High fidelity simulations enabled by high-performance computing will allow for unprecedented predictive power of molecular level processes that are not amenable to experimental measurement.

Pasco School District teachers join PNNL for an immersive teaching experience.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

Scientists at PNNL were awarded nearly $12 million to better understand pathogens, how they spread, and how to prepare the nation against future outbreaks.

The Human Factors Symposium took place at Discovery Hall at PNNL in May 2023. Fifty-seven attendees participated in the three-day event representing 15 different institutions.

Scientists can now generate a protein database directly from proteomics data gathered from a specific soil sample using a digital tool and deep learning computer model called Kaiko.

Summer internship programs with partnering colleges provide pathways for students to explore careers in science, technology, engineering, and math.

Faced with limited data, researchers at PNNL studied different techniques to improve disease prediction in resource-limited settings.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

Joint appointments at PNNL and UTEP are teaming together to strengthen and protect sensitive data.

This study profiled the 24-hour rhythmicity in bile salt hydrolase enzyme activity using simple fluorescence assay and the results showed that this rhythmicity is influenced by feeding patterns of the host.

New research from PNNL and Washington State University collaborators connects the microbiome in the gut to circadian rhythms, suggesting a role for the microbiome as an internal regulator.

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

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

PNNL and The University of Texas at El Paso expand their premier partnership to include the Cyber Halo Innovation Research Program.

ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

The popular approach of organizing soil bacteria into fast- or slow-growing groups is problematic because most bacteria grow at comparable rates in soil.

Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.

Metabolomics analysis revealed differences in metabolome profiles for two distinct modes of fungal wood decay.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.