162 citations · 325 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
Interpretable models for extrapolation in scientific machine learning
Eric S. Muckley, James E. Saal, Bryce Meredig +2
Data-driven models are central to scientific discovery. In efforts to achieve state-of-the-art model accuracy, researchers are employing increasingly complex machine learning algor…
Quantifying the performance of machine learning models in materials discovery
Christopher K. H. Borg, Eric S. Muckley, Clara Nyby +4
The predictive capabilities of machine learning (ML) models used in materials discovery are typically measured using simple statistics such as the root-mean-square error (RMSE) or…
Mapping Thermoelectric Transport in a Multicomponent Alloy Space
Ramya Gurunathan, Suchismita Sarker, Christopher K. H. Borg +4
Interest in high entropy alloy thermoelectric materials is predicated on achieving ultralow lattice thermal conductivity through large compositional disorder. However, h…
AutoMat: Accelerated Computational Electrochemical systems Discovery
Emil Annevelink, Rachel Kurchin, Eric Muckley +17
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and…
Quantifying uncertainty in high-throughput density functional theory: a comparison of AFLOW, Materials Project, and OQMD
Vinay I. Hegde, Christopher K. H. Borg, Zachary del Rosario +7
A central challenge in high throughput density functional theory (HT-DFT) calculations is selecting a combination of input parameters and post-processing techniques that can be use…
Thermodynamic Stability of Mg-based Ternary Long-Period Stacking Ordered Structures
James E. Saal, C. Wolverton
Mg alloys containing long-period stacking ordered (LPSO) structures exhibit remarkably high tensile yield strength and ductility. They have been found in a variety of ternary Mg sy…
Thermodynamic Stability of Co-Al-W L12 γ'
James E. Saal, Chris Wolverton
Co-based superalloys in the Co-Al-W system exhibit coherent L12 Co3(Al,W) γ' precipitates in an fcc Co γmatrix, analogous to Ni3Al in Ni-based systems. Unlike Ni3Al however, experi…