ExaGO, a power grid simulation and optimization platform developed at PNNL is the first of its kind to run on Frontier.

Advances in understanding the nature of the chemical bond are featured in this special issue of The Journal of Chemical Physics.

Vrabie co-organized the 2022 Workshop on Artificial Intelligence for Isotope R&D and Production for the Department of Energy Isotope Program.

An evaluation of models and prediction tools for distributed wind turbines has unearthed data that can help potential users make the most informed decisions on upfront investments.

The IAC will advise the Secretary of Commerce on the science and technology needs of the microelectronics industry.

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

PNNL wind energy experts have published the Distributed Wind Market Report: 2022 Edition, supplying key findings that can help businesses, communities, and homeowners make informed decisions.

Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference.

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

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.

Two PNNL studies that describe the potential value of offshore wind off the Oregon Coast and distributed wind in Alaska were published in the journal Energies.

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.

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

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.