Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.
Five staff members from PNNL received awards from the Department of Energy’s Federal Energy Management Program for contributions to projects for the U.S. Army.
As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.
Physicist named specialty chief editor of Battery Systems and Applications for Frontiers in Batteries and Electrochemistry and associate editor for Frontiers in Energy Research—Nano Energy.
PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.
PNNL’s fall Pathways to Excellence award ceremony celebrated nearly 50 staff for their contributions across science, engineering, operations, and STEM education.
The Department of Energy has issued updated energy conservation standards for manufactured homes. The effort to establish the standards, supported by PNNL, is expected to result in a range of benefits for the manufactured housing sector.
A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management.
Some rocks can potentially convert injected carbon dioxide into more stable solid minerals. A new review article explores what scientists know about the atom-by-atom process.
A new version of the Department of Energy’s Technical Resilience Navigator allows users to prioritize resilience solutions based on both risk reduction and emissions impact.
Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.
PNNL’s Ján Drgoňa and Draguna Vrabie are part of an international team that authored a most-cited paper on Model Predictive Control, an approach for improving operations, energy efficiency, and comfort in buildings.