FLCC March 19, 2007 CMP 1 FLCC Seminar Title: Effects of CMP Slurry Chemistry on Agglomeration of Alumina Particles and Copper Surface Hardness Faculty:

March 19, 2007 CMP

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FLCC Seminar

Title: Effects of CMP Slurry Chemistry on Agglomeration of Alumina Particles and Copper Surface Hardness

Faculty: Jan B. TalbotStudent: Robin IhnfeldtDepartment: Chemical EngineeringUniversity: University of California,

San Diego

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IntroductionIntegrated Circuit manufacturing requires material removal and global planarity of wafer surface – Chemical Mechanical Planarization (CMP)

–Material Removal Rate (MRR) is affected by:

•Abrasive size and size distribution•Wafer surface hardness

–Cu is the interconnect of choice- our research focus

–CMP slurries provide material removal by:

•Mechanical abrasion–Nanometer sized abrasive particles (alumina)

•Chemical reaction–Chemical additives (glycine, H2O2, etc.)

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slurry

waferpolishing pad

platen

polishing pad

wafer

slurry

wafer carrier

P = 1.5-13 psi

(100-300 ml/min)V= 20-90 rpm

(polyurethane)

Particle concentration = 1 - 30 wt% Particle size = 50 - 1000 nm dia

Cu MRR= 50 - 600 nm/minPlanarization time = 1- 3 minRMS roughness = < 1 nm

CMP Schematic

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Motivation– Better process control

• Understand role of slurry chemistry (additives, pH, etc.) • Develop slurries to provide adequate removal rates and global

planarity– Prediction of material removal rates (MRR)

• Predictive CMP models - optimize process consumables• Improve understanding of effects of CMP variables• Reduce cost of CMP

– Reduce defects• Control of abrasive particle size • Control of interactions between the wafer surface and the slurry

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Research Approach

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

• Function of pH, ionic strength, additives – Alumina particles in presence of common Cu CMP additives– Alumina particles in presence of copper nanoparticles

• Measurement of surface hardness as function of slurry chemistry

• Develop comprehensive model (Lou & Dornfeld, IEEE, 2003)

– Mechanical effects (Dornfeld et al., UCB)– Electrochemical effects (Doyle et al., UCB)

– Colloidal effects (Talbot et al., UCSD)

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Common Cu Slurry AdditivesAdditives Name Concentration

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

Complexing agent - bind with partial or fully charged species in solution

Glycine,Glycine,Ethylene-diamine-tetra-acetate(EDTAEDTA), citric acid

0.01-0.1M

Corrosion inhibitor - protect the wafer surface by controlling passive etching or corrosion

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

0.01-1wt%

Oxidizer - cause growth of oxide film

HH22OO22, KIO3, K3Fe(CN)

citric acid

0-2 wt%

Surfactant - increase the solubility of surface and compounds

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

1-20 mM

Robin Ihnfeldt and J.B. Talbot. J. Electrochem. Soc., 153, G948 (2006).

Tanuja Gopal and J.B. Talbot. J. Electrochem. Soc., 153, G622 (2006).

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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+

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Chemical Phenomena Chemistry of Glycine-Water System

copper-water system

[CuT]=10-5M

Ref.: Pourbaix (1957); (Aksu and Doyle (2002)

copper-water-glycine system

[LT]=10-1M, [CuT]=10-5M

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Colloidal Aspects of CMP1) Particle – particle

2) Particle – surface

3) Particle – dissolution product

4) Surface – dissolution product

Surface

Abrasive particleDissolution product

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Slurry Abrasives• 40 wt% -alumina slurry (from Cabot Corp.) • 150nm average aggregate diameter – 20nm primary particle diameter

Common Copper CMP Slurry Additives

• Glycine, EDTA, H2O2, BTA, SDS

Copper nano-particles• Added 0.12 mM to simulate removal of copper surface during CMP• <100 nm in diameter (from Aldrich)

Zeta Potential and Agglomerate Size Distribution• Brookhaven ZetaPlus

– Zeta Potential – Electrophoretic light scattering technique (±2%)– Agglomerate Size – Quasi-elastic light scattering (QELS) technique (±1%)

• All samples diluted to 0.05 wt% in a 1 mM KNO3 solution

• Solution pH adjusted using KOH and HNO3 and ultrasonicated for 5 min prior to measuring

Experimental Procedure

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Electrical Double Layer

+ +

++

+

+ + ++

++

++

++

+

+

+

+

++

a

+

+

+

Distance

Pote

ntia

l

1/

Diffuse Layer

Shear Plane

Particle Surface

2/122000

RT

IF

ro

i

ii zcI 2

2

1

/u

•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 de Waals attractive forces

•If potentials are near zero, abrasive particles may agglomerate

Zeta Potential

= ionic strength

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Zeta Potential - Potential at the Stern LayerElectrophoresis – Zeta potential estimated by applying electric field and measuring particle velocity

-60

-40

-20

0

20

40

60

80

2 4 6 8 10 12

pH

t Z

eta

Po

ten

tia

l (m

V)

0

1000

2000

3000

4000

g A

gg

lom

era

te S

ize

(n

m)

Surface charge on metal oxides is pH dependant:

• IEP at = 0

• Slurries are stable when || > 25 mV

M-OH + OH- → M-O- + H2OM-OH + H+ → M-OH2+

Cabot alumina without additives in 10-3M KNO3 solution (bars indicate standard deviation of

agglomerate size distribution)

Zeta Potential

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Cabot alumina in 10-3M KNO3 solution with and without 0.12mM copper

• IEP ~6.5 with and without copper• IEP~9.2 for -alumina from literature*

• Impurities (NO3-, SO4

2-, etc.) may lower IEP**

• At high pH values magnitude of zeta potential lower with copper than without

*M.R. Oliver, Chemical-Mechanical Planarization of Semiconductor Material, Springer-Verlag, Berlin (2004).

**G.A. Parks, Chem. Tevs., 65, 177 (1965).

-80

-40

0

40

80

0 2 4 6 8 10 12

pH

Ze

ta P

ote

nti

al (

mV

)Without CuWith Cu

Zeta Potential

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Agglomerate Size Distribution

• pH 2 – presence of copper causes decrease in agglomeration

• pH 7 – presence of copper causes increase in agglomeration

Cabot alumina dispersion in 1mM KNO3 solution with (red) and without (blue) 0.12 mM copper and without chemical additives

pH 2

0

10

20

30

0 2 4 Agglomerate size (mm)

% i

n s

olu

tio

n

pH 7

0

10

20

30

40

0 5 10Agglomerate size (mm)

% in

so

luti

on

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Potential-pH for Copper-water System[Cu]=10-4M at 250C and 1atm (M. Pourbaix 1957)

■ Agglomeration behavior is consistent with the Pourbaix diagram

Copper-Alumina-Water System

Average agglomerate size of bimodal distributions in a 1 mM KNO3 solution

IEP of CuO ~ 9.5*

*G.A. Parks, Chem. Tevs., 65, 177 (1965).

Robin Ihnfeldt and J.B. Talbot. J. Electrochem. Soc., 153, G948 (2006).

Small Average (nm)

Large Average (nm)

Small Average (nm)

Large Average (nm)

2 Cu, Cu+ 170 5000 160 8107 Cu, Cu2O, CuO, Cu(OH)2 580 3300 1700 9400

10 Cu, Cu2O, CuO, Cu(OH)2 150 720 300 1600

Without Copper With CopperPossible State of CopperpH

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Zeta PotentialCabot alumina in 0.1M glycine and 10-3M KNO3 solution with and without 0.12mM copper

• IEP ~6.5 without copper • IEP~9.2 increased with copper

*M.R. Oliver, Chemical-Mechanical Planarization of Semiconductor Material, Springer-Verlag, Berlin (2004).

**G.A. Parks, Chem. Tevs., 65, 177 (1965).

-80

-40

0

40

80

0 2 4 6 8 10 12

pH

Zet

a P

ote

nti

al (

mV

) Without CuWith Cu

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Potential-pH for Copper-Glycine-Water System*[Cu]=10-4M, [Glycine]=10-1M at 250C and 1atm

• Agglomeration behavior is consistent with Pourbaix diagram

Average agglomerate size of bimodal distributions in a 1 mM KNO3 solution with various additives

Copper-Glycine-Water System

*S. Aksu and F. M. Doyle, J. Electrochemical Soc., 148, 1, B51 (2006).

Small Average (nm)

Large Average (nm)

Small Average (nm)

Large Average (nm)

2 Cu, CuHL2+ 310 8100 220 7007 Cu, CuL2 2000 1900

10 Cu, CuL2-, CuL2 1030 6300 350 2100

2 Cu, CuHL2+ 130 300 1637 Cu, CuL2 1800 1400

10 Cu, CuL2-, CuL2 1200 1500

Possible State of Copper

Without Copper With CopperSolution

0.1M Glycine

0.1M Glycine+2.0wt%

H2O2

pH

-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

0 2 4 6 8 10 12 14 16pH

E, V

vs

. SH

E

Cu2+

CuO/Cu(OH)2

CuCu2O

CuO22-CuHL2+

CuL+

CuL2

CuL2-

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Measuring Wafer HardnessTriboScope Nanomechanical Testing

system from Hysitron Inc.

■ Considerations

– Large applied load will increase indentation depth –

• more likely for underlying layer to affect nanohardness measurements

– Slurry solutions with high etch rates will decrease copper thickness –

• thinner copper layer more likely for underlying layer to affect measurements

•1 cm2 silicon wafer pieces sputter deposited with 30 nm Ta + 1000 nm Cu

•10 min exposure in 100 ml of slurry solution (without abrasives), then removed and dried with air and measured

Robin Ihnfeldt and J.B. Talbot. 210th Meeting Electrochem. Soc., Cancun, Mexico, Oct. 29-Nov. 3, 602, 1147 (2006).

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■ pH 2 – appears that state of surface is Cu metal with increase in nanohardness from underlying layer

■ pH 7 and 12 – hardness less than that of bulk metallic Cu

– Cupric hydroxide, Cu(OH)2, is most likely forming

Copper Surface in Solution

Bulk metallic Cu H~ 2.3 GPa*

Surface nanohardness of Cu on Ta/Si (100uN applied load) after exposure to 1mM KNO3 solution

*S. Chang, T. Chang, and Y. Lee, J. Electrochemical Soc., 152, (10), C657 (2005).

Ta2O5 H~9 GPa

pH Possible State of CopperContact

Depth (nm)Etch Rate (nm/min)

Copper Thickness (nm)

Nanohardness (GPa)

2 Cu, Cu+, Cu2+ 30 16 810 2.97 Cu, Cu2O, CuO, Cu(OH)2 50 9 870 1.2

12 Cu, Cu2O, CuO, Cu(OH)2 43 0 960 1.2

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Glycine• Surface hardness is less than that of bulk Cu at pH 2 and 12 –

– Glycine may interact with surface layer to decrease compactness

• pH 7 appears to be Cu metal with increase due to underlying layer

Glycine + H2O2

• H2O2 increases solubility of Cu-glycinate complex or increases Cu oxidation

• Surface is less than bulk Cu at pH 2 and 7 – decrease in compactness due to glycine

• pH 12 appears to be cuprous oxide, Cu2O

Copper Surface in SolutionSurface nanohardness of Cu on Ta/Si (100uN applied load) after exposure to 1mM KNO3 solution and other additives

Chemistry pHPossible State of

CopperContact

Depth (nm)Etch Rate (nm/min)

Copper Thickness (nm)

Nanohardness (GPa)

2 Cu, CuHL2+ 41 0 960 1.37 Cu, CuL2 62 6 870 2.5

12 Cu, Cu2O, CuL2 81 14 780 0.5

2 Cu, CuHL2+ 135 22 640 0.87 Cu, CuL2 122 55 330 1.1

12 Cu, Cu2O, CuL2 48 -7 1020 3.6

0.1M Glycine

0.1M Glycine + 2.0wt% H2O2

Film Growth Increased Hardness

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CMP Experiments

Toyoda Polishing apparatus

(UC Berkeley)– IC1000 polishing pad pre-

conditioned for 20 minutes with diamond conditioner

– Polished 2 min with Cabot alumina

Silicon wafers (100 mm dia.) with 1 mm copper on 30 nm tantalum– Total of 18 wafers polished with various slurry chemistries and at

various pH values

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Experimental Copper CMP MRR

MRR is <20 nm/min for all pH values without additives, with 0.1M glycine

MRR is >100 nm/min for several pH values where both glycine and H202 are present

0

5

10

15

20

2 4 6 8 10 12pH

MR

R (

nm

/m

in)

No additives

0.1M Glycine

0.01M EDTA, 0.01wt% BTA,1mM SDS, 0.1wt% H2O2

0

100

200

300

400

2 4 6 8 10 12pH

MR

R (

nm

/m

in)

0.1M Glycine, 0.1wt% H2O2

0.1M Glycine, 2wt% H2O2

0.1M Glycine, 0.01wt% BTA,1mM SDS, 0.1wt% H2O2

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Lou and Dornfeld CMP Model

Slurry Concentration C

Average Abrasive Size Xavg

Proportion of Active Abrasives

N

Force F & Velocity

Active Abrasive Size Xact

Wafer hardness Hw/ Slurry Chemicals &

Wafer Materials

Vol

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

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ConclusionsColloidal Behavior • pH has greatest effect on colloidal behavior• Glycine acts as a stabilizing agent for alumina• Presence of Cu nanoparticles can increase or decrease

agglomeration depending on the state of copper in solution• Agglomeration behavior with copper is consistent with potential-

pH diagrams Nanohardness of Copper Surface• pH of the slurry affects copper surface hardness• Addition of chemical additives has large effect on the surface

hardness• State of copper on surface is consistent with potential-pH

diagrams• Under certain conditions glycine may cause decrease in copper

surface hardness

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Future Work

• Continue to investigate effect of copper on zeta potential and particle size– Determine state of Cu in solution– Study agglomeration as a function of time

• Initial hardness measurements show large differences in copper surface with pH and chemical addition– Determine reproducibility of hardness measurements– Determine state of Cu on surface

• Modeling – Luo and Dornfeld Model*– Incorporate experimental measurements (hardness and

agglomerate size distribution) into model and compare with experimental CMP data

*J. Luo and D. Dornfeld, IEEE Trans. Semi. Manuf., 14, 112 (2001).

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• Funded by FLCC Consortium through a UC Discovery grant. We gratefully acknowledge the companies involved in the UC Discovery grant: Advanced Micro Devices, Applied Materials, Atmel, Cadence, Canon, Cymer, DuPont, Ebara, Intel, KLA-Tencor, Mentor Graphics, Nikon Research, Novellus Systems, Panoramic Technologies, Photronics, Synopsis, Tokyo Electron

• Prof. Dornfeld and his research group at UC Berkeley for use of the CMP apparatus and model program

• Prof. Talke and his research group at UCSD for the use of the Hysitron Instrument.

Acknowledgments