DocumentCode
2479005
Title
Optimal design and operation of a multiscale GaAs/AlAs deposition process
Author
Behrens, Christopher M. ; Armaou, Antonios
Author_Institution
Dept. of Chem. Eng., Pennsylvania State Univ., University Park, PA, USA
fYear
2009
fDate
10-12 June 2009
Firstpage
4785
Lastpage
4790
Abstract
We consider optimal operating conditions of a gallium arsenide/aluminum arsenide (GaAs/AlAs) deposition process with objectives of uniform deposition of the film heterostructure across the wafer surface at the macroscopic scale and the interfacial uniformity of the GaAs/AlAs heterostructure at the microscopic scale. We use a finite element solver to determine macroscale solutions and kinetic Monte Carlo (kMC) techniques to determine the mesoscale solution of the problem.We characterize the interfaces between species and apply the simulation methodology to a multiscale optimization framework to minimize the interfacial step densities while also minimizing temperature, annealing time, and maximizing thickness uniformity. The design variables are temperature, annealing time, precursor concentration, and input velocity. In order to reduce the prohibitive computational expense of the function evaluations, we employ an in situ adaptive tabulation scheme around the mesoscale inputs. The resulting optimization problem combined with this methodology becomes computationally tractable, and is able to increase the thickness uniformity and maintain low interfacial step densities.
Keywords
III-V semiconductors; Monte Carlo methods; aluminium compounds; annealing; finite element analysis; gallium arsenide; interface structure; semiconductor thin films; GaAs-AlAs; aluminum arsenide; annealing; film heterostructure; finite element solver; gallium arsenide; interfacial step density; interfacial uniformity; kinetic Monte Carlo techniques; multiscale deposition process; multiscale optimization framework; wafer surface; Aluminum; Computational modeling; Finite element methods; Gallium arsenide; Kinetic theory; Microscopy; Monte Carlo methods; Optimization methods; Simulated annealing; Temperature;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2009. ACC '09.
Conference_Location
St. Louis, MO
ISSN
0743-1619
Print_ISBN
978-1-4244-4523-3
Electronic_ISBN
0743-1619
Type
conf
DOI
10.1109/ACC.2009.5160734
Filename
5160734
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