Complex metal alloys enter a new era of predictive design for aerospace and other high-temperature applications.

Researchers show application of a causal model better identifies direct and indirect causal relations compared to correlation and random forest analyses performed over the same dataset.

Researchers introduce revised emission treatment that conserves mass and preserves the original heterogeneity.

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

Publisher will draw on Katrina Waters' expertise in public health and infectious disease.

PNNL’s Nell Byler and Elise Bishoff shared their computer vision expertise with high school students at the National Science Bowl Science Day

Researchers are leveraging the ocean’s natural processes to advance approaches to remove carbon dioxide from the atmosphere and store it in the ocean.

Policy changes in power, energy, buildings, and more could help slow global temperature rise, according to a new report with co-authors from PNNL’s Joint Global Change Research Institute.

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’s Andrew Engel, Tony Chiang, and Sutanay Choudhury at the 2024 ICLR in Vienna.

New research sheds light on the biomolecular dangers of night shift work.

A new study suggests accessing groundwater in key regions could become prohibitively expensive as lower-cost stores are used up.

Five PNNL scientists participated in an invitation-only Department of Energy-sponsored workshop on coastal systems. 

New work finds hurricanes are intensifying faster close to the coast—a trend that’s likely to ramp up in a warmer world.

Vigorous exercise burns fat more in males than in females, but the benefits of exercise are broad for both sexes.

PNNL contributes to a nationwide research consortium investigating the molecular mechanisms triggered by endurance training.

With Earth system models running at higher resolutions, researchers evaluated the sensitivity of aerosol properties to horizontal grid spacing.

This study demonstrates a new model that integrates complex organic matter (OM) chemistry and multiple electron acceptors to predict kinetic rates of OM oxidation.

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.

A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.