collaborators

5 papers

cs.LG2026

UMA: A Family of Universal Models for Atoms

Brandon M. Wood, Misko Dzamba, Xiang Fu +15

The ability to quickly and accurately compute properties from atomic simulations is critical for advancing a large number of applications in chemistry and materials science includi…

cond-mat.mtrl-sci2026

Computational Design of Ductile Additively Manufactured Tungsten-Based Refractory Alloys

Kareem Abdelmaqsoud, Daniel Sinclair, Venkata Satya Surya Amaranth Karra +4

Tungsten exhibits exceptional temperature and radiation resistance, making it well-suited for applications in extreme environments such as nuclear fusion reactors. Additive manufac…

cond-mat.mtrl-sci2026

Electronic structure and elasticity of the Ta-W solid solution

Kareem Abdelmaqsoud, John R. Kitchin, Michael Widom

The brittleness or ductility of metals has long been attributed to their elastic constants, with high Poisson ratio, or equivalently high Pugh ratio, favoring greater ductility. Gr…

cond-mat.mtrl-sci2025

The Open DAC 2025 Dataset for Sorbent Discovery in Direct Air Capture

Anuroop Sriram, Logan M. Brabson, Xiaohan Yu +12

Identifying useful sorbent materials for direct air capture (DAC) from humid air remains a challenge. We present the Open DAC 2025 (ODAC25) dataset, a significant expansion and imp…

cs.LG2025

Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles

Tirtha Vinchurkar, Kareem Abdelmaqsoud, John R. Kitchin

Machine-learned potentials (MLPs) have revolutionized materials discovery by providing accurate and efficient predictions of molecular and material properties. Graph Neural Network…