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

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

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.

The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.

Erich Hsieh, Deputy Assistant Secretary for OE’s Energy Storage Division, shared insights about the Grid Storage Launchpad and energy storage innovations .

Energy storage expert Vince Sprenkle leads Office of Electricity's first facility to advance next-generation energy storage technologies.

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

PNNL celebrates World Energy Storage Day (September 22) by introducing you to some of our best and brightest in this area.

PNNL welcomes six Department of Energy Office of Science Graduate Student Research awardees from across the nation.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

PNNL researchers design liquid-based porous electrolyte that could transport lithium ions more easily between electrodes, improving battery efficiency.

HiSVSIM enables large-scale quantum simulations through graph partitioning.