Physics Colloquium | Machine-Learning-Driven Advances in Modeling Amorphous Solids, March 26

The Physics & Astronomy Colloquium Series presents Volker Deringer of University of Oxford, UK on “Machine-Learning-Driven Advances in Modeling Amorphous Solids” on Friday, March 26, at 4:10 p.m. at an Online Departmental Colloquium.

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Abstract : Structurally disordered materials continue to pose fundamental research questions. Some of the most central ones concern the atomic-scale structure: how can we quantify an amorphous (non-crystalline) structure at all; how is it linked to properties?

In this presentation, I will showcase recent advances in the modeling and understanding of amorphous materials that have been enabled by combining atomistic machine-learning approaches with density-functional theory. I will demonstrate how atomistic ML models have given new insight into the complex structural and electronic transitions in amorphous silicon under high pressure [1], and I will discuss initial applications and future perspectives in the area of battery materials modeling [2].

[1] Nature 2021, 589, 59 ( https://doi.org/10.1038/s41586-020-03072-z )

[2] J. Phys. Energy 2020, 2, 041003 ( https://doi.org/10.1088/2515-7655/abb011 )