A melting temperature database and a neural network model for melting temperature prediction

2021/10/20 by Qi‐Jun Hong, Hong, Qi-Jun
Computer Science · Materials Science · #FOS: Physical sciences #Machine Learning in Materials Science #Materials Science (cond-mat.mtrl-sci) #Neural Networks and Applications

paper · pdf · doi:10.48550/arxiv.2110.10748

openalex publication_date 2021/10/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

I build a melting temperature database that contains approximately 10,000 materials. Based on the database, I build a machine learning model that predicts melting temperature in seconds. The model features graph neural network and residual neural network architecture. The root-mean-square errors of melting temperature are 90 and 160K for training and testing, respectively. The model is deployed online and is publicly available.

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