paradigms shifts in cmp - nccavs usergroups€¦ · paradigm shifts in cmp 2 state of cmp market...

Paradigms Shifts in CMP Daniel Redfield Director - NMA

CMPUG - Semicon West 2018

External Use

Para

digm

Sh

ifts

in C

MP

2

State of CMP Market Inflections are driving CMP Growth and Complexity

Paradigm Shifts in CMPStrategies to address CMP Complexity

SMART CMPTailored CMP Pads

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NAND

3D NAND► More W & oxide CMP► CMOS Under Array► Stacked Cells► Multi-Material Polish

LOGIC

3D Transistor: FinFET Co contact & local interconnect 3D Multi Patterning

► SA Gate Contact

Large Die Form Factors► GPU

5

CMP Enabled Inflections

ADVANCED PACKAGING

Wafer Level Packaging► Image Sensors► Redistribution Layer (RDL)► Through Silicon Via (TSV)

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5

10

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20

25

30

1 2 3 4

Relat

ive N

o of

CMP

Pas

ses

0

10

20

30

40

50

60

1 2 3 4 5

Relat

ive N

o of

CMP

Pas

ses

3D NANDGen 1

3D NANDGen 3

3D NANDGen 2

2.5D Si INTERPOSER

3D DRAM

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How will we use AI enabled SMART CMP?

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CMP Input Parameters.

Hardware MaterialsEndpoint Pressure/Velocity

Chemistry Delivery Temp. Control

Slurry Pad

Conditioner Retaining Ring

Polymer

GroovePore

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Open Loop CMP

Stability achieved through reduced Input Parameter variability.

Static Process Recipe

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Input Output

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Property Input Change

Dynamic Process Control

Static Process Recipe

Process Controlled CMP

Performance improved through Dynamic Process Control of Input Parameters.CMPUG Semicon West 2018 -External Use

Input Output

Output

Dynamic Process Control (Property + AI)

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Property Input Change

AI Augmented Process Controlled CMP

AI has the promise of optimizing output through the interpolation of multiple Input Parameters.CMPUG Semicon West 2018 -External Use

Input Output

Output

Warning with regards to AI Processing

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Output success is a function of algorithm training.

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CMP Process Optimization

CMP Polish process versatility continues to enable new integration schemes.

Die Layout

Polish Inputs

Layout Opt.Dummy Fill

Polish Process

Hardware Input Mod.

MaterialsInput Mod.

Performanceto Specification

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Each Process Input has a Structure/Property Model

Hardware MaterialsEndpoint Pressure/Velocity

Chemistry Delivery Temp. Control

Slurry Pad

Conditioner Retaining Ring

Polymer

GroovePore

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10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1 100

Die level5-20mm

Wafer300mm

Log Scale(m)

Feature Arrays25-3000 m

Device Features10 nm

Cell Periphery

CMP Pad Structure/Property Input Parameters

Critical Length ScalesCMPUG Semicon West 2018 -External Use15

Pad Porosity10-50 m

Polymer Chains50-100 nm

10-9 10-8 10-7 10-6 10-5 10-4 10-3 10-2 10-1 100

Die level5-20mm

Wafer300mm

Log Scale(m)

Pad Groove100-500 m

Feature Arrays25-3000 m

Device Features10 nm

Pad Rebound10-100 mm

Polish Element 0.5-3 mm

Cell Periphery

Polymer Domains500-5000 nm

CMP Pad Structure/Property Input Parameters

Structure/Property relationships can be deployed to design locally optimized CMP pads.CMPUG Semicon West 2018 -External Use16

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CMP Pad Input Parameter Optimization

Inputs validated against Outputs. Results are developed into Pad Structure/Property Algorithms.

Domain

GroovePore

Feature Pad Rebound

Polymer Chain

Polish Process

Structured DOE

Baseline Polish Recipe

Experimental Inputs

Fixed Inputs

Pad Property Inputs

Per

form

ance

Out

put

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CMP Pad Design Optimization

Rigorous Modeling efforts allow for targeted optimization of CMP Inputs and improvementto Die level Performance Outputs.

Domain

GroovePore

Feature Pad Rebound

Polymer Chain

Polish Process

Structured DOE

Baseline Polish Recipe Pad Property Inputs

Per

form

ance

Out

put

Experimental Inputs

Fixed Inputs

Pad Input Model

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Dynamic Process Control

SMART CMP

SMART CMP: Input Parameter Model optimized AI deployed using Dynamic Process Control.

AI Input Models

SMART CMP

Domain

GroovePore

Feature Pad Rebound

Polymer Chain

Polish Process

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