TY - JOUR
T1 - Multiscale optimization using hybrid PDE/kMC process systems with application to thin film growth
AU - Varshney, Amit
AU - Armaou, Antonios
N1 - Funding Information:
Financial support for this work from the Department of Chemical Engineering, Pennsylvania State University is gratefully acknowledged. The authors would also like to thank Professor Costas Maranas for providing the necessary computational resources.
PY - 2005/12
Y1 - 2005/12
N2 - The problem of optimal time-constant and time-varying operation for transport-reaction processes is considered, when the cost functional and/or equality constraints necessitate the consideration of phenomena that occur over disparate length scales. Multiscale process models are initially developed, linking continuum conservation laws with microscopic scale simulators. Subsequently, order reduction techniques for dissipative partial-differential equations are combined with adaptive tabulation of microscopic simulation data to reduce the computational requirements of the optimization problem, which is then solved using standard search algorithms. The method is applied to a conceptual thin film deposition process to compute optimal substrate-surface temperature profiles that simultaneously maximize film-deposition-rate uniformity (macroscale objective) and minimize surface roughness (microscale objective) across the film surface for a steady-state process operation. Subsequently, optimal time-varying policies of substrate temperature and precursor inlet concentrations are computed under the assumption of quasi-steady-state process operation.
AB - The problem of optimal time-constant and time-varying operation for transport-reaction processes is considered, when the cost functional and/or equality constraints necessitate the consideration of phenomena that occur over disparate length scales. Multiscale process models are initially developed, linking continuum conservation laws with microscopic scale simulators. Subsequently, order reduction techniques for dissipative partial-differential equations are combined with adaptive tabulation of microscopic simulation data to reduce the computational requirements of the optimization problem, which is then solved using standard search algorithms. The method is applied to a conceptual thin film deposition process to compute optimal substrate-surface temperature profiles that simultaneously maximize film-deposition-rate uniformity (macroscale objective) and minimize surface roughness (microscale objective) across the film surface for a steady-state process operation. Subsequently, optimal time-varying policies of substrate temperature and precursor inlet concentrations are computed under the assumption of quasi-steady-state process operation.
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U2 - 10.1016/j.ces.2005.05.055
DO - 10.1016/j.ces.2005.05.055
M3 - Article
AN - SCOPUS:27144471786
SN - 0009-2509
VL - 60
SP - 6780
EP - 6794
JO - Chemical Engineering Science
JF - Chemical Engineering Science
IS - 23
ER -