Researchers at PNNL leveraged their experiences to connect with attendees at the 2022 SACNAS National Diversity in STEM Conference, October 27–29, 2022, in San Juan, Puerto Rico.

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.