The first-ever simulation of aluminum conductivity offers a recipe for an inexpensive, lightweight alternative to copper.

Road tripping? PNNL’s researchers driving science and technology for clean, efficient and convenient transportation.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

Quantum simulators help navigate noise on GPU-based HPC systems.

PNNL Chief Scientist for Computing Jim Ang will be part of a DOE Office of Science virtual discussion regarding industry collaborations on AI hardware.

Four research staff from PNNL are part of an international team that earned top honors for a journal paper focused on a new algorithm-evaluation approach for buildings.

PNNL researchers received the “Best Paper Award” at the 39th IEEE International Conference on Computer Design.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

PNNL researchers contributed to the International Conference on Data Science and Advanced Analytics 2021 Best Paper Award-winning publication.

Developed at PNNL, Shear Assisted Processing and Extrusion, or ShAPE™, uses significantly less energy and can deliver components like wire, tubes and bars 10 times faster than conventional extrusion, with no sacrifice in quality.

Tumeo joins other computer scientists in a contributed article on graph processing systems to the Communications of the ACM.

An energy-efficient method to extrude metal components wins Association of Washington Business Green Manufacturing Award. PNNL’s Shear Assisted Processing and Extrusion™ technology consumes less energy and enhances material properties.

PNNL’s suite of Solid Phase Processing tools like Cold Spray is helping to strengthen hydroelectric dam materials such as turbines.

Rotational Hammer Riveting, developed by PNNL, joins dissimilar materials quickly without preheating rivets. The friction-based riveting enables use of lightweight magnesium rivets and also works on aluminum and speeds manufacturing.

PNNL computer scientist Ang Li serves as one of the principal investigators for a project selected to receive DOE funding.

Slaven Peles, PNNL computational scientist and leader of a national high-performance computing project for power grid analysis, spoke about the project with the host of the Let’s Talk Exascale podcast.

Three recent doctoral graduates are beginning their research careers at Pacific Northwest National Laboratory after completing the WSU-PNNL Distinguished Graduate Research Program this spring.

Researchers to design their own computer accelerators for faster analysis of large datasets.

OpenCGRA expedites the design-prototype cycle of computer architecture development.

A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.