Researchers use models to represent relationships between climate and socio-economic processes, helping inform decisions for slowing climate change and enhancing resilience.

Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

PNNL chemical engineer Reid Peterson helped develop the process to pretreat Hanford Site tank waste by removing cesium-137.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere. Soil is a massive reservoir of carbon, holding three times the amount of carbon than in the atmosphere.

A larger HVAC workforce with training on modern heat pump technology will be pivotal to achieving the mass-scale electrification of household HVAC systems needed to meet building decarbonization goals.

Researchers from PNNL, CSET, and Google DeepMind delved into the potential risks of artificial intelligence in a roundtable discussion.

Researchers designed a new, highly efficient, stable redox-active material from neutral red dye that can efficiently capture CO2 from air.

Leaders from the DOE Office of Energy Efficiency and Renewable Energy visited PNNL October 19–20 for a firsthand look at capabilities and research progress.

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.

Clean hydrogen energy infrastructure is coming to the Pacific Northwest with a newly announced hydrogen hub, and PNNL experts are advising the work to come.

Less pollution and the odd shapes of snow grains as they pack together should help cut the decline of snowpack later this century.

PNNL’s Andrea Mengual co-chaired a working group that produced Building Performance Standards: A Technical Resource Guide. PNNL’s Kim Cheslak, Bing Liu, and Jian Zhang contributed to the effort.

Claudia Tebaldi, a PNNL Earth scientist, has been named a Fellow of the American Geophysical Union. Tebaldi and others will be recognized at AGU23 in December.

Lauren Charles has been named a scientist and engineer level 5 in the national security domain.

Lynn Wood has been named a scientist and engineer level 5 in the national security domain.