8:30 – 9:00 Research and Educational Objectives / Spanos

9:00 – 9:50 Plasma, Diffusion / Graves, Lieberman, Cheung, Haller

9:50 – 10:10 break10:10 – 11:00 Lithography / Spanos, Neureuther, Bokor 11:00 – 11:50 Sensors & Metrology / Aydil, Poolla, Smith, Dunn

12:00 – 1:00 lunch 1:00 – 1:50 CMP / 1:00 – 1:50 CMP / Dornfeld, Talbot, SpanosDornfeld, Talbot, Spanos

1:50 – 2:40 Integration and Control / Poolla, Spanos

2:40 – 4:30 Poster Session and Discussion, 411, 611, 651 Soda 3:30 – 4:30 Steering Committee Meeting in room 373 Soda 4:30 – 5:30 Feedback Session

3rd Annual SFR Workshop, November 8, 2000

11/8/2000

2

Chemical Mechanical Planarization

SFR Workshop

November 8, 2000

Andrew Chang, Tiger Chang, David Dornfeld, Tanuja Gopal, Edward I. Hwang, Jianfeng Luo, Zhoujie Mao, Costas Spanos,

Jan Talbot

Berkeley, CA

11/8/2000

3

CMP Milestones

• September 30th, 2001– Build integrated CMP model for basic mechanical and chemical

elements. Develop periodic grating metrology (Dornfeld, Talbot, Spanos).

• September 30th, 2002– Integrate initial chemical models into basic CMP model. Validate

predicted pattern development. (Dornfeld, Talbot) .

• September 30th, 2003– Develop comprehensive chemical and mechanical model. Perform

experimental and metrological validation. (Dornfeld, Talbot, Spanos)

11/8/2000

4

Abstract2001 Milestone: Build integrated CMP model for basic

mechanical and chemical elements. Develop periodic grating metrology

Key elements involved in this are:– Chemical Aspects of CMP (J. Talbot and T.Gopal)– Particle Size Distribution in CMP: Modeling and Verification (J.

Luo) – Slurry Flow Analysis and Integrated CMP Model (Z. Mao)– Scratch Testing of Silicon Wafers for Surface Characterization (E.

Hwang)– Process Monitoring of CMP using Acoustic Emission (A. Chang)– Development of periodic grating metrology (C. Spanos and T.

Chang)

We will review the recent activities in these areas

11/8/2000

5

OverviewModel Structure & Development Basic

Process Mechanism

Model Validation

Metrology, Process Control, &

OptimizationChem Mech

Chemical Aspects (JT/TG)

X X X

Particle Size Distribution (JL)

X X X

Slurry Flow (ZM) X X XSurface Effects (EH) XProcess Monitoring (AC)

X X

Grating Metrology (CS/TC)

X

Process control(KP) X

11/8/2000

6

Contact Pressure

ModelModel of

Active Abrasive

Number N

Model of Material

Removal VOL

by a Single Abrasive

Physical Mechanism; MRR: N´VOL

Slurry Concentration,

Abrasive Shape, Density,

Size and Distribution

Slurry Chemicals

Chemical Reaction

Model (RR0)chem

Pad Roughness

Pad Hardness

Wafer, Pattern,Pad and

Polishing Head Geometry

and Material

Pressure and Velocity

Distribution Model

(FEA and Dynamics)

Down Pressure

Relative Velocity

Wafer Hardness

Dishing &

Erosion

Preston’s Coefficient Ke (RR0 )mech

WIWNUSurface

Damage WIDNU

WIWNU

MRR

Fluid Model

Overview of Integrated Model

11/8/2000

7

Chemical Aspects of CMP Role of Chemistry - Tanuja Gopal, Jan Talbot UCSD

• Chemical and electrochemical reactions between material (metal, glass) and constituents of the slurry (oxidizers, complexing agents, pH) – Dissolution and passivation

• Solubility• Adsorption of dissolved species on the abrasive

particles• Colloidal effects• Change of mechanical properties by diffusion &

reaction of surface

11/8/2000

8

Mass Transfer Processes• (a) movement of solvent

into the surface layer under load imposed by abrasive particle

• (b) surface dissolution under load

• (c) adsorption of dissolution products onto abrasive particle surface

• (d) re-adsorption of dissolution products

• (e) surface dissolution without a load

Ref. L. M. Cook, J. Non-Crystalline Solids, 120, 152 (1990).

11/8/2000

9

Reaction Chemistries

• Dissolution of glass

(SiO2)x + 2H2O = (SiO2 )x-1 + Si(OH)4R+(glass) + H2O = H+(glass) + ROH

W + 6Fe(CN)6-3 + 4H2O WO4

-2 + 6Fe(CN)6-4 + 8H+

W + 6Fe(CN)6-3 + 3H2O WO3 + 6Fe(CN)6

-4 + 6H+

• Dissolution and passivation of W

11/8/2000

10

Generic Chemical Reactions

• Dissolution: M(s) + A > M(aq) + B M(s) + A > Mn+ + ne-

+ B

• Oxidation: M(s) + O >M-oxide(s)

• Oxide dissolution: M-oxide(s) + A > M(aq) + B

M-oxide(s) + A > Mn+ + ne- + B• Complexation (to enhance solubility)

11/8/2000

11

Colloidal Effects

• Surface charge (zeta potential or isoelectric point, IEP, the pH where the surface charge is

neutral) of polished surface and abrasive particle is important

(Malik et al.)

11/8/2000

12

Colloidal effects

• Maximum polishing rates for glass observed compound IEP ~ solution pH > surface IEP(Cook, 1990)

• Polishing rate dependent upon colloidal particle - W in KIO3 slurries (Stein et al., J. Electrochem. Soc. 1999)

11/8/2000

13

Experimental Program

• Electrochemical/chemical experiments with rotating disk electrode with and without abrasion

• Measurement of zeta potential of abrasives as function of pH (IEP) and solution chemistry

RDE

CounterElectrode

Reference Electrode

Polishing Pad

Potentiostat

11/8/2000

14

Modeling of Chemical Effects

• Electrochemical/chemical dissolution and passivation of surface constituents

• Colloidal effects (adsorption of dissolved surface to particles or re-adsorption)

• Solubility changes • Change of mechanical properties (hardness, stress)

11/8/2000

15

Contact Pressure

ModelModel of

Active Abrasive

Number N

Model of Material

Removal VOL

by a Single Abrasive

Physical Mechanism; MRR: N´VOL

Slurry Concentration,

Abrasive Shape, Density,

Size and Distribution

Slurry Chemicals

Chemical Reaction

Model (RR0)chem

Pad Roughness

Pad Hardness

Wafer, Pattern,Pad and

Polishing Head Geometry

and Material

Pressure and Velocity

Distribution Model

(FEA and Dynamics)

Down Pressure

Relative Velocity

Wafer Hardness

Dishing &

Erosion

Preston’s Coefficient Ke (RR0 )mech

WIWNUSurface

Damage WIDNU

WIWNU

MRR

Fluid Model

11/8/2000

16

Synergistic Effects

• MRR = kchem (RRmech)o + kmech (RRchem)o

(RRmech)o = mechanical wear = Ke PV (RRchem)o = chem. dissolution = kr exp(-E/RT)Ci

n

Ke affected by surface chemical modification Ci affected by mass transport (i.e., V)

Ref.: Y. Gokis & R. Kistler, ECS Meeting Abstract 496, Phoenix, Oct. 2000.

11/8/2000

17

Potential Results for Chemical MP Modeling

• Selective chemical slurries:1) control reaction chemistry 2) control colloidal properties of abrasives and removed material3) enhance solubility of removed material

• Material wear properties (eg, hardness)

• Chemically active pads

11/8/2000

18

Chemical Effects of CMP

• Synergistically enhances the rate of material removal with mechanical polishing

• Influences the colloidal stability of the abrasive particles

• Undesired effects are unwanted etching and dishing of features and increased surface roughness

DishingErosion

11/8/2000

19

Effect of Particle Size Distribution in CMP Modeling Abrasive Geometry and Size - J. Luo UCB

Two Abrasive Geometries

• Spherical Shape for Obtuse Abrasives• Conical Shape for Sharp Abrasives

0

10

20

30

40

50

60

-8 -6 -4 -2 0 2 4 6 8

Xavg

y

        

   

   

SEM Picture of Slurry Abrasives for Si CMP (Moon, PhD Thesis, 1999)

Abrasive Size and Size Distribution

• Nano-Scale Size X• Normal Distribution (Xavg , ) and p((Xavg , )

• Xavg, Xmax and Standard Deviation

Schematic of Spherical and Conical Abrasive Shapes in the Model

X

100nm

Schematic of Abrasive Size Distribution

X

Portion of Active Abrasive

Xmax

11/8/2000

20

V = Vol

a12= F2/Hw

1

Chemical Reaction

Schematic of Wafer-Chemical-Abrasive-Pad Interaction to

Model the Volume Removed by A Single Abrasive

Contact Mechanics( Pad Topography/Abrasive Size/Pressure )

Ab

rasi

ve

Ge

om

etr

y

a22= F2/Hp

Xmax-Y=2

Abrasive Geometry

Pad Hardness

Schematic of Wafer-Abrasive-Pad Interaction to Model the Number of Active Abrasive Number

Contact Mechanics( Pad Topography/Abrasive Size/Pressure )

Ab

rasi

ve S

ize

D

istr

ibu

tion N

Material Removal Rate Function:MRR= N Vol= C1Hw

-3/2 {1-(1-

C2P01/3}P0

1/2V. Correct on both average scale &

local single points

Role of Abrasive Size in the Architecture of the Integrated CMP

Model

Detailed Fluid Model

?

-40-30

-20-10

010

2030

40

-7000-6000-5000

-4000

-3000

-2000

-1000

0

1000

2000

3000

4000

5000

6000

7000

8000

-40

-30-20

-100

1020

3040

Z A

xis

(A)

Y Axis

(mm

)

X Axis (mm)

Pressure and velocity distribution over wafer-

scale

Pattern Density

Surface Damage

Slurry pH Value and so on

WIWNU

WIDNUn

11/8/2000

21

MRR As A Function of Particle Size Distribution Before Saturation (Luo & Dornfeld, 2000)

2

4

4

433

33

33

331

avg

avg

avgavg

avgX

C

XCp

XX

CX

C

Contribution of Active Particle

Number

Contribution of Total Number of Particles over the

Wafer-Pad Interface

MRR=MRR as A Function of Down Pressure and Velocity: MRR= N Vol= C1Hw

-3/2 {1-(1-C2P01/3}P0

1/2V.

MRR as A Function of Particle Size and Size Distribution

C3: A Function of Down Pressure, Velocity, Weight Concentration etc.C4: 0.25(4/3)2/3(1/Hp)Ep

2/3/b1P01/3 A

Function of Down Pressure, Pad Hardness and Pad Topography.

Function p: The probability of the appearance of abrasive sizeFunction : Probability density function.

Contribution of Active Particle

Size (Larger than Xavg)

11/8/2000

22

Particle Size Distribution Measurement (II)

Dynamical Light Scattering

0.2887680.88AA07

0.2106330.60AKP15

1.0561972.00AA2

0.1189590.38AKP30

0.0702220.29AKP50

Standard Deviation (m)

Mean Size (m)

*Bielmann et. al. 1999

11/8/2000

23

y = 325.1x-0.6411

y = 314.77x-0.6695

0

100

200

300

400

500

600

700

800

0 0.5 1 1.5 2 2.5

Particle Size (10-6m)

Mate

rial R

em

oval R

ate

(nm

/min

)

Experimental Mean MRR

Prediction of the Model

Power (Experimental Mean MRR)

Power (Prediction of the Model)

Particle Size Dependence on MRR: Experiment VS. Model Predictions

C4: 0.25(4/3)2/3(1/Hp)Ep2/3/b1P0

1/3= 0.015

(0.29, 0.07022)

(0.38, 0.118959)

(0.60, 0.210633)

(0.88, 0.288768)

(2.0, 1.056197)

* Bielmann et. al. 1999

11/8/2000

24

Fraction of Active Particles Based on Model Prediction

[0.726, 0.737m] 0.1827%

[1.213, 1.231m] 0.1798%

[1.720, 1.746m] 0.1815%

[5.091, 5.169m] 0.1719%

[0.49, 0.50m] 0.19105%

11/8/2000

25

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 0.05 0.1 0.15 0.2 0.25 0.3

Standard Deviation (10-6m)

Nor

mal

ized

Mat

eria

l R

emov

al R

ate Xavg= 0.29um

Xavg=0.38um

Xavg=0.60um

Xavg=0.88um

Xavg=2um

Relationship between Standard Deviation and MRR Based on Model Prediction

Size Dominant Region

Number Dominant Region

11/8/2000

26

Wafer

Down Pressure

H

H

a

Smaller contact area

Larger contact area

   

2002 & 2003 GoalsDevelop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003.

11/8/2000

27

Slurry Flow Analysis and Integrated CMP Model Zhoujie Mao UCB

Motivation

• Study the effects of slurry flow on the material removal in CMP

• Develop integrated process model for CMP to provide insight into the MRR and WIWNU

• Develop process model for environmental impact analysis for CMP

11/8/2000

28

Overall Picture of Slurry Flow in CMP

Side view

Polishing plate

Polishing pad

Wafer

Carrier film

Carrier Slurry Slurry feeder

• Two flow stages: slurry flow on the polishing pad, slurry flow between wafer and polishing pad

11/8/2000

29

Slurry Flow on the pad

Polishing pad

Slurry

Abrasive particle

• Estimate the abrasive particle settling mechanism on the polishing pad

• Study the effects of slurry supply rate and slurry delivery position on the material removal rate

11/8/2000

30

Abrasive Particle Settling Rate Vs. Slurry Supply Rate

0 20 40 60 80 100 120 140 160 180 2000

1

2

3

4

5

6

7

8x 10

15

Radius (mm)

Ra

te o

f d

ep

os

itio

n (

n/m2 /s

ec

)

Q=50ml/min Q=100ml/minQ=150ml/min

Radius (mm)

Rat

e of

Dep

osit

ion

(n/m

2 /s)

11/8/2000

31

Abrasive Particle Settling Rate Vs. Delivery Position

100 120 140 160 180 200 220 240 260 280 3001

2

3

4

5

6

7

8x 10

16 Average Settling Rate Underneath Wafer

Raidial Position (mm)

Av

era

ge

Se

ttlin

g R

ate

(n

/m2 /s)

e=0mm e=100mme=200mm

Eccentricity

Average Settling Rate Beneath Wafer

Ave

rage

Set

tlin

g R

ate

(n/m

2 /s)

Radial Position (mm)

11/8/2000

32

Integrated Slurry Flow Model

• Slurry flow between wafer and polishing pad• Slurry flow inside polishing pad• Deformation of wafer• Deformation of polishing pad

h(x)

Pad

hp(x)

11/8/2000

33

2002 & 2003 Goals

Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003.

•Simulation of Integrated CMP model

•Experimental verification of integrated CMP model (role of active abrasives in mechanical material removal)

11/8/2000

34

Scratch Testing of Silicon Wafers for Surface Characterization

Edward Hwang UCB

Motivation

• Wafer surface characterization is important to understand and model the material removal mechanism in CMP

- Scratch testing supports the identification and verification of surface characteristics of the wafer representative of the CMP process

- Scratch testing can give insight on the stress levels occurring during the CMP Process

11/8/2000

35

Actual CMP Situations

Cross Section View

polishing pad

Si wafer

bulk

not affected by the process

layer 1(order of a few nm )

highly hydrated, loosely bound network

– lower densityTrogolo et al “Near Surface Modification of Silica Structure Induced by Chemical/Mechanical Polishing”, J. Materials Science 29 (1994) pp. 4554 - 4558

layer 2(order of 20 nm )

plastically compressed network

– higher density

11/8/2000

36

Experimental Setup

•Workpiece: Silicon wafer <100> p-typePre-CMP Wafers & Post-CMP Wafers

• Diamond tool: Nose radius: 48μm• Feed rate: V=399μm/s• Tilt angles: 0.06 degrees.• Acoustic emission sensor: DECI Pico-Z AE sensor• Data collection: 50kHz sampling rate

11/8/2000

37

Layers vs. AE Signals (1)

Pre-CMP Wafers

0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

AE

sig

nal

s (v

olt

s)

time(s)

AE signals are proportional to the depth of cut in

11/8/2000

38

Layers vs. AE Signals (2)

Post-CMP Wafers

0.35

0.00 0.05 0.10 0.15 0.20 0.25 0.30-1.0

-0.8

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

time(s)

AE

Raw

Sig

nal

s (v

olt

s)

Air-cut + Layer 1

Layer 2 Bulk

Unlike the pre-CMP wafers, post-CMP wafers show discontinuous transitions in the AE signal due to penetration of Layer 2.

11/8/2000

39

Results

• Observation of distinct signal changes for transitions between Layer 1 Layer 2 bulk supports surface characterization

• Signal for Layer 2 is observed up to 20 nm depth of cut• Highly compressed Layer 2 is more ductile than bulk :

- Plastic deformation dominates the material removal mechanism in this regime and should relate to removal rate during CMP

• SEM images support the verification of the multi-layered wafer surface

11/8/2000

40

2002 & 2003 Goals

• Replicate the scratch testing with AFM machine in order to be closer to actual CMP situations

• Quantify the wafer surface characteristics in CMP

Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003.

11/8/2000

41

Process Monitoring of CMP using Acoustic EmissionAndrew Chang UCB

Motivation

• AE monitoring is an applicable diagnostic tool for studying abrasive interaction during CMP

• Experimental verification for abrasive particle interaction is needed for CMP modeling

• Alternative sensing methods are in-direct (motor current, pad temperature, etc.) or limited to localized areas of the wafer

11/8/2000

42

Acoustic Emission Sources in CMP

• Acoustic emission is highly sensitive to abrasive particle interaction between wafer and pad

11/8/2000

43

Experimental Setup

PC Data Acquisition Pre-amplifier(60 dB)

Amplifier(40 dB)RMS Filter

Raw Sampling Rate = 2 MHzRMS Sampling Rate = 5 kHz

RMS AE

Raw AEAE Transducer

Wafer

Pressure = ~ 1 psiTable Speed = 20 – 80 RPMSlurry flowrate = 150 ml/min

Polishing Conditions

IC 1000/Suba IV stacked padPad type

ILD 1300, abrasive size (~100 nm)W-Slurry, abrasive size (~37 nm)Alumina slurry, abrasive size (~100 nm)

Slurry type

Oxide, aluminum, tungsten, copper blanket wafersTest Wafers

Toyoda Float Polishing MachineCMP Tool

11/8/2000

44

AE Ratio Signal ProcessingHFpeak

t

ASL

LFpeak

t

High Pass Filter>100 kHz

Ratio = HFpeak

LFpeakLow Pass Filter20-60 kHz

ASL

Raw AE Signal

AE Ratio for Oxide Wafer

0.5

0.7

0.9

1.1

1.3

1.5

1.7

0 20 40 60 80 100Table RPM

HF

/LF

Rat

io

Oxide-DIW

Oxide-Slurry

11/8/2000

45

AE Signal for Varied Materials

High Frequency Average Signal Level during CMP Polishing

0

1000

2000

3000

4000

0 20 40 60 80 100

Table RPM

AE

AS

L (

mV

)

BackgroundNoise

Oxide

Aluminum

Tungsten

Copper

11/8/2000

46

AE Ratio for Oxide Polishing

0.35

0.4

0.45

0.5

0.55

0.6

0.65

0 50 100 150 200

Time (sec)

AE

Ra

tio

Oxide begins to clear

Oxide cleared

Application to Endpoint Detection• The sensitivity of acoustic emission to various materials

during polishing is ideal for endpoint detection in CMP

Oxide Wafer

Pad

Pad

Pad

11/8/2000

47

Sensitivity to CMP Process

• Background noise characterization• AE is insensitive to low-frequency (audible) noise from CMP

tool (motors, belts, etc.)

• Sensor location (backside of wafer is ideal) isolates signal from process and filters noise

• Signal from process is sensitive to abrasive particle interaction

• Signal comparison between deionized water and abrasive slurry

• Sensitivity to different materials

11/8/2000

48

2002 & 2003 Goals

Develop comprehensive chemical and mechanical model. Perform experimental and metrological validation, by 9/30/2003.

•Future tests planned with industrial CMP tool manufacturer

•Further experimental tests for validation of integrated CMP model (role of active abrasives in mechanical material removal)

11/8/2000

49

Pattern density mask - MIT 96.4

Feature size 10 mDie size 20mm by 20mmPattern density ranges from 4% to 100%

Establishing full-profile metrology for CMP modelingCostas Spanos & Tiger Chang UCB

11/8/2000

50

Process Flow

The final structure

Get the mask files

Design contact mask

Make emulsion mask

Aluminum 0.7 m

PECVD oxide ~2m

CMP

PSG deposition 1 m

Pattern Aluminum

11/8/2000

51

Results of Experiment (typical)

0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 13000

3500

4000

4500

5000

5500

6000

6500

7000

effective Pattern Density

Oxi

de

Re

mo

val R

ate

A/3

min

ute

sWafer #2 r=0.9807 PL=2.450mm

The characteristic length is about 2~3mm; this motivates a new mask design

11/8/2000

52

New Mask Design

• The size of the metrology cell is 250m by 250m

• 2m pitch with 50% pattern density

11/8/2000

53

Key ideas

SubstrateOxide

• Use Scatterometry to monitor the profile evolution• The results can be used for better CMP modeling

11/8/2000

54

Current status

• Done mask design and processing in the Lab, 12 wafers are ready to polish

• Before the characterization experiments, we want to know – Is the scatterometer signal sensitive enough for the profile

evolution?• Simulated a conceptual profile evolution

– How does the initial profile look like?• LEO can give a cross section SEM view (we need to cut the

wafer, then can’t do CMP on this wafer anymore!)

• AFM can give a smooth profile (it needs reliable de-convolution)

11/8/2000

55

CMP Profile evolution used in GTK simulation

0 500 1000 1500 20000

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5Profile Evolution during CMP

Oxide (nm)

pro

file

(m

icro

n)

11/8/2000

56

GTK Metrology Simulation Results

• We simulated 1 m feature size, 2 m pitch and 500nm initial step height, as it polishes.

• The simulation shows that the response difference was fairly strong and detectable.

Tan PSI Response to Profile Evolution

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

240

280

320

360

400

440

480

520

560

600

640

680

720

760

Wavelength(nm)

tan

PS

I

tan PSI 500nm

tan PSI 400nm

tan PSI 300nm

tan PSI 200nm

tan PSI 100nm

tan PSI Flat Surface

Cos DEL Response to Profile Evolution

-1.5

-1

-0.5

0

0.5

1

1.5

240

280

320

360

400

440

480

520

560

600

640

680

720

760

Wavelength(nm)

cos

DE

L

cos DEL 500nm

cos DEL 400nm

cos DEL 300nm

cos DEL 200nm

cos DEL 100nm

cos DEL Flat Surface

11/8/2000

57

Profiles before polishing (LEO)

11/8/2000

58

Immediate Metrology Objectives

• Do measurements using Sopra for the initial structures, compare results with the AFM measurements

• Build a pseudo response library• Design experiments, polish finished wafers and do

scatterometry measurements• AFM measurements at AMD, refine the library

11/8/2000

59

Conclusions

• Chemical effects model and synergy with mechanical effects being developed

• Integrated model validated for abrasive size and activity• Fluid modeling of particle behavior corroborates abrasive

activity• Extent and behavior of surface modified layer being

characterized• Sensing system for process monitoring and basic process

studies being validated• Scatterometry metrology sensitivity study indicates suitability

for observing profile evolution