s

D e t e c t o r i m a g e c o n t r a s tC h a n g e =

Dipole Illumination: s = 0.3, NA= 0.78, Attenuated PSM, CD =90nmAperture mask: wa = 40nm, t = 90nm

• Defocus Testing (Focus vs. Contrast):

Aperture mask improve the contrast value as defocus, making the aberration detecting easy and meaningful


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FLCC

IAIS Assembly• Wafer Reconstituting:

Si Substrate SiO2

Polymer

CCD

ARC Dyed PMMA


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FLCC

IAIS Assembly• Flip-Chip Bonding:

Wire bonding pad on the CCD chip

Solder bump

Flip-chip Bonding

Si Substrate

SiO2

Amorphous Si

CCD chip


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FLCC

Student(s): Paul Friedberg, Willy Cheung

Faculty: Costas J. Spanos

Title: Modeling Gate Length Spatial Variation for Process/Design Co-Optimization

2005 FLCC Workshop


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FLCC

Motivation• Manufacturing-induced variation in device parameters leads to

variability in circuit performance• Two approaches to address this concern:

– Tailor IC design to minimize sensitivity to parameter variation– Use process control to reduce manufacturing variation

• Both approaches can be investigated through Monte Carlo analysis of canonical circuits– Various design styles can tested for susceptibility to variation– Hypothetical control scenarios can be mapped directly into circuit

performance space to determine robustness

• For accurate, useful predictions, Monte Carlo framework must model reality very well– Specific focus of this work: spatial variation effects (correlation)


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FLCC

2005 Main Objective• Milestone M30: Spatial CD Correlation in IC Design

• Extract within-die spatial variation components from dense gate length measurements (historical study)

• Investigate effects of spatial variation on circuit performance variability using Monte Carlo framework based on historical study results

• Design new test structures to explore mid-range (10-1000 micron) spatial variability

• Submit new test structures for manufacture; gather measurements from fabricated test structures


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FLCC

Departure Point: Spatial Correlation Calculation• Exhaustive ELM poly-CD measurements (280/field):

• Standardize each CD measurement, using wafer-wide distribution:

• For each spatial separation considered, calculate correlation r among all within-field pairs of points using:

( ) nzzr kjjk /*∑=

( ) σ/xxz ii −=

ELM data provided by Jason Cain, UC Berkeley


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FLCC

Spatial Correlation Results• Within-field correlation vs. horizontal/vertical distance,

evaluated for entire wafer:

• Shape of correlation curve is confounded by non-stationary (systematic) components of variation


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FLCC

Decomposition of Nonstationary Variation Components

• CD variation can be thought of as nested systematic variations about a true mean:

CDij = µ + fi + wj + σ

Across-field

Across-waferTrue mean

Random

Wafer

Field

Spatial components


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FLCC

WIF Systematic Variation Component• Within-field variation:

Average Field

Scan

Slit

Scaled Mask Errors Non-mask related across-field systematic variation

- =

Polynomial model of across-field

systematic variation

Removing this component of variation will simulate WIF

process control


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FLCC

AW Systematic Variation Component• Across-wafer variation:

- -

=

Average Wafer Scaled Mask Errors Across-Field Systematic Variation

Across-Wafer Systematic Variation

Polynomial Model

Removing this component of variation will simulate AW

process control


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FLCC

Die-to-Die Dose Control• One more round of control: die-to-die (D2D) dose control

-

=


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FLCC

Simulated Full Process Control• Removing WIF, AW, and D2D variation components:

• Large(mm)-scale spatial correlation is largely accounted for by systematic variation; smaller(µm)-scale correlation may still have structure, to be investigated in future work


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FLCC

Test Structure for Mid-Range CD Variation• 2x10 Probe frame: 100um x 100um pads, 150um pitch• Dense ELM base case test structure:


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FLCC

Variant ELM Submodules• Dummy lines used to extend measureable range, explore effects of pattern density and regularity


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FLCC

Student(s): Qiaolin(Charlie) Zhang

Faculty: Kameshwar Poolla, Costas Spanos

Title: CD Uniformity Control Across Litho-etch Sequence

2005 FLCC Workshop


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FLCC

Motivation• Across-wafer CD uniformity (CDU) is critical for

– Advanced logic devices, MPU and memory– Yield improvement

• Etch tool sets have limited control authority to address spatialnon-uniformity– Dual-zone He chuck is often the only knob

• Litho tool sets have much more control authority to address spatial non-uniformity– Multi-zone PEB bake plate– Variable dose settings at exposure


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FLCC

2005 Main Objectives

Build process models for PEB step: (done) CD offset model & temperature offset model

Assess potential DI & FI CDU improvement (done) Based on CD offset model Based on temperature offset model

Expand CDU control concept to simultaneous CDU control for multiple CD targets (new)

Experimentally extract baseline CD signature of dense, iso and semi-iso CD targetsFormulate simultaneous CDU control as a minimax optimization problem

• Experimentally verify DI & FI CDU improvement using our approach(ongoing)


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FLCC

The Problem

How can we improve the across-wafer CDU ?

Poor Across-Wafer CD Uniformity

Processing Tool

EtchEtch

Wafer

LithoLitho


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FLCC

Our Approach• Compensate for systematic across-wafer CD variation sources across the

litho-etch sequence using all available control authority :– Exposure step: die to die dose– PEB step: temperature of multi-zone bake plate– Etch: backside pressure of dual-zone He chuck

Exposure PEB /Develop Etch

Wafer-levelCD MetrologyOptimizer

Scatterometry/CDSEM

dose temperature He pressure


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FLCC

Multi-zone PEB Bake Plate

• PEB step is critical due to chemically amplified resist

• Spatially programmable bake plate is introduced into PEB to enable PEB temperature uniformity

Schematic setup of multi-zone bake plate

(approximate)

24

36

5 71


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FLCC

Develop Inspection (DI) CDU Control• DI CD is a function of zone offsets

baselineresistDI CDSTCD→→→

+∆=

( )

( )⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=

→

721

72111

...,...

...,...

OOOg

OOOg

T

TT

mm

baselineTTT→→→

−=∆

( )

( )⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=

→

721

72111

...,...

...,...

OOOf

OOOf

CD

CDCD

nn

DI

• Seen as a constrained nonlinear programming problem

• Minimize• Subject to: Up

iLow OOO ≤≤

2argettDI CDCD −

7...2,1=i


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FLCC

Simulation Results of DI CDU Control

69%61%72%CDU Improvement

Isolated LineSemi-isolated LineDense Line

Dense Line Semi-isolated Line Isolated Line

Experimentally extracted baseline

DI CDU

Simulated optimal DI CDU after applying PEB

tuning


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FLCC

Final Inspection (FI) CDU Control• Across-wafer FI CD is

function of zone offsets

• Minimize:

DIFIsp CDCDCD→→∆→

−=∆ _

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡=∆+=

→→→

)...,(...

)...,(

721

7211

_

OOOg

OOOgCDCDCD

n

spDIFI

• Plasma etch signature:

Upi

Low OOO ≤≤• Subject to: 7...2,1=i

Assumed bowl shape plasma etch signature

2argettFI CDCD −


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FLCC

FI CDU Control Simulation - Bowl Plasma SignatureDense Semi-isolated Isolated

Simulated baseline FI CD

Simulated corrected DI CD after PEB

tuning

Simulated optimal FI CD after PEB tuning

65%57%68%FI CDU Improvement

IsolatedSemi-isolated Dense

Note that DI CDU may actually worsen!


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FLCC

Simultaneous CDU Control for Multiple CD Targets

)))((max(minarg OFWO iiiO

opt =

2_ iii TCDCDF −=

• It is good to have simultaneous CDU control for multiple CD targets

• Formulated as a minimax optimization problem

Minimax finds optimal offsets

Wi is the weighting factor for CD target i


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FLCC

Simultaneous CDU Control for Multiple CD Targets

62.6%32.4%60.1%Wd = 0.05; Ws =0.05 ; Wi =0.9054.1%54.7%48.2%Wd = 0.05; Ws =0.90 ; Wi =0.0561.8%15.9%66.8%Wd = 0.90; Ws =0.05 ; Wi =0.0558.4%44.7%62.9% Wd =0.36; Ws =0.33 ; Wi =0.31

Iso LineSemi-iso LineDense Line

Simulation of simultaneous CDU control for dense, semi-iso and iso lines

Dense Semi-isolated Isolated

Simulated baseline FI CD

Simulated optimal FI CD after PEB tuning


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FLCC

Future Milestones (Year 3)• Zero-footprint Optical Metrology Wafer (SENS Y3.1)

Modeling and demonstration of metrology wafer for detection and thin-film roughness monitoring. Initiate prototyping of wireless data acquisition/transmission and evaluate performance with measurements made in experimental systems.

• Complete experimental study for CD non-uniformity reducing across the litho-etch sequence (SENS Y3.2) Experimentally verify DI & FI CDU improvement using model based optimal control of PEB with various CD objective functions.

• Using Spatial CD Correlation in IC Design (SENS Y3.3) Perform spatial variation analysis and incorporate results into Monte Carlo framework. Evaluate impact of updated variation/correlation models on circuit performance variability using Monte Carlo Framework.

• Aerial Image Metrology (SENS Y3.4) Complete the micro-assembly of the commercial CCD with the Si carrier wafer. Integrate the aperture mask and the CCD arrays.


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FLCC

Future Milestones (Year 4)• Integrated sensor platform development 4 (M54)

Incorporate optical spectroscopy capability with optical filters integration.• Final phase of CD uniformity control project (M55)

Complete study of feed-forward and feedback based schemes for process/equipment control to enhance feature level pattern transfer. Study various control architectures in terms of sensor integration, implementation cost, and expected benefit.

• Real time feature-level test structures (M58)Develop feature-level test structures that can be monitored for real-time insight in their evolution. Examples include real-time etch-rate monitors that are subject to micro-loading.

Sensors and Control - University of California, San Diego

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