Reducing Ultra-High-Purity (UHP) Gas Consumption By Characterization of Trace Contaminant Kinetic and Transport Behavior in UHP Fab Environments
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1 Reducing Ultra-High-Purity (UHP) Gas Consumption By Characterization of Trace Contaminant Kinetic and Transport Behavior in UHP Fab Environments Customized Project; Sponsored by Intel Graduate Students : Roy Dittler: Ph.D. student, Chemical and Environmental Engineering, UA Hao Wang: Ph.D. student, Chemical and Environmental Engineering, UA J. K. Jhothirama: Ph.D. student, Chemical and Environmental Engineering, UA PI: Farhang Shadman, Chemical and Environmental Engineering, UA Co-PI: Carl Geisert, Sr. Principal Engineer, Intel 1
2 Back Diffusion Sources and Mechanisms Line A P A >P B = No Risk of Contamination Line B 2
3 Back Diffusion Sources and Mechanisms 3
4 Objectives Develop operational parameters that will minimize back diffusion of impurities into fluidic distribution systems. Develop and validate a process simulator that can help industry design and operate systems while minimizing back diffusion, gas usage, and system dead volumes. Develop a better understanding of back diffusion since little is known or has been published on the subject. Motivation and ESH Impact Contamination of gas distribution systems during normal operation results in major wasting of materials, energy, and valuable tool operation time. 4
5 Lateral Zero Gas Line Experimental Testbed Laterals Added to the Main Line P Gas Delivery System P Calibration Line 2-way Valve MFC 4 Flow-restrictor APIMS CRDS MFC 3 MFC 2 Permeation Tube Moisture Impurity Source Moisture Analyzers MFC 1 Houseline N 2 Calibration Loop CRDS: low ppb low ppm APIMS: sub ppb low ppb Gas distribution systems with different sizes and geometries were fabricated and provided by Intel Multistage Gas Purifier System 5
6 Back Diffusion Process Simulator 6
7 Gas phase moisture concentration, Cg (ppb) Process Simulator Verification Simulator Prediction Experimental Results Model Prediction psia, lateral length of m Volumetric flow rate through lateral, Q 3 (liters/min) 7
8 Gas Phase Moisture Concentration, Cg (ppm) Laminar to Turbulent Flow Transition 800 Parametric Studies Effect of Flow Rate on Gas Phase Moisture 95 psia, lateral length of m Laminar Turbulent E-4 1E-3 1E-2 1E-1 1E+0 1E+1 1E+2 Volumetric Flow Rate in Lateral, Q3 (Liters/min) 8
9 Gas Phase Moisture Concentration, Cg (ppm) 1E+4 Parametric Studies Effect of Lateral Length on Gas Phase Moisture 95 psia, 1/16 th inch OD 1E+3 Re = 4Q 3 νπd lateral L 3.0 L % = 300% increase in lateral length 1E+2 1E+1 Q 1.0 Q 3.0 Q % = 67% reduction in gas usage 1E+0 1E-1 1E-2 1E-3 Re=30000 Re=20000 Re= Lateral Length, L (meters) 9
10 Gas Phase Moisture Concentration, Cg (ppb) 3.5E+6 Parametric Studies Effect of Lateral Diameter on Gas Phase Moisture 3.0E+6 2.5E+6 2.0E+6 Turbulent flow occurs below the line 1.5E+6 1.0E+6 5.0E lpm 7.6 lpm 15.3 lpm 30.6 lpm 95 psia L= m 0.0E+0 1.0E-3 1.0E-2 1.0E-1 1.0E+0 Lateral Diameter, d (meters) 10
11 Gas Phase Moisture Concentration, Cg (ppm) Laminar to Turbulent Flow Transition 800 Parametric Studies Effect of Reynolds Number on Gas Phase Moisture 95 psia, lateral length of m Re = U 3d lateral ν = Convective Transport Viscous Transport E-1 1E+0 1E+1 1E+2 1E+3 1E+4 1E+5 1E+6 Reynolds Number, Re 11
12 Gas Phase Moisture Concentration, Cg (ppm) Laminar to Turbulent Flow Transition 800 Parametric Studies Effect of Peclet Number on Gas Phase Moisture 95 psia Pe = U 3L D e = Convective Transport Effective Dispersive Transport Peclet Number, Pe 12
13 Gas Phase Moisture Concentration, Cg (ppb) 1E+6 Parametric Studies Effect of Peclet Number on Gas Phase Moisture 95 psia EXAMPLE 1E+5 1E+4 1E+3 1E+2 Pe = U 3L D e = 4Q 3 L 2 πd lateral D e Q 3 = 5. 0 liter min d lateral = 1 4 inch D e (intrinsic, extrinsic) = 0. 8 m2 sec 1E+1 1E+0 Turbulent Flow Regime L = 4. 5 meters 1E-1 1E Peclet Number, Pe Pe
14 Back Diffusion Process Simulator: Orifice Addition z = 0, D m C g atm C g t = Q 3 A ori C g 14
15 Gas Phase Moisture Concentration, Cg (ppb) Orifice Addition to Simulator 25 Kinetic Molecular Theory of Gases Falls Apart 20 D D m 15 Impurity 10 Orifice C g Q ori A ori 5 C g D t Q ori A ori Orifice Characterization Constant, D/t (m/s) 15
16 Gas Phase Moisture Concentration, Cg (ppb) Orifice Impact on Design and 10 Operational Parameters micron Orifice EXAMPLE Q 3 = 5. 0 liter min d lateral = 1 4 inch 0.1 D e (intrinsic, extrinsic) = 0. 8 m2 sec 0.01 Pe = U 3L D e = 4Q 3 L 2 πd lateral D e L = 0. 7 meters Pe Peclet Number, Pe 16
17 Simulation: 1 Position in Main Header (meters) 17
18 Simulation: 2 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 18
19 Simulation: 3 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 19
20 Simulation: 4 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 20
21 Simulation: 5 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 21
22 Simulation: 6 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 22
23 Simulation: 7 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 23
24 Simulation: 8 Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 24
25 Simulation: 9 Contamination Source Contamination Source Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 25
26 Simulation: 10 Contamination Source Contamination Source Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 26
27 Gas Phase Moisture Concentration, Cg (ppb) Compounding Effect of Multiple Sources 1.4E-2 of Impurity 1.2E-2 1.0E-2 8.0E-3 6.0E-3 Why not a flat line? 4.0E-3 2.0E-3 Lateral locations (Source of Impurity) Higher Peclet Number 0.0E Position in Main Supply Line, x (meters) 27
28 Gas Phase Moisture Concentration, Cg (ppb) Compounding Effect of Multiple Sources 6.0E-3 of Impurity 5.0E-3 4.0E-3 Why not a flat line? 3.0E-3 2.0E-3 1.0E-3 Lateral locations (Source of Impurity) 0.0E Position in Main Supply Line, x (meters) 28
29 Simulation: 11 Tool Contamination Source Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 29
30 Simulation: 12 Tool Contamination Source Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 30
31 Simulation: 13 Tool Contamination Source Gas Phase Moisture Concentration, Cg (mol/m 3 ) Position in Main Header (meters) 31
32 Highlights The experimental approach allowed for the observation of back diffusion in an adjustable and controllable manner. The process model accurately predicted experimental results and was invaluable in performing parametric studies. The moisture contamination due to back diffusion was a strong function of lateral diameter, length, and gas flow rate through the lateral. Characteristic groups were identified that allowed us to present generalized correlations that would help in the design and operation of UHP fluidic systems being exposed to a source of contamination This methodology was expanded to include an orifice and lateral in series and was effective in determining a design approach that will safeguard against the back diffusion of impurities into both bulk and process gases. The simulator showed flexibility in regards to being able to predict contaminant transport in systems with multiple sources of contamination as well as predicting the impact of such contamination on neighboring tools. 32
33 Industrial Interactions and Future Plans Continue our work with Intel on novel impurity control strategies to reduce gas usage Making the process simulator available to industry Extending the present study to other fluids, contaminants, and components Carl Geisert, Intel Tiger Optics support team Acknowledgements 33
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