Modeling glasses from first-principles using random structure sampling
Laszlo Wolf, Andrew Novick, Vladan Stevanovi\'c

TL;DR
This paper introduces a first-principles method for modeling glasses by sampling random local minima, enabling accurate property predictions with reduced computational cost and potential for high-accuracy electronic structure calculations.
Contribution
The approach uses random structure sampling of small-cell local minima to efficiently approximate glass properties, reducing computational complexity compared to traditional large-cell simulations.
Findings
Accurately reproduces experimental properties of vitreous SiO2
Reduces computational cost by focusing on small-cell local minima
Enables high-accuracy electronic structure calculations for glasses
Abstract
We present an approach to approximating static properties of glasses without experimental inputs rooted in the first-principles random structure sampling. In our approach, the glassy system is represented by a collection (composite) of periodic, small-cell (few 10s of atoms) local minima on the potential energy surface. These are obtained by generating a set of periodic structures with random lattice parameters and random atomic positions, which are then relaxed to their closest local minima on the potential energy surface using the first-principles methods. Using vitreous SiO2 as an example, we illustrate and discuss how well various atomic and electronic structure properties calculated as averages over the set of such local minima reproduce experimental data. The practical benefit of our approach, which can be rigorously thought of as representing an infinitely quickly quenched…
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Taxonomy
TopicsCultural Heritage Materials Analysis
