Abstract

The continuous development and improvement of interatomic potential models for oxide glasses have made classical molecular dynamics a powerful computational technique routinely used for studying the structure and properties of such materials on a par with the more advanced experimental techniques. In this brief review, we retrace the development of the most used interatomic potential models from the earliest MD simulations up to now with a look at the possible future developments in this field due to the advent of the machine learning era and data-driven methods. • An historical overview of the interatomic potentials models for oxide glasses is provided. • The applicability and accuracy of the developed models are discussed. • Practical considerations for optimizing interatomic potential parameters are reported. • Future perspectives on the development of Machine Learning Force-Fields are discussed.

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