CACTUS provides AI-powered cheminformatics for autonomous science.

PNNL’s Center for Cloud Computing is addressing challenges in data management and hybrid cloud solutions with industry and academic partnerships.

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

PNNL researchers work with industry partners to transform large language models.

University of Washington Professor David Baker won the 2024 Nobel Prize in Chemistry for computational protein design.

In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.

ChemReasoner combines decades of chemistry knowledge with large language models to propose strategies for effective new catalysts.

Early life exposure to polycyclic aromatic hydrocarbons (PAHs), found in smoke, has been linked to developmental problems. To study the impacts of these pollutants, PAH metabolism in infants and adults were compared.

Data from SOSAT web tool informs site selection and management for the subsurface injection of captured carbon dioxide.

PMedIC, the PNNL and OHSU joint research collaboration, contributes to student success and impact in biomedicine.

To improve our ability to “see” into the subsurface, scientists need to understand how different mineral surfaces respond to electrical signals at the molecular scale.

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL shared recent developments in artificial intelligence at the inaugural Special Competitive Studies Project AI for National Competitiveness Expo.

Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.

PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.

Researchers used a combination of sophisticated laboratory incubations and field measurements to determine the role of microbial production and consumption of methane in soils with different exposure to tidal inundation

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

Researchers devised a quantitative and predictive understanding of the cloud chemistry of biomass-burning organic gases helping increase the understanding of wildfires.

Reproducible workflows for binning and visualizing nuclear magnetic resonance spectra from environmental samples.

Spatial proteomics enables researchers to link protein measurements to features in the image of a tissue sample, which are lost using standard approaches.