3 papers
cond-mat.mtrl-sci2024
Deep Learning Accelerated Phase Prediction of Refractory Multi-Principal Element Alloys
A. K. Shargh, C. D. Stiles, J. A. El-Awady
The tunability of the mechanical properties of refractory multi-principal-element alloys (RMPEAs) make them attractive for numerous high-temperature applications. It is well-establ…
cond-mat.mtrl-sci2023
Evaluating the diversity and utility of materials proposed by generative models
Alexander New, Michael Pekala, Elizabeth A. Pogue +4
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 g…
cs.LG2022
Curvature-informed multi-task learning for graph networks
Alexander New, Michael J. Pekala, Nam Q. Le +3
Properties of interest for crystals and molecules, such as band gap, elasticity, and solubility, are generally related to each other: they are governed by the same underlying laws…