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Meeting 2021 TMS Annual Meeting & Exhibition
Symposium AI/Data Informatics: Applications and Uncertainty Quantification at Atomistics and Mesoscales
Presentation Title Use of Atomistic Based Informatics to Model Ionic Bombardment to Synthesize Boron Carbides
Author(s) Kwabena Asante-Boahen, Nirmal Baishnab, Paul Rulis, Michelle Paquette, Ridwan Sakidja
On-Site Speaker (Planned) Kwabena Asante-Boahen
Abstract Scope In this study, we systematically modeled an important aspect of the synthesis process for a-BxC:Hy by utilizing the Reactive Molecular Dynamics (MD) in modeling the argon bombardment from the orthocarborane molecules as the precursor. The MD simulations are used to assess the dynamics associated with the free radicals that result from the ion bombardment. By applying the Data Mining/Machine Learning analysis into the datasets generated from the large reactive MD simulations, we were able to identify and quality the kinetics of these radicals. Overall, this approach allows for a better understanding of the overall mechanism at the atomistic level of Ar bombardment and the role of radical species towards the formation of the orthocarborane network and in turn the boron carbide thin films. The support from the NSF-DMREF program (Award No. 1729176) is gratefully acknowledged. Keywords: Orthocarbones, Boron carbide, Reactive MD simulations, Data Mining, Machine Learning
Proceedings Inclusion? Planned:

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Use of Atomistic Based Informatics to Model Ionic Bombardment to Synthesize Boron Carbides
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