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.

Launching a premier partnership, PNNL and the University of Texas El Paso (UTEP) signed a memorandum of agreement on UTEP’s campus on October 6.

Across the United States, water moving between the river and riverbed sediments does not overcome localized processes that govern organic matter chemistry.

SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy.

Research organizations work toward compelling market-ready solutions for building operations.

New research makes molecular-level calculations of water faster and easier.

PNNL worked with the Department of Energy on the Commercial Packaged Boiler rule, which will help reduce energy use, enhance the environment, and save dollars.

Updated flexible software generates and optimizes monitoring programs for detecting potential leaks from geological carbon storage with an enhanced user experience.

A process developed at PNNL that converts biomass and waste into a chemical intermediate or into gasoline, diesel, and jet fuel is available for commercial licensing.

PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing.

Researchers studied water cycling to assess the achievability of net-zero water usage at military installations in the Pacific Islands.

Eight Office of Science Graduate Student Research join PNNL.

New research from PNNL results in faster and more accurate variational quantum algorithm training.

PNNL offers six distinct pathways for deploying place-based renewable energy infrastructure at scale.

New research simulates power demand, supply, and cost in a hotter, drier climate.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

A new perspective article discusses how integrating carbon dioxide capture and conversion in solvents can lead to cheaper and more efficient carbon management systems.

Providing a perspective on the importance of integrating experimental work with theory and simulations when designing new carbon capture solvents.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.