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Título

Particle swarm optimization-based continuous cellular automaton for the simulation of deep reactive ion etching

AutorLi, Yuan; Gosálvez, M. A. ; Pal, Prem; Sato, K.; Xing, Yan
Palabras claveSimulation
PSO-CCA method
Deep reactive ion etching
Particle swarm optimization
Continuous cellular automaton
Fecha de publicación2015
EditorInstitute of Physics Publishing
CitaciónJournal of Micromechanics and Microengineering 25: 055023 (2015)
ResumenWe combine the particle swarm optimization (PSO) method and the continuous cellular automaton (CCA) in order to simulate deep reactive ion etching (DRIE), also known as the Bosch process. By considering a generic growth/etch process, the proposed PSO-CCA method provides a general, integrated procedure to optimize the parameter values of any given theoretical model conceived to describe the corresponding experiments, which are simulated by the CCA method. To stress the flexibility of the PSO-CCA method, two different theoretical models of the DRIE process are used, namely, the ballistic transport and reaction (BTR) model, and the reactant concentration (RC) model. DRIE experiments are designed and conducted to compare the simulation results with the experiments on different machines and process conditions. Previously reported experimental data are also considered to further test the flexibility of the proposed method. The agreement between the simulations and experiments strongly indicates that the PSO-CCA method can be used to adjust the theoretical parameters by using a limited amount of experimental data. The proposed method has the potential to be applied on the modeling and optimization of other growth/etch processes.
URIhttp://hdl.handle.net/10261/136585
DOI10.1088/0960-1317/25/5/055023
Identificadoresdoi: 10.1088/0960-1317/25/5/055023
e-issn: 1361-6439
issn: 0960-1317
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