Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.

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

The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.

Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.

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 Department of Energy’s Vehicle Technologies Office recognized Livewire’s outstanding teamwork and technical expertise.

From enhancing biofuel crops to setting up automated experiments and improving energy storage—interns at PNNL are making an impact.

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.

Anderson is one of only 25 women from throughout the world selected to participate in the Epistimi-Women in STEMM Leadership Workshop on “Women in the Energy Sector,” held July 15–19 in Athens, Greece.

The Grid Storage Launchpad will enable researchers to accelerate and validate new battery materials and systems.

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

Clean hydrogen energy infrastructure is coming to the Pacific Northwest and PNNL experts are advising the work to come.

Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.

Recycling polyolefin materials is challenging. One waste management strategy is plastic upcycling. New work demonstrates a single-step upcycling route coupling cracking and alkylation, recycling carbon and keeping valuable resources active.

A new approach validates quantum algorithms for low-energy nuclear physics applications

PNNL’s patented Shear Assisted Processing and Extrusion (ShAPE™) technique is an advanced manufacturing technology that enables better-performing materials and components while offering opportunities to reduce costs and energy consumption.

Ji-Guang (Jason) Zhang has been named the first Department of Energy Lab Innovator of the Year.

PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence

Scott Whalen, a chief scientist in the Applied Materials and Manufacturing group at PNNL, has been named 2023 PNNL Inventor of the Year

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