3 papers
cond-mat.mtrl-sci2024
Towards Informatics-Driven Design of Nuclear Waste Forms
Vinay I. Hegde, Miroslava Peterson, Sarah I. Allec +11
Informatics-driven approaches, such as machine learning and sequential experimental design, have shown the potential to drastically impact next-generation materials discovery and d…
cond-mat.mtrl-sci2024
Evaluation of GlassNet for physics-informed machine learning of glass stability and glass-forming ability
Sarah I. Allec, Xiaonan Lu, Daniel R. Cassar +8
Glasses form the basis of many modern applications and also hold great potential for future medical and environmental applications. However, their structural complexity and large c…
cond-mat.mtrl-sci2023
A case study of multi-modal, multi-institutional data management for the combinatorial materials science community
Sarah I. Allec, Eric S. Muckley, Nathan S. Johnson +9
Although the convergence of high-performance computing, automation, and machine learning has significantly altered the materials design timeline, transformative advances in functio…