214 citations · 1.4k across the 34 of their papers we have counts for
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Reflections from the 2024 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Yoel Zimmermann, Adib Bazgir, Zartashia Afzal +141
Here, we present the outcomes from the second Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry, which engaged participants across global hyb…
Machine Learning Materials Properties with Accurate Predictions, Uncertainty Estimates, Domain Guidance, and Persistent Online Accessibility
Ryan Jacobs, Lane E. Schultz, Aristana Scourtas +7
One compelling vision of the future of materials discovery and design involves the use of machine learning (ML) models to predict materials properties and then rapidly find materia…
Twins in rotational spectroscopy: Does a rotational spectrum uniquely identify a molecule?
Marcus Schwarting, Nathan A. Seifert, Michael J. Davis +3
Rotational spectroscopy is the most accurate method for determining structures of molecules in the gas phase. It is often assumed that a rotational spectrum is a unique "fingerprin…
Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision
Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman +13
Deep learning methods are transforming research, enabling new techniques, and ultimately leading to new discoveries. As the demand for more capable AI models continues to grow, we…