MyTm: An Automated Melting Temperature Calculation Toolkit
Abstract
Melting temperature calculation is one of the important topics in computational materials science. In high-throughput in silico screening and artificial intelligence assisted design of materials, it usually requires a rapid and autonomous assessment of the melting temperature of the target. Unfortunately, molecular dynamics (MD) simulations of the melting point require many cumbersome and manual operations, making large-scale calculation of the melting point challenging. In this work, we introduce MyTm, a toolkit that employs MD to automatically determine the melting point. The method is fully modularized, and by combining these modules, the program enables fully automated melting calculations by using commonly adopted approaches, including the direct-heating method, the void method, the modified void method, the solid-liquid coexistence method, and the Z method. Moreover, a machine learning (ML) method is proposed and employed to recognize and classify the solid like and liquid like atoms, which effectively resolve the low accuracy issue in conventional classification approaches, thus making the automated high throughput pipeline of melting-point calculation possible. The robustness and efficacy of MyTm have been demonstrated by several well studied systems.
Versions
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BibTeX
@misc{huang2026mytm,
title = {{MyTm: An Automated Melting Temperature Calculation Toolkit}},
author = {Y. S. Huang and H. X. Song and Y. Sun and J. L. Li and Y. L. Xu and F. C. Wu and Y. C. Gan and Y. F. Wang and H. Wang and Hua Y. Geng},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.39686},
eprint = {2609.39686},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.39686},
}
RIS
TY - UNPB
TI - MyTm: An Automated Melting Temperature Calculation Toolkit
AU - Y. S. Huang
AU - H. X. Song
AU - Y. Sun
AU - J. L. Li
AU - Y. L. Xu
AU - F. C. Wu
AU - Y. C. Gan
AU - Y. F. Wang
AU - H. Wang
AU - Hua Y. Geng
PY - 2026
DA - 2026/09/30
PB - arXiv
DO - 10.48550/arxiv.2609.39686
UR - https://arxiv.org/abs/2609.39686
AB - Melting temperature calculation is one of the important topics in computational materials science. In high-throughput in silico screening and artificial intelligence assisted design of materials, it usually requires a rapid and autonomous assessment of the melting temperature of the target. Unfortunately, molecular dynamics (MD) simulations of the melting point require many cumbersome and manual operations, making large-scale calculation of the melting point challenging. In this work, we introduce MyTm, a toolkit that employs MD to automatically determine the melting point. The method is fully modularized, and by combining these modules, the program enables fully automated melting calculations by using commonly adopted approaches, including the direct-heating method, the void method, the modified void method, the solid-liquid coexistence method, and the Z method. Moreover, a machine learning (ML) method is proposed and employed to recognize and classify the solid like and liquid like atoms, which effectively resolve the low accuracy issue in conventional classification approaches, thus making the automated high throughput pipeline of melting-point calculation possible. The robustness and efficacy of MyTm have been demonstrated by several well studied systems.
ER -