The 2024 Jack Simons Award honor recognizes Li for his expertise in integrating chemistry with computing for fundamental science research.

New research informs the development of foundational models for computational chemistry through hardware-software co-design.

Chemists Wilma Rishko and Samantha Johnson are set to receive an ACS Division of Inorganic Chemistry Award for Undergraduate Research as a mentor-mentee pair.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

A team of scientists at PNNL developed new computational models to predict the behavior of these impurities and reduce the expense and risk related to actinide metal production.

Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science

Robert Rallo from Pacific Northwest National Laboratory will direct a machine learning thrust for a new Department of Energy-funded project led by SLAC National Accelerator Laboratory.

At the Nonproliferation, Counterproliferation, and Disarmament Science Gordon Research Conference, researchers from PNNL shared research and scientific approaches for countering diverse threats.

Computational chemistry libraries from NWChem, NWChemEX, SPEC, and more are now available on Azure Quantum Elements.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Xantheas was one of four professors in 2021/2022 to be selected by the Göttingen Academy of Sciences and Humanities for this award.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Vanda Glezakou and Laboratory Fellow Roger Rousseau collaborated with other experts to write an American Chemical Society book chapter.

A hybrid computing approach for solving quantum chemical problems offers a practical bridge between classical and quantum computing.

The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.