Evaluating the diversity and utility of materials proposed by generative models

• Main Authors: New, Alexander, Pekala, Michael, Pogue, Elizabeth A, Le, Nam Q, Domenico, Janna, Piatko, Christine D, Stiles, Christopher D
• Format: Journal Article
• Language: English
• Published: 09.08.2023
• Subjects: Computer Science - Learning; Physics - Computational Physics; Physics - Materials Science

Generative machine learning models can use data generated by scientific modeling to create large quantities of novel material structures. Here, we assess how one state-of-the-art generative model, the physics-guided crystal generation model (PGCGM), can be used as part of the inverse design process....