Conference Tools for 2021 TMS Annual Meeting & Exhibition

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About this Abstract
Meeting	2021 TMS Annual Meeting & Exhibition
Symposium	AI/Data Informatics: Applications and Uncertainty Quantification at Atomistics and Mesoscales
Presentation Title	Decision Trees in Continuous Action Space for High-throughput Exploration of Potential Energy Surfaces
Author(s)	Sukriti Manna, Troy Loeffler, Rohit Batra, Suvo Banik, Henry Chan, Subramanian Sankaranarayanan
On-Site Speaker (Planned)	Sukriti Manna
Abstract Scope	The dynamic evolution of nanoclusters and temperature-dependent stability and properties remain unexplored due to lack of their available force field. To mitigate this issue, we use a Monte Carlo Tree Search (MCTS) with reinforcement learning to develop potential models in a high throughput manner for nanoclusters of different elements across the periodic table. To ensure the transferability of these parameters across different size regimes, we used an extensive training data set that encompasses the structural and energetic properties of nanoclusters over a wide range of energy windows. Our parameterized BOP model can accurately capture the structure, energetics, forces, and dynamics of several different elemental clusters across the periodic table. This makes our newly developed scheme and the resulting models to be computationally robust but inexpensive tool for investigating a wide range of materials phenomena across a broad range of nanoclusters.
Proceedings Inclusion?	Planned:
Keywords	Machine Learning, Modeling and Simulation, Computational Materials Science & Engineering

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