activity
20212025
most citedMachine Learning Materials Properties with Accurate Predictions, Uncertainty Estimates, Domain Guidance, and Persistent Online Accessibility

3 citations · 5 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2025★ 2 cited

34 Examples of LLM Applications in Materials Science and Chemistry: Towards Automation, Assistants, Agents, and Accelerated Scientific Discovery

Yoel Zimmermann, Adib Bazgir, Alexander Al-Feghali +32

Large Language Models (LLMs) are reshaping many aspects of materials science and chemistry research, enabling advances in molecular property prediction, materials design, scientifi…

cond-mat.mtrl-sci2024★ 3 cited

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…

physics.chem-ph2024

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…

cs.DC2022

Linking Scientific Instruments and HPC: Patterns, Technologies, Experiences

Rafael Vescovi, Ryan Chard, Nickolaus Saint +10

Powerful detectors at modern experimental facilities routinely collect data at multiple GB/s. Online analysis methods are needed to enable the collection of only interesting subset…

cs.DC2021

RADICAL-Pilot and Parsl: Executing Heterogeneous Workflows on HPC Platforms

Aymen Alsaadi, Logan Ward, Andre Merzky +4

Workflows applications are becoming increasingly important to support scientific discovery. That is leading to a proliferation of workflow management systems and, thus, to a fragme…