1

Colloidal Aspects of Chemical Mechanical Polishing (CMP)

Tanuja Gopal & Jan Talbot Chemical Engineering Program

University of California, San DiegoMay 10, 2004

2

Outline

IntroductionBackground & MotivationResearch ApproachExperimental ResultsConclusionsFuture 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 VariablesWafer down pressureWafer velocityPad characteristics

Particle characteristicsSlurry chemistrySubstrate characteristics

Process ResultsMaterial Removal RatePlanarizationSurface finish

7

Typical Process ConditionsWafer

Wafer rotational speed = 20 - 60 rpmApplied pressure = 1.5-13 psi

SlurryFlow rate = 100 - 300 ml per minParticle type = silica, alumina, ceria, titania, etc.Particle concentration = 1 - 30 % by weightParticle size = 50 - 1000 nm diameter

Removal RateSiO2 = 200 - 300 nm per minute Cu or W = 300 - 600 nm per minute Planarization time = 1- 3 minRMS 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 surfacesGlobal planarization

200 and 300 mm (8 and 12 inch) wafersICs have feature sizes <0.2 µmRMS roughness: < 1nm

DisadvantagesLarge water consumptionCMP defectsEnd point detection

11

Motivation for Research

Fundamental understanding of chemical effects in CMPRole of slurry chemistry not understood (additives, ionic strength, pH)Optimize slurries -high removal rates w/ adequate planarityReduce consumables (slurries are expensive, mostly not recycled)Enhance post CMP cleaning – large water usageFocus on Copper CMP – Cu interconnect of choice

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

12

Research ApproachExperimental study of colloidal behavior of CMP slurries

Zeta potential and particle size distribution measurementsFunction of pH, ionic strength, additives

Commercial alumina slurriesAlumina – no additivesAlumina in presence of common Cu CMP additivesAgglomeration during CMP

Incorporate colloidal chemistry into existing mechanical model by Lou and Dornfeld

Average particle size, standard deviation parametersComparison to literature material removal rates

13

Cu CMP Chemical ReactionsDissolution: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

16

Electrical Double Layer

+ +

++

+

+ + +++

+

++

++

+

+

+

+

++

a

+

+

+

Distance

Pote

ntia

l

ζ

1/κ

Diffuse Layer

Shear Plane

Particle Surface

2/122000⎟⎟⎠

⎞⎜⎜⎝

⎛=

RTIF

roεεκ

∑=i

ii zcI 2

21

εηζ /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 |ζ| < 5mV.

17

Measurement of Zeta PotentialEYEPIECE

PRISM

MICROSCOPE

ζ calculated using Smoluchowski eqn:

(valid for κ a >>1)

ζ = 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

|ζ|≥ 30 mV: stable

|ζ| < 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

Al2O3SiO2W

Polishing Regime

pH

Zet

a Po

tent

ial (

mV

)

19

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

• Polishing rate dependent upon colloidal particle - W in KIO3slurries (Stein et al., J. Electrochem. Soc. 1999)

Polis

hing

rat

e (Α

/min

)

Colloid oxide

Gla

ss p

olis

hing

rat

e (µ

m/m

in)

Oxide Isoelectric point

20

Agglomeration

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

(Bellman et al., 2002)

21

Removal Rate in CMPPreston’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 effectsFails 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 = ρw N Vol

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

23

Model ReviewChemical 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)ΠCi

n

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%

Mat

eria

l Rem

oval

Rat

e (n

m/m

in)

.. 0.1M glycine

without glycine

etch rate withoutglycine

(Seal et al., 2003)

26

Experimental Study

Alumina, silicapHIonic strengthUltrasonicationCu 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-dispersedBi-modal – near IEP

27

Research Study

ExperimentsCeralox® alumina

DI H2Ow/ 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

28

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

Pot

entia

l (m

V)...

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

Zet

a Po

tent

ial (

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

Ioni

c St

reng

th (M

)

30

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

IEP ~9, agglomerationBroader distribution near IEPAverage size 300 nm

Standard deviationpH 3.5-7 ~ 10 nmpH 9 ~300 nm

-50-40-30-20-10

010203040

3 5 7 9 11

pH

Zeta

Pot

entia

l (m

V)...

0

0.5

1

1.5

2

Effe

ctiv

e D

iam

eter

(mic

rons

)...0

20

40

60

80

100

120

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

Inte

nsity

pH 8.8pH 5.6

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Common Cu slurry additives

1-20 mMSodium-dodecyl-sulfate (SDSSDS), cetyltrimethyl-ammonium-bromide (CTAB)

Surfactant

0-2 wt%HH22OO22, KIO3, K3Fe(CN)citric acid

Oxidizer

0.01-1wt%Benzotriazole (BTABTA)3-amino-triazole (ATA) KI

Corrosion inhibitor

0.01-0.1MGlycineGlycineEthylene-diamine-tetra-acetate(EDTAEDTA)citric acid

Complexing agentbulk pH 3-8NH4OH, KOHKOH, HNOHNO33Buffering agent

ConcentrationNameAdditives

32

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

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

-40

-20

0

20

40

60

3 4 5 6 7 8 9 10 11

pH

Zet

a Po

tent

ial (

mV

)..

0

500

1000

1500

2000

2500

3000

3500

Effe

ctiv

e Pa

rtic

le S

ize

(nm

)..

particle size standard deviationζ < 5nm for pH>8ζ > 300 nm for pH<8

33

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

IEP ~9, agglomerationζ 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

Pot

entia

l (m

V)...

0

500

1000

1500

2000

2500

3000

3500

4000

4500

Effe

ctiv

e Pa

rticl

e Si

ze (n

m)...

0.001M glycine0.01M glycine0.1M glycine

34

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

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

-50-45-40-35-30-25-20-15-10-50

3 5 7 9

pH

Zeta

Pot

entia

l (m

V)..

100

150

200

250

300

Parti

cle

Size

(nm

)..-5

0

5

10

15

20

25

30

0 50 100 150 200 250 300 350

Particle Size (nm)Pe

rcen

tage

pH 6

35

ζ and particle size vs. pH for EKC Tech aluminawith 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

Zet

a Po

tent

ial (

mV

)..

0

500

1000

1500

2000

2500

3000

Eff

ectiv

e Pa

rtic

le S

ize

(nm

)..-30

-20

-10

0

10

20

30

40

50

3 4 5 6 7 8 9 10 11pH

Zet

a Po

tent

ial (

mV

)..0

500

1000

1500

2000

2500

3000

Effe

cti v

e Pa

rtic

le S

ize

(nm

)..

36

Lou and Dornfeld Mechanical Model

Slurry Concentration C

Average Abrasive Size Xavg

Proportion of Active Abrasives

NForce 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 ApproachComprehensive 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

38

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

xavg

avg∝

+ 32

3

σ

39

Collision Efficiency

•CMP 104-106 s-1

•Collison Efficiency(αο)−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)

Col

lisio

n E

ffic

ienc

y...

1000 nm

500 nm

300 nm

100 nm

104 106105

⎥⎦

⎤⎢⎣

⎡= 336

)(Ga

Aafo πµα

40

Maximum Aggregate Size

600300

900200

Total aggregate break up400 or greater

1800100

Shear rate 103s-1

Total aggregate break up200 or greater

180100

Shear rate 104s-1

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

Rmax = 2/1

218⎟⎠⎞

⎜⎝⎛

δπGaA

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 additivesMax. MRR 120nm/min with 0.1M glycine

0

50

100

150

200

250

3 4 5 6 7 8 9 10 11

pH

MR

R (n

m/m

in) @

1ps

i..

0

500

1000

1500

2000

2500

3000

3500

4000

Eff

ectiv

e Pa

rtic

le S

ize

(nm

)..0

50

100

150

200

250

3 4 5 6 7 8 9 10 11pH

MR

R (n

m/m

in) @

1ps

i...

0

5001000

1500

2000

25003000

3500

4000

Effe

ctiv

e Pa

rtic

le S

ize

(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

MR

R (n

m/m

in) @

1ps

i..

0

500

1000

1500

2000

2500

3000

3500

4000

Effe

ctiv

e Pa

rtic

le S

ize

(nm

)..0

50

100

150

200

250

3 5 7 9 11

pHM

RR

(nm

/min

) @ 1

psi..

0

500

1000

1500

2000

2500

3000

3500

4000

Effe

ctiv

e Pa

rtic

le S

ize

(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

MR

R (n

m/m

in) @

1ps

i

0

500

1000

1500

2000

2500

3000

3500

4000

Effe

ctiv

e Pa

rtic

le S

ize

(nm

)

0123456789

10

3 4 5 6 7 8 9 10 11pH

MR

R (n

m/m

in) @

1ps

i0

500

1000

1500

2000

2500

3000

3500

4000

Effe

ctiv

e Pa

rtic

le S

ize

(nm

)

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

45

Summary- effects of additives

2x agglomeration, stable, negative ζ

SDS

Unstable, agglomeration

EDTA

No effectBTA

ζ stabilizing agentGlycineEffectAdditive

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 wellModel is sensitive to variation of ζ

47

Future Work

Cu CMP Experiments Slurry additives: glycine, hydrogen peroxide

Zeta potential – w/ dissolved Cu or Cu particlesModel improvements

Use actual particle distributionSurface hardness link to chemistryPassivation rate of Cu (Doyle)

Adhesion tests – post-CMP cleaning