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Machine-learned interatomic potential for titanium carbide MXenes: Application to ion irradiation simulations · arXivDesk

2603.04152Mar 4, 2026

Machine-learned interatomic potential for titanium carbide MXenes: Application to ion irradiation simulations

Jesper Byggmästar

Materials Science Computational Physics

arXiv PDF

Abstract

A computationally efficient and accurate machine-learned (ML) interatomic potential is developed for bare Ti $_{n+1}$ C $_n$ MXenes. With a diverse set of structures computed with density functional theory, the trained ML potential demonstrates good accuracy and robustness to a wide range of bond distances and environments, making it a useful tool for molecular dynamics simulations of MXenes subjected to mechanical load or irradiation. The ML potential is applied to simulations of light and heavy ion irradiation, gathering insight into the statistics and probabilities of sputtering, reflection, defect creation, and implantation into bare Ti $_{n+1}$

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A computationally efficient and accurate machine-learned (ML) interatomic potential is developed for bare Ti_n+1C_n MXenes. With a diverse set of structures computed with density functional theory, the trained ML potential demonstrates good accuracy and robustness to a wide range of bond distances and environments, making it a useful tool for molecular dynamics simulations of MXenes subjected to mechanical load or irradiation.

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Researchers working in cond-mat.mtrl-sci and adjacent areas.

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The paper addresses: Machine-learned interatomic potential for titanium carbide MXenes: Application to ion irradiation simulations.
A computationally efficient and accurate machine-learned (ML) interatomic potential is developed for bare Ti_n+1C_n MXenes.