Suitability of Available Interatomic Potentials for Sn to Model Its 2D Allotropes

Area of Science:

• Materials Science
• Condensed Matter Physics
• Computational Chemistry

Background:

• Stanene, a 2D allotrope of tin, exhibits unique electronic and topological properties.
• Accurate modeling of stanene requires reliable interatomic potentials.
• Existing potentials may not adequately capture the complex structural and mechanical behaviors of stanene phases.

Purpose of the Study:

• To assess the suitability of various interatomic potentials for simulating stanene.
• To identify the most accurate potential for modeling diverse stanene allotropes.
• To provide a quantitative comparison of different potential models.

Main Methods:

• Density Functional Theory (DFT) calculations were employed to establish reference data.
• Molecular Statics (MS) simulations utilized ten different interatomic potentials.
• Potentials evaluated include Tersoff, Modified Embedded Atom Method (MEAM), and Machine Learning-based Interatomic Potentials (ML-IAP).

Main Results:

• The study systematically compared structural and mechanical properties across multiple stanene phases (F, LB, HB, FD, TD, HD, LHD).
• Performance variations were observed among Tersoff, MEAM, and ML-IAP models.
• Machine learning potentials demonstrated high accuracy in predicting key material characteristics.

Conclusions:

• Certain ML-IAP models are highly suitable for simulating stanene allotropes.
• The findings guide the selection of appropriate potentials for future stanene research.
• This work facilitates more reliable computational studies of 2D tin.