Characterization Methods and Metrics for Patterned Wafer CMP

C M P P a t t e r n D e p e n d e n t M o d e l i n g

Boning 1 MIT-MTL

Characterization Methods and Metricsfor Patterned Wafer CMP

Prof. Duane Boning

Massachusetts Institute of TechnologyElectrical Engineering and Computer Science

Microsystems Technology LaboratoriesRoom 39-567, Cambridge, MA 02139

Phone: (617) 253-0931Email: [email protected]

http://www-mtl.mit.edu/Metrology


Boning 2 MIT-MTL

Pattern-Dependent CMP Concerns

GlobalNonplanarity

Oxide CMP:

SiO2

Metallines

Silicon

Oxide

Nitride

SiO2

Erosion

Corner

Dishing

Rounding

Shallow TrenchIsolation:

Copper CMP:

Cu

CopperOxide

SiO2

ErosionDishing

Cu

LocalStep

Height


Boning 3 MIT-MTL

Preview: Density & Global Planarity in Oxide CMP

Chemical-Mechanical Polishing to

remove local step

Goal: Reality:ρ1=low ρ2=high

t=0

t=ρ1z1/K

t=ρ2z1/K

Oxide Metal

LocalSteps

GlobalNonplanarity

turninto

density density


Boning 4 MIT-MTL

Need for Patterned Wafer Oxide CMP Standards

Planarization performance on patterned features is

inconsistently

and

incompletely

reported

■

Profilometry scans often shown over small to long distances

❏

But... planarization depends on a whole 2-10 mm region around that structure

■

Step height reduction (step height vs. time plots) often shown

❏

But... the results again depend strongly on nearby density

■

Total Indicated Range (TIR) often reported across a scan or across a die

❏

But... the TIR depends greatly on the specifics of the die.

❏

Reported numbers provide no information about performance on other die

■

What is needed:

❏

Standard masks or patterns for which performance can be measured

❏

Common terminology and metrics to succinctly capture patterned CMP performance


Boning 5 MIT-MTL

Outline

■

Motivation: Pattern Dependencies in Oxide, STI, and Metal Polishing

❏

Key Idea #1: Characterization using Test Masks and Test Patterns

❏

Key Idea #2: Planarization Length as Metric for Oxide CMP

■

Oxide Characterization Mask Evolution

■

Oxide CMP Model -- Effective Density

■

Planarization Length as a Metric

■

Future Issues

❏

Step height dependencies and characterization

❏

Dishing and erosion in STI, metal CMP

❏

Electrical test masks for copper CMP


Boning 6 MIT-MTL

Oxide CMP Characterization & Modeling: Key Ideas■ Problem: Global non-planarity within die in oxide CMP

■ Goal: Efficient chip-level characterization, comparison, and prediction of oxide thickness across arbitrary product die patterns

■ Approach: Characterization methods coupled to analytic model ❏ Removal rate is inversely proportional to effective density

❏ Effective density determination is critical: • polish at each point is affected by nearby topography and pattern density

■ Effective Density Calculation:❏ Weighted average of nearby layout density

❏ Approximation: use uniformly weighted square window

❏ Better: circular elliptically weighted “response function” for effective density

■ Planarization Length extraction using carefully designed characterization masks with various density and pitch structures

02

46

810

12

02

46

810

120

0.25

0.5

0.75

1

1.25

68

1012

0

0.25

0.5

0.75

1

1.25

Top Side


Boning 7 MIT-MTL

CMP Characterization Test Mask Evolution

1. Electrical Oxide CMP Test Masks

❏

With HP and LSI Logic

❏

Discovery: long range effects very important

2. MIT/Sandia/HP Characterization Mask Set

❏

Optical film thickness & Profilometry

❏

Discovery: density is the key parameter in oxide CMP

3. STI Mask

❏

Pitch structures and down area polishing

❏

Importance of deposition profile characterization

4. Step Density Variants

5. Comprehensive Dielectric Characterization Mask

❏

Combines key density (gradual & step) and pitch structures on one die


Boning 8 MIT-MTL

1. Electrical Test Mask for Oxide CMP (w/. HP)

LayoutFactorStructures

AreaFactorStructures

■ Line width

■ Line Spacing

■ Finger Length

■ No. of fingers

■ Orientation

■ Interaction Ringor Interaction Distance

■ Area of structure (fixed lw/ls)


Boning 9 MIT-MTL

Electrical Structures for Post-CMP ILD Thickness

■ Issue: design structure to isolate variation factors of interest & block other factors

■ Fingered capacitor test structure:

■ Coupling to TCAD tools to convert measurements to parameters of interest

van der Pauwsheet resistance structure

kelvin cdstructures

Capacitive test

Insulator

Bottom conductorwith variouslayout factors

tILD

A A’

Top metal plate

OxideDielectric

structures


Boning 10 MIT-MTL

Example Results

−0.08 −0.06 −0.04 −0.02 0 0.02 0.04 0.06 0.08

05

1015

2025

05

1015

2025

−0.1

−0.05

0

0.05

0.1

XY

-0.1

-0.05

0

0.05

0.1

(nor

mal

ized

)IL

D T

hick

ness

Spatial Die Pattern

■ Layout factors important -- but at a much longer length scale than expected in the original mask design.


Boning 11 MIT MTL

2. MIT/Sandia/HP Oxide Characterization Mask Set

■ Purpose: Identify pattern effects in oxide CMP

■ Publicly available at MIT web site; widely used

Area Mask Pitch Mask

Density Mask Perimeter/Area


Boning 12 MIT-MTL

Ex: Compare ILD Polish with Two Different Pads

Field Oxide Deposition0.8µm PETEOS

Metal Stack Formation25nm TiW

0.75µm Al/0.5% Cu25nm of TiN

Metal Pattern and Etch

ILD Deposition2.0µm PETEOS

CMPwith IC-1400 Pad

CMPwith IC-2000 Pad


Boning 13 MIT MTL

Ex: Profilometry Results

0 2 4 6 8 10

02468100

0.5

1

X (mm)Y (mm)

ILD

Thi

ckne

ss (

mic

rons

)

0 2 4 6 8 10

02468100

0.5

1

X (mm)Y (mm)

0 2 4 6 8 10

02468100

0.5

1

X (mm)Y (mm)

ILD

Thi

ckne

ss (

mic

rons

)

0 2 4 6 8 10

02468100

0.5

1

X (mm)Y (mm)

0 2 4 6 8 10

02468100.5

1

1.5

X (mm)Y (mm)

ILD

Thi

ckne

ss (

mic

rons

)

0 2 4 6 8 10

02468100.5

1

1.5

X (mm)Y (mm)

0 2 4 6 8 10

02468100.5

1

1.5

X (mm)Y (mm)

ILD

Thi

ckne

ss (

mic

rons

)

0 2 4 6 8 10

02468100.5

1

1.5

X (mm)Y (mm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

AreaMask

PitchMask

DensityMask

AspectRatioMask

IC-1400 IC-2000


Boning 14 MIT MTL

Conclusion: Density is Key Effect

■ Universal linear relationship between final oxide thickness and effective density

IC1400 IC2000

0 2 4 6 8 10−0.5

−0.25

0

0.25

0.5

Area (mm^2)

ILD

Thi

ckne

ss (

mic

rons

)Thickness vs. Area

IC1400 IC2000

0 250 500 750 10000

0.25

0.5

0.75

1

Pitch (microns)

ILD

Thi

ckne

ss (

mic

rons

)

Thickness vs. Pitch

IC1400 IC2000

0 0.25 0.5 0.75 10.5

0.75

1

1.25

1.5

Density

ILD

Thi

ckne

ss (

mic

rons

)

Thickness vs. Density

IC1400 IC2000

0 25 50 75 100−0.5

−0.25

0

0.25

0.5

Aspect Ratio

ILD

Thi

ckne

ss (

mic

rons

)

Thickness vs. Aspect Ratio

∆ IL

D T

hick

ness

(µm

)

ILD

Thi

ckne

ss (

µm)

ILD

Thi

ckne

ss (

µm)

∆ IL

D T

hick

ness

(µm

)

Area (mm2) Pitch (µm)

Density Aspect Ratio

Thickness vs. Area Thickness vs. Pitch

Thickness vs. Density Thickness vs. Aspect Ratio


Boning 15 MIT-MTL

3. Shallow Trench Isolation Masks (w/ AMAT, Sandia)

■ Oxide Polish Phase:❏ Density dependence extraction

■ Nitride Over-Polish Phase: ❏ Study dishing and erosion as function of density, pitch, feature size

Silicon

Oxide

Nitride

SiO2

Erosion

Corner

Dishing

Rounding

T. Pan et al., VMIC ‘98

Integrates

- density- pitch- SEM

structures on one mask.


Boning 16 MIT-MTL

Effective Density and Oxide Topography(Pan et al., VMIC ‘98)

0 2 4 6 8 10 12 14 16 18 200.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Die−X (mm)

Effe

ctiv

e D

ensi

ty

SACVD

mask

HDPCVD

■ For STI oxide modeling, oxide topography is critical

optical film thickness measurement

(a) (b)

■ Effective density model for oxide polish

HDPCVD SACVD


Boning 17 MIT-MTL

4. Step Density Masks (w/ TI)

0 4 8 12 16 200.5

1.0

1.5

0 4 8 12 16 200.5

1.0

1.5

20 mm

Characterization Mask

L1

L2L1 - Constant Density (50%)

L2 - Step Densities

Th

ickn

ess

(µm

)T

hic

knes

s (µ

m)

10% 90% 30% 70% 50%

Minimal patterneffect on raised

Significantpattern effectrange 5000Å

Polishing Evolution

time4 m

m

at final polish

varying pitch constantdensity

varying density constantpitch

time features

■ Step densities enable larger data for better up-area polish model extraction

■ Pitch blocks enable study of down-area polishing (step-height reduction) as a function of spacing width


Boning 18 MIT-MTL

5. MIT Comprehensive Dielectric Characterization Mask

■ 20mm x 20mm die size

■ Gradual density region

■ Step density region

■ Pitch region (constant 50% density)

■ SEM/Dielectric deposition characterization structures

■ Feature sizes down to 0.25µm

20

50

60 80

10030

40

70 90

20 m

m

10 90 30 70 50

P10 P50 P100

P500P200P30P80

P0.5 P0.7

P1 P2

10

P20

4 m

m

20 mm

P4 P6

P8 P10

GRADUAL

STEP

PITCHBIAS


Boning 19 MIT-MTL

Analytic CMP Model (Stine et al., CMPMIC ‘97)

■ CMP Characterization Mask Set❏ Pitch (linewidth and line space), perimeter, and structure area are minor effects

❏ Conclusion: Effective density is the key layout parameter

❏ Observe a simple oxide thickness vs. effective density dependence!

■ Oxide CMP Global Planarization Model

1. Polish rate at each point on the die is inversely proportional to the effective pattern density

2. Effective pattern density at each point depends on the nearby topography and density

3. The effective pattern density can be determined by the planarization length (or planarization window)

4. The planarization length must be characterized for a given CMP consumable set and process


Boning 20 MIT-MTL

Oxide CMP Pattern Dependent Model (Stine et al. ‘97)

■ Evaluation of pattern density is key to model development

■ Removal rate inversely proportional to density:

■ Density assumed constant (equal to pattern) until local step has been removed:

■ Final oxide thickness related to effective density:

dzdt----- k p pv– K

ρ x y,( )-----------------–= =

ρ x y z, ,( )ρ0 x y,( )

1

=z z0 z1–>

z z0 z1–<

zz0

Ktρ0 x y,( )---------------------

–

z0 z1– Kt– ρ0 x y,( )z1+

Kt ρ0z1<

Kt ρ0z1>

=

z1

z=0

z > z0-z1

z < z0-z1

up areas down areas

Metal

z0

Oxide

z = final oxide thickness over metal features

K = blanket oxide removal rate for a die of inter-est

t = polish timeρ0 = local pattern density

ρ0 x y,( )


Boning 21 MIT-MTL

Effective Density Using a Moving Window

L■ Effective density at X for a square constant weight

window is:

❏ L is defined as planarization length

■ The long-range “moving average” density calculation corresponds to a simple convolution picture:

❏ d(x,y) is the effective density at (x,y)

❏ p(x,y) is the “planarization impulse response” (weighting function) to raised features

❏ l(x,y) is the local (feature-scale) density

Raised area in square

Total area of square

d x y,( ) p x y,( ) l x y,( )⊗=

X

X

L


Boning 22 MIT-MTL

Importance of Effective Density vs. Layout Density

0 2 4 6 8 10 12

20

40

60

80

100

0 2 4 6 8 10 12

20

40

60

80

100

❏ Effective density ρ0 at X:

❏ Final oxide thickness is linearly related to effective density:

Raised Area in SquareArea of Square

z c ρ0 x y,( )z1+=

LX

12 mm

Eff

ecti

ve D

ensi

ty (

%)

Eff

ecti

ve D

ensi

ty (

%)

9%

57%

L = 2.5 mm

L = 10.0 mm

Effective Density along (B-B’)

B B’

(mm)


Boning 23 MIT-MTL

Definition: Planarization Length

PlanarizationLength

SiO2

Metal

lines

■ Planarization Length ❏ Distance over which further

planarization does not occur

❏ Approximation: distance of a “ramp” step in polished oxide thickness between two regions of different density

❏ Formal definition is possible

❏ Methods for characterization/extraction available

❏ Given the planarization length for a consumable set and process -- predictions for new layouts are possible


Boning 24 MIT-MTL

Definitions: Step Height and Local Planarity

Oxide/ILD Metal

h0 = step heightstep height reduction as function of polish time

local planarity: when local

feature step has been removed


Boning 25 MIT-MTL

Step Height Reduction

0 10 20 30 40 50 60 70 80 900

1000

2000

3000

4000

5000

6000

7000

Ste

p H

eig

ht

Polish Time

50% density,

High densityLow density

Low Density

1000µm pitch

High Density

50% density,1000µm pitch

■ Down area oxide thickness measurements used to study SHR as function of density and line spacing:


Boning 26 MIT-MTL

Definition: Total Indicated Range (TIR)

■ TIR = Total Indicated Range = Max ILD thickness -

Min ILD thickness❏ Measures total within-die (or within-

scan) global nonuniformity

❏ Good figure of merit for a given mask layout and process/consumable set

❏ Must know where high and low oxide thicknesses are located in die

❏ Provides little information that is applicable to other masksExample profilometry scans over

existing test structures on a die.

Scan actually depends on layout several mm away


Boning 27 MIT-MTL

Density Mask: Effective vs. Layout Density for Different Planarization Lengths

LX

■ Effective density (and thus ILD thickness) changes depending on size of window■ The location of the high and low spots on the MIT density mask change location

depend on the pad/process (planarization length)!

0.00

0.20

0.40

0.60

0.80

1.00

1.20

0.04

0.12

0.2

0.28

0.36

0.44

0.52

0.6

0.68

0.76

0.84

0.92 1

Layout Density

Eff

ec

tiv

e

De

ns

ity 2 mm

3 mm

4 mm

5 mm

6 mm

7 mm

8 mm

9 mm

Acknowledge Doug Goetz (3M) for

observations on effective density

Planariz.Length


Boning 28 MIT-MTL

Planarization Length Extraction

LX

z

ρ

L

Min

imiz

e S

um

of

Sq

uar

e E

rro

r

CandidatePlanarization

Length

Effective Densityfor Measured

Points

Fit/Plot Oxidevs. Effective

Density

Rep

eat

to


Boning 29 MIT-MTL

Planarization Length - Extraction Methods■ Window Size with Best Regression Fit

1. Extract layout densities with different window sizes

2. Fit measured ILD thickness vs. density

3. Pick window size with largest R2

■ Linear Regression with Correct Slope (Equal to Initial Step Height)

1. Pick window size for linear regression that matches known initial step height

■ Density Step Response

1. Experimentally fabricate a large step in density

2. Measure (e.g. via profilometry) the resulting ILD

Window Size (mm)

⊗ =

l(x) t(x)p(x)


Boning 30 MIT-MTL

Determining the Interaction Distance (Example)

3 3.5 4 4.50.25

0.5

0.75

1

1.25

3 3.5 4 4.50.25

0.5

0.75

1

1.25

Planarization

Slop

e (µ

m)

IC-1400 PadIC-2000 Pad

Knownstep height

(z1)Sl

ope

(µm

)

Knownstep height

(z1)

Length (mm)Planarization Length (mm)

Density Mask Area Mask


Boning 31 MIT-MTL

Planarization Length & WIndow Size

■ Effective Density Window IDENTICAL TO “ Planarization Length”❏ Density window captures what nearby topography the process “sees” at point X.

■ Alternative Characterization Method: Fabricate a layout “ step density”❏ The resulting oxide thickness provides a “step density response” of the pad and

process -- that can be measured experimentally

10%90%

⊗ =

l(x) t(x)p(x)

90%10%TopView

SideView

planarizationimpulse response

local layoutdensity final oxide

thickness

⊗underlying metal pattern with given density

XX ... X


Boning 32 MIT-MTL

Signal Processing Analogy: Pad “ Impulse” Response

■ The long-range “moving average” density calculation corresponds to a simple convolution picture:

❏ p(x,y) is the “pad impulse response” to raised features

❏ l(x,y) is the local (feature-scale) density, i.e. linewidth/pitch

❏ t(x,y) is the resulting oxide thickness

■ Goal: Determine the correct pad impulse response shape and size

■ Approach #1 - Deconvolution via Fourier Transform

where , and .

p x y,( ) l x y,( )⊗ t x y,( )=

P kx ky,( )T kx ky,( )L kx ky,( )---------------------=

T kx ky,( ) F t x y,( )( )= p x y,( ) F 1– P kx ky,( )( )=


Boning 33 MIT-MTL

Extraction using Step Response Experiments

■ Approach #2: Step Response❏ Direct measurement of the impulse response is difficult

❏ However, the “pad step response” can be experimentally measured

❏ Impulse response can be recovered (in some circumstances) by differentiation

■ One-Dimensional Example:

⊗ =

l(x) t(x)p(x)

l ξ( ) p x ξ–( ) ξd∞–

∞

∫ t x( )=

xdd

t x( ) p x( )=


Boning 34 MIT-MTL

Experimental Idea: Step Density Test Structure

0

50

0

50

0

50

0

500

0.5

1

0

50

0

500

0.5

1

0 50 0 500

0.2

0.4

0.6

0.8

1

0 500

0.2

0.4

0.6

0.8

1

0 50

2-D Step Response for Square Window■ Fabricate step density

structures; polish

■ Experimentally measure oxide thickness across step density structure❏ trace = “step response”

■ In 1D case, can differentiate “step response” to recover the “impulse response” shape

■ In 2D square window case, can also differentiate trace to recover planarization response function shapewindow

(impulselocal

density

final

thicknessoxidelayout

response)

recovered

shapewindow⊗ =

step response


Boning 35 MIT-MTL

New Elliptically Weighted Planarization Response

0

50

0

50

0

50

0

500

0.5

1

0

50

0

500

0.5

1

0 50 0 500

0.2

0.4

0.6

0.8

1

0 500

0.2

0.4

0.6

0.8

1

0 50

window(impulse

local

density

final

thicknessoxidelayout

response)

recovered

shapewindow⊗ =

■ Recovering a unique window shape from the step response trace appears difficult -- assume a shape

■ Question: What window shape should be used?

■ Approach: ❏ Find a physically sensible window

❏ Tune the length scale of shape function to best match the step response (or other) experimental data

■ Proposal: specially weighted window:❏ Radial symmetry

❏ Weighting as an elliptic function


Boning 36 MIT-MTL

Motivation: Deformation Profi le in an Elastic Material

a q

0

■ Deformation of elastic material (e.g. pad) under a spatially localized load of width L

L

■ Within the load area (r<a):

■ Outside the load area (r>a):

w r( ) 4 1 v2–( )qaπE

---------------------------- 1r2

a2-----

2θsin– θd

0

π2---

∫=

w r( ) 4 1 v2–( )qrπE

---------------------------- 1a2

r2-----

2θsin– θd

0

π2---

∫ 1 a2

r2-----–

θd

1a2

r2-----

2θsin–

---------------------------------0

π2---

∫–=


Boning 37 MIT-MTL

Planarization Response Function: Length Scale Parameterization

−10 −5 0 5 100

0.5

1.0

L

2/π

■ New Definition: “planarization length” is defined as the width (length scale) parameter in the elliptic elastic deformation function:❏ L = width of response

function at of its peak value

2 π⁄

−10 −5 0 5 100

0.2

0.4

0.6

0.8

1.0

L=1000L=2000L=3000

■ Planarization response function❏ Shape can be varied

substantial by choice of the planarization length L:

❏ Use L to characterize response for given pad, process


Boning 38 MIT-MTL

Planarization Length - What Definition to Use?

2 3 4 5 60.8

0.9

1

1.1

1.2

0

1

Square

0

1

Cylinder

0

1

Gaussian

0

1

Elliptic

Tool/Process 1:

Filter RMS Error Window Size

☛ Square 91Å 5.25 mmCylindrical 100Å 5.85 mmGaussian 56Å 10.5 mm

Elliptic 42Å 7.35 mm

A A’

10% 90%

4 mm 4 mm

~0% ~0%

Square & Elliptic fits


Boning 39 MIT-MTL

Response Function Comparisons - Test Die

0

1

Square

0

1

Cylinder

0

1

Gaussian

0

1

Elliptic

0 4 8 12 16 200.5

1

1.5

0 4 8 12 16 200.5

1

1.5

0.5

1

1.5

0.5

1

1.5

Density mapwithin smallgrid cells

Tool/Process 2:

Filter RMS Error Window Size

Square 257 A 2.7 mmCylindrical 251 A 3.3 mmGaussian 243 A 5.1 mm

Elliptic 239 A 7.8 mm


Boning 40 MIT-MTL

Die-Level Effective Density Calculation UsingPlanarization Response Function

■ Use elliptically weighted window to calculate effective density for each point on the patterned die

■ Effective density determines polish rate:

X

PL

50%

regions

gradualdensity regions

stepdensity regions

density

PRK

ρ x y PL, ,( )---------------------------=

Effective Density Map

Ouma et al., IITC ‘98

Integrated DielectricCharacterization Mask


Boning 41 MIT-MTL

Example: Post-Oxide Polish Thickness Prediction

0 10 20 30 40 50 600.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

ActualModel

0 10 20 30 40 50 601.5

1.55

1.6

1.65

1.7

ActualModel

Raised Area Predictions

Th

ickn

esse

s (µ

m)

Site # Site #

Down Area Predictions

Th

ickn

esse

s (µ

m)

RMSE = 273Å RMSE = 253Å

■ Density dependent model applied to both “up” (over metal) and “down” (between metal) oxide thickness resulting from oxide CMP:

50%

regions


stepdensity regions

density50%

regions


stepdensity regions

density

Smith et al.,CMP-MIC ‘99


Boning 42 MIT-MTL

Planarization Length/Response vs. TIR

■ TIR = Total Indicated Range = Max oxide thickness - Min oxide thickness❏ Measures total within-die global nonuniformity

❏ Good figure of merit for a given mask layout and process/consumable set

❏ Must know where high and low oxide thicknesses are located in die

❏ Provides little information that is applicable to other masks

■ Planarization Length and Response Function❏ Measures planarization capability of a given process/consumable set

❏ A derived metric based on measurements & characterization mask

❏ Powerful: used to efficiently predict oxide thickness for arbitrary layout:

❏ Future: relate planarization length to fundamental pad/process parameters

05

1015

20

05

1015

200

1

Effective density with elliptic filter of length 7.8 mm


Boning 43 MIT-MTL

Density Range and Resulting ILD Variation

2 4 6 8 10 120

20

40

60

80

100

0 1000 2000 3000 4000 5000 6000 7000 80000

20

40

60

80

100

TIR (Å)

Den

sity

Ran

ge,

(

%)

∆ρ

■ Effective density range across chip for any given CMP process/consumables:

=

■ Density variation results in oxide thickness variation -

Total Indicated Range (TIR):

, where

is initial deposition step height

∆ρ ρmax ρmin–

TIR ∆z ∆ρ z1•= =

z1


Boning 44 MIT-MTL

Future Issues

■ Step height dependencies and characterization❏ Important for small step height prediction (oxide, STI, other)

❏ Oxide Model Improvements• Density is not the whole story (just most of the story)• Integrated model combining effective density and step height dependence

improves model prediction accuracy

■ Model extensions needed for Copper/Metal/STI CMP❏ Dishing and erosion effects in STI and Metal CMP

❏ Characterization test masks for copper CMP


Boning 45 MIT-MTL

Step Height Dependence

■ Incompressible Pad Model: ❏ Up area removal rate scaled by density (e.g. MIT density model)

■ Compressible Pad Model:❏ Up area removal rate proportional to step height (Burke, Tseng, others)

■ Transition from incompressible to compressible pad model (Grillaert et al. - IMEC)

❏ Occurs at contact height or contact time where h1

Wafer Wafer

CMP Pad CMP Pad

Incompressible Pad Model Compressible Pad Model

h1

tc h1 h0 tcKρ----⋅

–=


Boning 46 MIT-MTL

Step Height Reduction■ Large Step Heights ■ Small Step Heights

Grillaert et al., CMP-MIC ‘98

❏ Density effect dominates

❏ Step height reduction linear in time❏ Up/down area pressure difference

❏ Step height reduction exponential in time


Boning 47 MIT-MTL

Integrated Effective Density/Step Height Model

■ Need efficient prediction for arbitrary layouts❏ Utilize the effective density concept

❏ Parameter used here is the planarization length (PL)

■ Need higher accuracy in low density regions and for remaining step height❏ Include the step height or linear/exponential time dependency

❏ Parameters include:• Exponential time constant ( )

• Contact height ( ) for each site

• Blanket removal rate (K)

❏ Contact heights forced to be dependent on effective pattern density:

•

■ Integrated model has 6 parameters to be extracted for a given pad/process

τh1

h1 a1 a2 eρ a3⁄–

⋅+=


Boning 48 MIT-MTL

Results: Integrated Density/Step Height Model

0 10 20 30 40 50 600.5

0.6

0.7

0.8

0.9

1

1.1

1.2

1.3

ActualModel

0 10 20 30 40 50 601.5

1.55

1.6

1.65

1.7

ActualModel

Raised Area Predictions

Th

ickn

esse

s (µ

m)

Site # Site #

Down Area Predictions

Th

ickn

esse

s (µ

m)

RMSE = 98Å RMSE = 83Å

■ Dramatically reduced errors: ❏ 273 Å rms (density model) --> 98 Å RMSE (integrated model)

■ Challenge:❏ Over-predicts down polish in low density regions: macro pad bending limit?

Smith et al.,CMP-MIC ‘99


Boning 49 MIT-MTL

Model Generalization for Copper CMP

bulk

OxideErosion

MetalDishing

Stage 1 copperremoval

Stage 2 barrierremoval

Stage 3

over-polish

■ Approach: Extend density/step-height model to each stage in the copper polish process

■ “Removal Rate” Diagrams:❏ Track RR for metal and oxide

during each phase

■ Approximation: neglect barrier removal phase


Boning 50 MIT-MTL

Removal Rate Diagrams

hexh

RRm

1 ρm–---------------

down areaRRm

up area

Removal

Local

Rate

StepHeight

RR

metal rate

metal rate

time

dss

metal

oxide

Removal

Metal

Rate

DishingHeight

RR

rate

rate

time

RRm

)

RRox

)

RRox

1 ρm–---------------

)

dmax dm

Stage 1 - Bulk Metal Polish Stage 3 - Metal/Oxide Overpolish

❏ Key idea: RR as f(step height)

❏ Use a contact height hex

❏ Density affects up area Cu rate

❏ Key idea: RR as f(dishing height)

❏ dmax is max dishing (pad loses contact)

❏ dss is steady state dishing (Elbel)


Boning 51 MIT-MTL

Dishing and Oxide Removal Rate Dependencies

W

Maximum

Metal

Dishing

LineWidth

dmax

S*

OxideSpaceWidth

RRox

)

S

dmax Depends on Line Width RRox Depends on Line Space

❏ dmax relates to pad contact

❏ Function of metal width (or density)

❏ Derive from contact mechanics

❏ Capture additional acceleration (beyond density) for thin oxide spaces

❏ For large space RR = blanket oxide rate

Effective OxideRemoval Rate

RRox


Boning 52 MIT-MTL

Metal (Copper) CMP - Electrical Test Mask

■ Physical (profilometry, AFM) arrays to study dishing and erosion

■ Electrical (resistance) test structures❏ E-test extraction of line loss

❏ Applicable to very fine pitch structures

■ Design as a function of density and pitch (or density, linewidth, linespace)

■ Variations and experiments in progress in collaboration with Sematech, TI, Applied Materials


Boning 53 MIT-MTL

Current Status: Extraction/Validation of Model

PITCH BLOCKS

DENSITY

BLOCKSDENSITY

BLOCKS

240 270 300 330 360 390 4200

0.2

0.4

0.6

0.8

1

Remaining Cu Thickness (µm)

Polish Time (sec)

10%30%50%70%90%

MetalDensity

o = Extracted* = Physical

Extraction ofElectrical/PhysicalTest Mask Pattern Dependencies

❏ Test structure & mask design

❏ Methodology development

❏ Extract model parameters for time evolution & pattern dep. effects

❏ Validate dishing and erosion trends and dependencies


Boning 54 MIT-MTL

Conclusions■ Standards needed for Characterization of Pattern Dependencies in CMP

❏ Key Idea #1: Characterization using Test Masks and Test Patterns

❏ Key Idea #2: Planarization Length as Metric for Oxide CMP

✔ Mask Evolution ❏ leading to “Comprehensive Dielectric CMP Characterization Mask”

✔ Oxide CMP Model -- Effective Density

✔ Planarization Length as a Metric

■ Future Issues❏ Characterization masks, methods and metrics for metal CMP still needed


Boning 55 MIT-MTL

Profi lometry (Cont.)

■ Wafer warpage and profilometry stage bias can be eliminated using combined optical/profilometry techniques.

Profilometry (Before Correction)

Profilometry (After Correction)

Optical Measurements

Documents

Characterization Methods and Metrics for Patterned Wafer CMP