parallel dsmc gas flow simulation of an in-line coater for

Pfl, Sie, Szy 2006-09-20

FraunhoferInstitutSchicht- undOberflächentechnik

Andreas Pflug, Michael Siemers, Bernd Szyszka

Fraunhofer Institute for

Surface Engineering and Thin Films IST

Bonn,

September 20, 2006

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Parallel DSMC Gas flow Simulation of an In-line Coater for Reactive Sputtering

Pfl, Sie, Szy 2006-09-20


1. Introduction

2. Details of parallel DSMC implementation

3. DSMC model of an in-line coater

4. 3D Gas flow simulation with moving

glass substrates

5. Conclusion

Outline

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


1. Introduction




glass substrates

5. Summary and outlook

Outline

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


Reactive magnetron sputteringSketch of an in-line sputtering compartment and a magnetron

Magnetron Compartment of an in-line sputtering coater

Introduction / Motivation

N S S N N S S N+ / - - / +

to MF generator

Transport system

Glass substrate

Shielding Shielding

Vacuum Vacuum

Gas inlete. g. Ar, O , ...2

Target-Material

Gas inlete. g. Ar, O , ...2

N S S N

B B

E E E

a) Cross section through a magnetron sputtertarget

b) Erosion track on target surface

Pfl, Sie, Szy 2006-09-20


Goals for simulation of reactive magnetron sputtering

� Process stability - Feedback control for non-stable transition mode- Coupling of magnetrons- Pumping speed, noise and latency times

� Homogeneity - Lateral homogeneity: influence of substrate movement- Vertical homogeneity: magnetron drift current

� Productivity - Fast access of operation conditions after maintenance or product change


Pfl, Sie, Szy 2006-09-20


Concept of DOGMADynamic, spatially resolved, coupled, macroscopic model

Monte Carlosimulation

DSMC - Gas flow

Monte Carlosimulation

PIC-MC plasmaSputter particles

Balance between surface and volume

Berg‘s Model1986

Surfacechemistry

Pressuredistribution

Surface metallization

Flowconductances

Time consumingMC calculations(initial step)

Runge-Kutta integration (fast!)

Heuristic modelof the plasmaimpedance


�� A. Pflug et al.; Thin Solid Films 442(2003) 21-6.

Pfl, Sie, Szy 2006-09-20


Gas flow modelsPressure regimes

(nach Bird 94)

Kn = /dλ

100.10.01 1.0 100 ∞0

Navier StokesEuler

Boltzmann transport equationBoltzmann transportequation withoutcollision treatment

Typical processconditions

Limit of free particles

Fluid limit

DSMC Method

FEM flow simulation

�� G. A. Bird, Molecular gas dynamics and the direct simulation of gas flows, Oxford Engineering Science Series 42 (1994)


Pfl, Sie, Szy 2006-09-20


»Direct Simulation Monte Carlo« (DSMC) - Method

� Introduced by Bird, 1981

� Statistically obtained solution of theBoltzmann transport equation incl. collision term

� Especially suited for low pressureand high velocity� Simulation of turbo blades� Satellite reentrance into earth atmosphere

� With increasing pressure the computationaleffort rapidly increases (~ p2…p4)

� Fraunhofer IST: 3D parallel implementationbased on domain decomposition. Capable of multiple particle resolutions.

720.0 710.0 700.0 690.0 680.0 670.0 660.0 650.0 640.0 630.0 620.0 610.0 600.0

x

z

x

y

Argon partial pressure [mPa]

TwinMagtargets To pumps in

next module

Substrate holder

y

z


Pfl, Sie, Szy 2006-09-20


1. Introduction




glass substrates


Outline

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


»Direct Simulation Monte Carlo« (DSMC) - method

Details of parallel DSMC implementation

Cube

Tube_A

Tube_Bconnecting surfacebent in 3D

planar surface

planar surfacex

z

y

n = 10x

n =

3y

n =

6z

Lx

Lz

L y

z

n =

4z

Lz

r2

r1

nr = 4n = 12ϕ

a) Volume elements

b) Connections between volume elements

GeometrySchedule

Initialization

Time cycles

MovementCollisionPumpingNew particles

Averaging cycles

Evaluation

Super particlesMaxwellian distribution

Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeOverall layout of software framework


RIG-VM DSMC MasterRIG-VM API

DSMC Worker

DSMC Worker

DSMC Worker

DSMC Worker

libc

PVM3 API

Particleexchange

Object orientedscripting language

with a C style syntax

Sub class ofRIG-VM

RIG-VMAPI

PVM3API

Particleexchange

Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeLayout of worker processes

DSMC_Base

DSMC_Volume DSMC_Border DSMC_SVT

DSMC_CylinderJunction

DSMC_Quad

DSMC_Cone

DSMC_Diffuse_Border

DSMC_Specular_Border

DSMC_Open_Border

DSMC_Outlet_Border

DSMC_Combined_Border

Further volume types

Transformation between3D volume coordinates and2D surface coordinates(one class for each combination)

� Object oriented, C++

� Abstract base class for- Border type- Volume element

(geometry)

� Further geometricvolume elements andborder types can easilybe added withoutloss in performance


Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeGeneral parallelization scheme


Master

Worker 1

Worker 2

Worker 3

Worker 4

PVM messages

Time axis

Perform task

Perform task

Perform task

Wait for 'DSMCC_SUCCESS'

RIG-VM interpretercalls method ofDSMC-master module

Further proceeding of RIG-VMscript

Perform task

PV

M m

ess

ag

es

Su

cess

co

de

DS

MC

C_S

UC

CE

SS

Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeParallelization scheme – Particle transfer between workers


� Particle transfer shouldbe handled solely between workers, i. e. should be invisiblefor the master

� Within a fixed time

step δt, a particle trajectory could spanover multiple workers (see right graph)

� The main problem fora worker is finding out the right moment to say‘DSMCC_SUCCESS’

Typical particle transfer scenarios in a DSMC setup consisting of three worker tasks A-C

p1

A B

C

p2

Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeParallelization scheme – Asynchronous particle exchange


Active state Waiting state

Particle generation

Collision treatment

Particle Movement

NS==0?

NS particles are sent to neighbour

processes via

Send

to master

Yes

Switch to waiting state

Pfl, Sie, Szy 2006-09-20


Parallel DSMC codeParallelization scheme – Asynchronous particle exchange


p1

A B

C

p2

Master

A

B

C

Command

Time axis

Move, one particlehas stopped

Wait fortwo particles

Move, transfer twoparticles, remember: n=2 n=1

Receive: 1

Move, stop-> n=0

Move, wall collision, move, transfer one particle

Move, notransfer

Wait for 'DSMCC_SUCCESS'

Move, notransfer

Pfl, Sie, Szy 2006-09-20


1. Introduction




glass substrates


Outline

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


In-line coater at Applied Materials (former Applied Films) Sketch of compartments M5-M11

M11(Empty)

M10(Pumping)

M8(Pumping)

M7(Empty)

M6(process)

M5(pumping)

M9

3x TurboLeybold 1600



0.7 m 0.7 m 0.7 m 0.7 m 0.6 m 0.6 m 0.6 m

To load lock in M1Moving glass substrate

Substrate size: 1.0 x 3.21 m²

Dual rotatables

Glass transport system Gas inlet

»BigMag« experimental inline coater- Compartment width: 4.35 m (same as for »Jumbo sized« substrates)- 7 Compartments à 0.6 m length- 4 Compartments à 0.7 m length- Total length ~ 8 m

DSMC model of an in-line coater

Pfl, Sie, Szy 2006-09-20


In-line coater at Applied Materials (former Applied Films)View into sputter compartment M9»BigMag« – M9

• Compartment widthof 4.35 m

• Gas inlet is hiddenbeneath shielding

• Connection to pumpingcompartments via 20rectangular orifices,left and right.

• Different target typescan be mounted

Slits for pumping of sputter compartment

Shielded gas inlet system

M9M8 M10


Pfl, Sie, Szy 2006-09-20


Domain decomposition in XY plane

332x43.753x11.9 49.5 x

29.5

HGRG

44 .7x17.9

438x26.353x11.9

RGHG49.5 x29.544.7x17.9

MM

MG

74x11 0

53x9.470 .5x9.4

BL_ABL_B

BL_F

74x110

53x9.470.5x9.4

B R_AB R_B

BR_F

680x306

20 x 60(x 150 in z-dir ection)

700 x16

680x306

700x16

510*138

MO

85x103

LO RO85x103

123x9.4 BL_E17.5118x9 .4 BL_D17.5

119x 9.4 BL_C17.517.5

39

*85

.6

BL_G

20 x 60(x 150 in z direction)

123x9.4BR _E 17.5118x9.4BR_D 17.5

119x9.4BR_C 17.5

39

*85

.6

BR_ G

34 40 3440

23x23

172.5 x 23172.5 x 23 U9_UMU9_UL U9_UR

115.5 x 100 115.5 x 100

U9_L

U8U5

700 x16 OG_9 OG_8OG_10

U9_2: 33x10 U9_3: 3 3x10

U9_OM: 267 x27U9_123x32

U9_R

U9_423x32 U98_A

30.5x3 0

U8_R95x100

U9

8_

BU

98_

C

U9_OR: 148.5 x5

81.2x9.4BL_J62.0x9.4BL_I

BL_H

170.7x9.4147.4x9.4

KGKF

125.1x9.4 KE

8 8.7x85.6

K D

d = 220 m m

81.2x9.4 BR_J62 .0x9.4 B R_I

BR_H

170.7x9.4

147.4x9.4125.1x9.4

KA

KCKB

Gla

sssu

bstra

te

221 x 77

335 x 23

U9_M

U7U6

49.2x9.4 49.2x9.4

x

y

Sputter compartment M9M10 M8


Pfl, Sie, Szy 2006-09-20


Domain decomposition in YZ plane


ZP3 ZP2 ZP1 ZM ZV1 ZV2425 300 600 1700 600 300

150

25 7537.5

ZV3425

ZP1 ZPM ZV1600 1700 600

ZP2275

ZV2275

Area of glass substrate transport

ZP3450

ZV3450

Area between transport rolls

Connecting slots between M8-M9 and M9-M10

z

y

Area above glass substrate

DSMC gas flow model comprises- Total volume of 7.5 m³- 1005 Volume elements

Pfl, Sie, Szy 2006-09-20


1. Introduction




glass substrates


Outline

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


DSMC implementation dataLinux cluster at Fraunhofer IST

3D Gas flow simulation with moving substrate

Implementation details

� Linux cluster with 5 nodes à 2 Opteron-250 (2.4 GHz) processorsand GBit ethernet

� 4 GB (8x512 MB) of memory for each node

� Debian sarge, g++ 3.3.5, pvm 3.4.1

� Time cycle = 2.5x10-5 s

� 150000 cycles for first glass position

� 25000 cycles for each of 56 subsequent glass positions (+10000 cycles for time averaging)

� Approx. 106 simulation particles in total

Pfl, Sie, Szy 2006-09-20


DSMC model of BigMag coaterPressure distribution around sputter compartment M9

180.0 170.0 160.0 150.0 140.0 130.0 120.0 110.0 100.0 90.0 80.0 70.0 60.0

Argon-Druck [mPa]

M10 M9 M8

Ohne Glassubstrat


Without glass substrate

Pfl, Sie, Szy 2006-09-20


DSMC model of BigMag coaterInfluence of glass substrate

180.0 170.0 160.0 150.0 140.0 130.0 120.0 110.0 100.0 90.0 80.0 70.0 60.0

Argon-Druck [mPa]

M10 M9 M8

Mit GlassubstratWith glass substrate


Pfl, Sie, Szy 2006-09-20


Substrate movementInfluence of substrate movement on total pressure in M10Simulation vs. Measurement

• Good agreement betweensimulation and experiment

• Experimental values takenfrom coign of chamberM10

• Absolute values of pressure measurements are verydifficult to obtain

0.0 0.5 1.0 1.5 2.0

121

122

123

124

125

126

127

128

Deposition range

BigMag-Logfile:

Si3N

4 deposition

Ionivac BAG 100 in M10

scaled by factor 1/2.79

DSMC simulation in M10

(Ar pressure)

Pre

ssu

re [

mP

a]

Glass front position [m]


Pfl, Sie, Szy 2006-09-20


DSMC model of BigMag coaterLoad balancing


ηηηη Speedup[%]

Time for 1000 cycles [s]

ηηηη Speedup[%]

Time for 1000 cycles [s]

371183014510

40122381279

49114361528

51122421487

52141431696

58150412135

64170452414

67219572553

2

1

M

8127274297

438438

Load balance by averaged CPU clock() results

Load balance by number of particles

Load balance� Equally distributed

load per process� Load can be either

estimated from totalnumber of particlesor measured via theclock() function duringtest cycles

� Auxiliary condition:Minimizing the numberof communication paths over network(typically 2000�200)

� »Simulated Annealing«

Pfl, Sie, Szy 2006-09-20


Substrate movementHeuristic simulation of resulting film thickness profile

Heuristic simulation ofreactive magnetronsputtering

• Simplified model ofthe whole process

• Model of in-line coateruses 2D pressure distribution averagedalong target direction(z-Axis)

�� Pflug et al., Proc. 47th SVC Tech. Conf. (2004) 155-60.

�� Pflug et al.; Proc. 49th SVCTech. Conf. (2006) 14-20.


Location x on substrate [m]~

Re

lativ

e t

hic

kn

ess

de

via

tio

n

t /

t [%

]∆

_

0.0 0.2 0.4 0.6 0.8 1.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5 Heuristic model Reactive ZnO, 11.02.2004, center Reactive SiO

2, 16.06.2004, center

Pfl, Sie, Szy 2006-09-20


3D gas pressure distributionPhase shift at different positions within chamber

xx x xx

0.0 0.5 1.0 1.5 2.00.166

0.167

0.168

0.169

0.170

0.171

0.172

0.173

0.174

0.175

0.176

0.177

0.178

0.179

0.180

0.181

Arg

on

pre

ssu

re [

mP

a]

Position of glass front [m]

Segments

ZP3 / ZVP

ZP1 / ZV1

ZM

ZP3 ZP2 ZP1 ZM ZV1 ZV2425 300 600 1700 600 300

150

25 7537.5

ZV3425

ZP1 ZPM ZV1600 1700 600

ZP2275

ZV2275

Glass substrate

ZP3450

ZV3450

Upper area

Lower area

Connecting slotsbetween compartments

z

y

� “Phase shift” in gaspressure distributionbetween differentpositions along targetaxis.


Pfl, Sie, Szy 2006-09-20


1. A high precision parallel DSMC code forrarefied gas flow simulation has been developed at Fraunhofer IST

2. The DSMC code has been applied to an in-linecoater with a moving substrate

3. The simulation is in good agreement with pressuremeasurements. A 2D heuristic model derived from theDSMC simulations is partially capable of describing the resulting film thickness distribution on substrate

4. In many cases a 2D heuristic model is not an appropriate description for large in-line coaters. This is most probably caused by the phase shift in theXZ-pressure distribution between different locationsalong target axis

Summary

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


1. Network latency of GBit ethernet cards seems to be a significant limitation. This willbe further investigated.

2. A PIC-MC plasma simulation system has been implemented based on the parallel DSMC code �� M. Siemers et al.,

Proc. 49th SVC Tech. Conf. (2006) 60-63.

Outlook

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


Thank you very much for your attention!

This work has partially been funded by

Bundesministerium für Bildung und Forschung (BMBF) and

VolkswagenStiftung Hannover

49th Annual SVC Technical Conference 2006

Pfl, Sie, Szy 2006-09-20


Backup slides

Euro-PVM/MPI 2006, Sept. 17-20, 2006

Pfl, Sie, Szy 2006-09-20


Low-E coatings: Demand on film thickness homogeneityInfluence of film thickness deviations for double-Ag-low-E

0.50

0

-0.50

-1.0

1.0

-1.5

1.5

-2.0

2.0

-2.5

2.5 -3.0

3.0

-3.5

3.5

-4.0

43 44 45 46 47 48

74

75

76

77

78

79

1 nm

d1 [nm]

d2 [

nm

]

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.50

0

0.50 1.0

1.52.0

2.53.0

3.54.0

43 44 45 46 47 48

74

75

76

77

78

79

d1 [nm]

d2 [

nm

]

Float

SnO2

ap

pro

x. 1

80

nm

AgNiCrOx

d3

d2

d1

dAg + dNiCrOx = 9 nm

Example:SnO2 based double-Aglow-E stack

Demand on large area coatings:(substrate size: 6.0*3.21 m²)

��

Dependency of color coordinates a*, b* on thickness


Pfl, Sie, Szy 2006-09-20


»Direct Simulation Monte Carlo« (DSMC) - method Overall calculation schedule

Details of parallel DSMC imlementation

Geometry Volume elements

Initial particle distribution

Boundary surfaces and pumping

Particle movement

during interval [ , + ]t t tδ

Collision treatment

during interval [ , + ]t t tδ

Newparticle

generation

Initialisation

Mesh of sub cells

Time cycles Evaluation

Data loggi ng(every m steps)

N time cycles = 10 ...10 sδt -4-7

Save final state (= velocitiy, coordinates of each simulation particle) in to state file

Averaged net flows of particles

Density

Averaged velocitycompon ents <v >, <v >, <v >

x y z

Averages squarevelocity <v >2

Perform N cycles of time averagingavg

Species and collision parameters

Random (Maxwellian distribu tion)

Restore from state file

Results

parallel dsmc gas flow simulation of an in-line coater for

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