(224d) Optimal Operation of Plasma Enhanced Atomic Layer Deposition Via Machine Learning
AIChE Annual Meeting
2020
2020 Virtual AIChE Annual Meeting
Topical Conference: Next-Gen Manufacturing
Big Data and Applications in Advanced Modeling and Manufacturing
Tuesday, November 17, 2020 - 8:45am to 9:00am
In light of this, a comprehensive multiscale computational fluid dynamics (CFD) model has been proposed to capture the integrated dynamic profile of a remote plasma PEALD process with Tetrakis-dimethylamino-Hafnium (TDMAHf) and oxygen plasma as precursors. Based on the simulation model, in this work, the operation of a PEALD reactor under different operating conditions is discussed, and the optimal operating regime of this reactor is analyzed. Specifically, an operational database is constructed using the multiscale CFD model to map a variety of reactor operation input combinations to their resulting film qualities and deposition profile. This database is then processed through machine learning analysis to explore the feasible operating domain, and within which, the optimal operating decision can be identified according to the desired production throughput and economic demand.
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