Topic: AI/ML for Materials Discovery and Computing

The advent of machine learning (ML) and artificial intelligence (AI) has revolutionized many aspects of modern science and technology and has sparked significant interest in the material science community in recent years. Despite some early deployment of AI/ML in materials science and engineering, the full potential of AI still needs to be explored. This Special Issue highlights the recent progress of advanced and novel AI/ML algorithms and AI/ML-enhanced computational approaches, with applications spanning materials science and engineering. These include fast and accurate material property prediction, crystal structure prediction (CSP) and generation, material process optimization, high-throughput materials computing and discovery, and inverse design of novel materials with target or desired properties.

Topics of interest include, but are not limited to:
● Physics- and chemistry-informed, explainable ML for material development;
● High-throughput material simulation enabled by ML algorithms;
● User-inspired or universal ML interatomic potentials;
● Generative models for CSP;
● AI/ML-accelerated density functional theory and quantum physics and chemistry methods;
● ML for processing-structure-property-performance (PSPP) relationships of materials science and engineering;
● AI/ML-guided materials design and characterization;
● Inverse design of novel materials;
● Foundation or large language models for materials development.

31 Mar 2025