StatMechGlass: Python based software for composition–structure prediction in oxide glasses using statistical mechanics

Mikkel S. Bødker, Collin J. Wilkinson, John C. Mauro, Morten M. Smedskjaer

Research output: Contribution to journalArticlepeer-review

Abstract

Knowledge of the distribution of short range-order structural units in oxide glasses is important for deciphering their composition–property relations. However, measurements of the fractions of such units are often difficult and time consuming, especially for multicomponent glasses. Here, we introduce StatMechGlass, a Python-based software for calculating the short range-order structure distribution in oxide glasses based on statistical mechanics. By accounting for the enthalpic and entropic contributions to the network interactions in glass-forming melts, the atomic-scale structures of the resulting glasses can be calculated. As input, the software requires accurate interaction enthalpy values that can be supplied by the user or obtained directly by the software from experimental structure data. StatMechGlass thus enables the prediction of composition–structure relations for any oxide glass composition. When coupled with existing composition–property databases of experimental data, it enables the construction of composition–structure–property databases and models. StatMechGlass is open source and designed in a modular fashion for easy tailoring for specific needs.

Original languageEnglish (US)
Article number100913
JournalSoftwareX
Volume17
DOIs
StatePublished - Jan 2022

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Science Applications

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