1

Colloidal Aspects of Chemical Mechanical Polishing (CMP)

Tanuja Gopal & Jan Talbot

Chemical Engineering Program

University of California, San Diego

May 10, 2004

2

Outline

Introduction

Background & Motivation

Research Approach

Experimental Results

Conclusions

Future Work

3

What is CMP?

Unplanarized

Surface smoothing

Localplanarization

Globalplanarization

Ref.: Steigerwald, J. M., Murarka, S. P. and R. Gutmann, Chemical Mechanical Planarization of Microelectronic Materials, Wiley and Sons, New York (1997).

CMP is a method through synergistic effects of chemical and mechanical forces to achieve local and global planarization of Integrated Circuit (IC) structures.

4

CMP Applications

Oxide CMP

Metal CMP

Barrier Layer DepositionPatterning Dielectric

Blanket Metalization After CMP

Cu

SiO2

CMP

Ta

Si Si

CMPSiO2

5

CMP Schematic

slurry

wafer polishing pad

platen head

polishing pad

wafer

slurry

wafer carrier

P = 1.5-13 psi

(100-300 ml/min)V= 20-60 rpm

(polyurethane)

6

CMP Parameters

Process Variables Wafer down pressure Wafer velocity Pad characteristics Particle characteristics Slurry chemistry Substrate characteristics

Process Results Material Removal Rate Planarization Surface finish

7

Typical Process Conditions

Wafer Wafer rotational speed = 20 - 60 rpm Applied pressure = 1.5-13 psi

Slurry Flow rate = 100 - 300 ml per min Particle type = silica, alumina, ceria, titania, etc. Particle concentration = 1 - 30 % by weight Particle size = 50 - 1000 nm diameter

Removal Rate SiO2 = 200 - 300 nm per minute Cu or W = 300 - 600 nm per minute Planarization time = 1- 3 min RMS roughness = < 1 nm

8

Mass Transfer Process

(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 (f) dissolution products washed away or dissolved

Surface

Dissolution products

Abrasive particle

Surface dissolution

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

9

CMP Defects

Surface Particle Embedded

ParticleRipout Residual

Slurry Micro-scatch

Dishing

Ref.: Philipossian et al. (2001)

10

Why CMP ?

Multi-material surfaces

Global planarization 200 and 300 mm (8 and 12 inch) wafers ICs have feature sizes <0.2 m RMS roughness: < 1nm

Disadvantages Large water consumption CMP defects End point detection

11

Motivation for Research

Fundamental understanding of chemical effects in CMP Role of slurry chemistry not understood (additives, ionic

strength, pH) Optimize slurries -high removal rates w/ adequate planarity Reduce consumables (slurries are expensive, mostly not

recycled) Enhance post CMP cleaning – large water usage Focus on Copper CMP – Cu interconnect of choice

Lack of comprehensive CMP model Lou and Dornfeld CMP mechanical model- add colloidal effects

12

Research Approach

Experimental study of colloidal behavior of CMP slurries Zeta potential and particle size distribution measurements

Function of pH, ionic strength, additives Commercial alumina slurries Alumina – no additives Alumina in presence of common Cu CMP additives Agglomeration during CMP

Incorporate colloidal chemistry into existing mechanical model by Lou and Dornfeld Average particle size, standard deviation parameters Comparison to literature material removal rates

13

Cu CMP Chemical Reactions

Dissolution:Cu(s) + HL CuL+(aq) + H+ + e Oxidation:2Cu + H2O Cu2O + 2H+ + 2e

Oxide dissolution: Cu2O + 3H2O 2CuO2

2- + 6H+ + 2e

Complexation (to enhance solubility)Cu2+ + HL CuL+ + H+

Cu

CuO, Cu2O, CuL2

CuL+, Cu2+, Cu+

14

Pourbaix Diagrams

Pourbaix diagrams-predicts stable phases in aqueous systems at equilibrium

copper-water system, [CuT]=10-5M

Ref.: Aksu and Doyle (2002)

copper-water-glycine system, [LT]=10-1M [CuT]=10-5M

15

Colloidal Aspects of CMP

1) Particle – particle

2) Particle – surface

3) Particle – dissolution product

4) Surface – dissolution product

Surface

Abrasive particleDissolution product

Interaction forces influence particle stability, aggregation,deposition

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Electrical Double Layer

+ +

++

+

+ + +++

+

++

++

+

+

+

+

+

+

a

+

+

+

Distance

Pote

ntia

l

1/

Diffuse Layer

Shear Plane

Particle Surface

2/122000⎟⎟⎠

⎞⎜⎜⎝

⎛=

RTIF

roεε

∑=i

ii zcI 2

2

1

εη /u=

EVu /=•Potential at surface usually stems from adsorption of lattice ions, H+ or OH-

•Potential is highly sensitive to chemistry of slurry

•Slurries are stable when all particles carry same charge; electrical repulsion overcomes Van der Waals attractive forces

•Agglomeration may occur for || < 5mV.

17

Measurement of Zeta PotentialEYEPIECE

PRISM

MICROSCOPE

calculated using Smoluchowski eqn:

(valid for a >>1)

= vη/εE

Particle velocity measured through microscope using rotating prism technique

•Pen Kem Lazer Zee Meter•accuracy = ± 5mV

• Brookhaven ZetaPlus•accuracy = ± 2%•particle size-light scattering

||≥ 30 mV: stable

|| < 5 mV: agglomeration

18

Background – Colloidal Effects

Zeta potential and iso-electric point (IEP, pH where surface charge is neutral) of polished surface and abrasive particle is important

Ref.:Malik et al. (1997)

-100

-80

-60

-40

-20

0

20

40

1 2 3 4 5 6 7 8 9 10

Al2O3

SiO2

W

Polishing Regime

pH

Zet

a P

oten

tial

(m

V)

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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)

Pol

ish

ing

rate

(

/min

)

Colloid oxide

Gla

ss p

olis

hin

g ra

te (m

/min

)

Oxide Isoelectric point

20

Agglomeration

Agglomeration process of the slurry versus pH, additive concentration, and ion concentration

(Bellman et al., 2002)

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Removal Rate in CMP

Preston’s Equation - most widely used model in CMP: MRR = K*V*P – MRR = Material removal rate

– K = Preston constant– P = Pressure in the wafer- pad space– V = Linear pad- wafer velocity

Drawbacks of Preston’s Eqn: Does not take into account

chemical synergistic effects Fails to provide insight into the

interaction process (particle size, concentration, pad variables etc.)

Ref.: Luo and Dornfeld (1998)

22

Model Review

Mechanical Models:•Boning (2001)

•Parameters:P,V, pattern density, step height•Discretize the chip to create a P profile then use Preston’s Eqn. to calculate removal rate.

•Dornfeld (2001)•Parameters: P, V, pad hardness, pad roughness, abrasive size, abrasive geometry, wafer hardness•MRR = w N Vol

w = density of wafer•N = number of active abrasives•Vol = volume removed by single abrasive

23

Model Review

Chemical Models:•Stein model (1999) : MRR = k’PV/(1+k”PV)

•Main variables: type of colloidal species and concentration•Chemistry, particle size, P, V constant•Found that MRR and temperature were functions of colloid species concentration

•Subramanian model (1999): mass transport model•Chemical removal of material coupled with mass transport•MRR lower than observed rates because excludes mechanical action

•Gutman (2000): MRR = k’[O]/(1+k”[O])•Main variable: Oxidizer concentration•MRR increases with oxidizer concentration upto saturation point (2 wt %)

24

Model Review

Synergistic Model:•Gokis (2000)- MRR results from abrasive and chemical action

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

(RRmech)o = mechanical wear = Ke PV

(RRchem)o = chem. dissolution = kr exp(-E/RT)Cin

kchem = factor accounting for chemical modification

kmech = factor accounting for abrasive activation

25

Effects of glycine and H2O2 on Cu removal rate

0

100

200

300

400

500

0 2 4 6 8 10

H2O2 wt%

Material Removal Rate (nm/min)

.. 0.1M glycine

without glycine

etch rate withoutglycine

(Seal et al., 2003)

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Experimental Study

Alumina, silica pH Ionic strength Ultrasonication Cu CMP additives

Stability of colloidal particles

A) Measurement of Zeta Potential

B) Measurement of particle size and distribution as function of slurry chemistry

Coagulation/ well-dispersed Bi-modal – near IEP

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Research Study

Experiments Ceralox® alumina

DI H2O w/ KCl to alter ionic strength –(Babu et al., 2000)

Commercial alumina slurries from Stein (Sandia National Laboratories)

EKC Tech slurry (Doyle, UCB)- Cu CMP slurry additives

Model MRR predictions vs. literature experimental polishing data Average particle size and standard deviations used in Lou and Dornfeld

model

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Alumina particles in DDI H2O

-40

-30

-20

-10

0

10

20

30

40

50

60

3 4 5 6 7 8 9 10 11 12

pH

Zeta Potential (mV)

...

IEP 9

(Sumitomo Chem. Co.,250 nm)

(Ceralox®, 300 nm)

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Ceralox® alumina – ionic strength

Ionic Strength: 10-4 to 10-7M

-50

-40

-30

-20

-10

0

10

20

30

40

3 4 5 6 7 8 9 10 11

Zeta Potential (mV)

1.0E-08

1.0E-07

1.0E-06

1.0E-05

1.0E-04

1.0E-03

1.0E-02

1.0E-01

1.0E+00

Ionic Strength (M)

30

vs. pH for Ceralox alumina particles with 10-3M KNO3

IEP ~9, agglomerationBroader distribution near IEPAverage size 300 nm

Standard deviation pH 3.5-7 ~ 10 nm pH 9 ~300 nm

-50

-40

-30

-20

-10

0

10

20

30

40

3 5 7 9 11

pH

Zeta Potential (mV)

...

0

0.5

1

1.5

2

Effective Diameter

(microns)

...

0

20

40

60

80

100

120

0 500 1000 1500 2000 2500 3000 3500Diameter (nm)

Intensity

pH 8.8pH 5.6

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Common Cu slurry additives

Additives Name Concentration

Buffering agent NH4OH, KOHKOH, HNOHNO33 bulk pH 3-8

Complexing agent GlycineGlycineEthylene-diamine-tetra-acetate(EDTAEDTA)citric acid

0.01-0.1M

Corrosion inhibitor Benzotriazole (BTABTA)3-amino-triazole (ATA) KI

0.01-1wt%

Oxidizer HH22OO22, KIO3, K3Fe(CN)

citric acid

0-2 wt%

Surfactant Sodium-dodecyl-sulfate (SDSSDS), cetyltrimethyl-ammonium-bromide (CTAB)

1-20 mM

32

and particle size vs. pH for EKC Tech alumina with 10-3M KNO3

IEP ~9 → agglomeration varied by±15%200 nm - pH<8

-40

-20

0

20

40

60

3 4 5 6 7 8 9 10 11

pH

Zeta Potential (mV)

..

0

500

1000

1500

2000

2500

3000

3500

Effective Particle Size (nm)

..

particle size standard deviation < 5nm for pH>8 > 300 nm for pH<8

33

and particle size vs. pH for EKC Tech alumina with 10-3M KNO3 and glycine

IEP ~9, agglomeration varied by ±2%200 nm pH<8

-30

-20

-10

0

10

20

30

40

50

60

70

3 4 5 6 7 8 9 10 11

pH

Zeta Potential (mV)

...

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Effective Particle Size (nm)

...

0.001M glycine

0.01M glycine

0.1M glycine

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and particle size vs. pH for EKC Tech alumina with 10-3M SDS and 10-3M KNO3

ranged from -34 to -46 mVAverage particle size ~220nm (approximately double stated size)Particle size standard deviation small (< 5nm)

-50

-45

-40

-35

-30

-25

-20

-15

-10

-5

0

3 5 7 9

pH

Zeta Potential (mV)

..

100

150

200

250

300

Particle Size (nm)

..

-5

0

5

10

15

20

25

30

0 50 100 150 200 250 300 350

Particle Size (nm)

Percentage

pH 6

35

and particle size vs. pH for EKC Tech alumina with 0.01 wt% BTA or 0.01M EDTA & 10-3M KNO3

BTA - no effectEDTA - shifted IEP to pH 5, large particles

-30

-20

-10

0

10

20

30

40

50

3 4 5 6 7 8 9 10 11

pH

Zeta Potential (mV)

..

0

500

1000

1500

2000

2500

3000

Effective Particle Size (nm)

..

-30

-20

-10

0

10

20

30

40

50

3 4 5 6 7 8 9 10 11pH

Zeta Potential (mV)

..

0

500

1000

1500

2000

2500

3000

Effecti ve Particle Size (nm)

..

36

Lou and Dornfeld Mechanical Model

Slurry Concentration C

Average Abrasive Size Xavg

Proportion of Active Abrasives

N

Force F & Velocity

Active Abrasive Size Xact

Passivation rate

Wafer hardness Hw

Vol

Basic Eqn. of Material Removal: MRR = N x Vol

Ref.: Lou and Dornfeld (2001)

37

Overall Research Approach

Comprehensive Model (Dornfeld, 2003)a) Mechanical effects (Dornfeld et al., UCB)b) Electrochemical effects (Doyle et al., UCB)c) Colloidal effects (Talbot & Gopal, UCSD)

(Moon and Dornfeld et al. 1999)Slurry film thickness (mm)

•Si Wafer

•Pressure: 1.5 psi

•Velocity: 2-12 rpm

•Polishing time: 2-4 hours

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Model Sensitivity to Standard Dev.

Simplified dependency on standard deviation

For xavg <500 nm small variation σ results in large % change in MRR

( )MRR

x

x

avg

avg

∝+ 3

2

3

σ

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Collision Efficiency

•CMP 104-106 s-1

•Collison Efficiency)fraction collisions → permanent attachment

•Most particles do not agglomerate

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

10000 100000 1000000

G (Shear Rate s -1)

Collision Efficiency

...

1000 nm

500 nm

300 nm

100 nm

104 106105

⎥⎦

⎤⎢⎣

⎡=

336)(

Ga

Aafo πμ

α

40

Maximum Aggregate Size

Effective Particle Size (nm) Max. Aggregate Size (nm)

Shear rate 104s-1

100 180

200 or greater Total aggregate break up

Shear rate 103s-1

100 1800

200 900

300 600

400 or greater Total aggregate break up

Rmax =

2/1

218⎟⎠

⎞⎜⎝

⎛δπGa

A

41

•P = 1 psi, 4 inch blanket wafer, wafer carrier & platen velocity = 100 rpm, pad hardness = 100 MP, passivation rate = 100 nm/min

42

MRR prediction and particle size for alumina with and without glycine

Max. MRR 160 nm/min without additives

Max. MRR 120nm/min with 0.1M glycine

0

50

100

150

200

250

3 4 5 6 7 8 9 10 11

pH

MRR (nm/min) @ 1psi

..

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size (nm)

..

0

50

100

150

200

250

3 4 5 6 7 8 9 10 11

pH

MRR (nm/min) @ 1psi

...

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size (nm)

No additives 0.1 M glycine

43

MRR prediction and particle size for alumina with glycine and hydrogen peroxide

Max. MRR 170 nm/min with 0.1 wt% H2O2

Max. MRR 220 nm/min with 2 wt% H2O2

0.1M glycine, 0.1wt% H2O2

0

50

100

150

200

250

3 5 7 9 11

pH

MRR (nm/min) @ 1psi

..

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size (nm)

..

0

50

100

150

200

250

3 5 7 9 11

pH

MRR (nm/min) @ 1psi

..

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size (nm)

..

0.1M glycine, 2 wt% H2O2

44

MRR prediction and particle size for alumina with Cu slurry additives

MRR 1-10 nm/min

Particle size 0.5 -3 microns

0.01wt% BTA, 10-3M SDS, 0.1M glycine, 0.1wt% H2O2,

0123456789

10

3 4 5 6 7 8 9 10 11pH

MRR (nm/min) @ 1psi

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size

(nm)

0

1

2

3

4

5

6

7

8

9

10

3 4 5 6 7 8 9 10 11pH

MRR (nm/min) @ 1psi

0

500

1000

1500

2000

2500

3000

3500

4000

Effective Particle Size

(nm)

0.01wt% BTA, 10-3M SDS, 0.01M EDTA, 0.1wt% H2O2,

45

Summary- effects of additives

Additive Effect

Glycine stabilizing agent

BTA No effect

EDTA Unstable, agglomeration

SDS 2x agglomeration, stable, negative ζ

46

Conclusions

Background electrolyteParticle size distribution vs. IEPEffects of Cu polishing rates w/different chemistries Cu-glycine complexes in presence of H2O2 result in

increased MRR

Slurry additives affect colloidal behavior – pH largest effectLou and Dornfeld model Can predict trends well Model is sensitive to variation of

47

Future Work

Cu CMP Experiments Slurry additives: glycine, hydrogen peroxide

Zeta potential – w/ dissolved Cu or Cu particlesModel improvements Use actual particle distribution Surface hardness link to chemistry Passivation rate of Cu (Doyle)Adhesion tests – post-CMP cleaning