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Proceedings Paper

Rapid recipe formulation for plasma etching of new materials
Author(s): Meghali Chopra; Zizhuo Zhang; John Ekerdt; Roger T. Bonnecaze
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Paper Abstract

A fast and inexpensive scheme for etch rate prediction using flexible continuum models and Bayesian statistics is demonstrated. Bulk etch rates of MgO are predicted using a steady-state model with volume-averaged plasma parameters and classical Langmuir surface kinetics. Plasma particle and surface kinetics are modeled within a global plasma framework using single component Metropolis Hastings methods and limited data. The accuracy of these predictions is evaluated with synthetic and experimental etch rate data for magnesium oxide in an ICP-RIE system. This approach is compared and superior to factorial models generated from JMP, a software package frequently employed for recipe creation and optimization.

Paper Details

Date Published: 16 March 2016
PDF: 6 pages
Proc. SPIE 9781, Design-Process-Technology Co-optimization for Manufacturability X, 978111 (16 March 2016); doi: 10.1117/12.2219171
Show Author Affiliations
Meghali Chopra, The Univ. of Texas at Austin (United States)
Zizhuo Zhang, The Univ. of Texas at Austin (United States)
John Ekerdt, The Univ. of Texas at Austin (United States)
Roger T. Bonnecaze, The Univ. of Texas at Austin (United States)


Published in SPIE Proceedings Vol. 9781:
Design-Process-Technology Co-optimization for Manufacturability X
Luigi Capodieci, Editor(s)

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