Using public data from the entire 1,500-square-mile Los Angeles metropolitan area, PNNL researchers reduced the time needed to create a traffic congestion model by an order of magnitude, from hours to minutes.

PNNL researchers have shown an improved binarized neural network can deliver a low-cost and low-energy computation to help the performance of smart devices and the power grid.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

PNNL and Microsoft Quantum partner to link quantum circuits to powerful government supercomputers.

Pacific Northwest National Laboratory researchers developed a graphical processing unit (GPU)-centered quantum computer simulator that can be 10 times faster than any other quantum computer simulator.

In a new video series, PNNL is highlighting six scientific and technical experts in the national security domain throughout the fall. Each was promoted to scientist and engineer Level 5, one of PNNL’s most senior research roles.

Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

PNNL’s new Smart Power Grid Simulator, or Smart-PGSim, combines high-performance computing and artificial intelligence to optimize power grid simulations without sacrificing accuracy.

A zoonotic coronavirus known as SADS-CoV that has killed many pigs has the ability to infect human cells, surprising scientists.

The MIT-sponsored competition encourages community approaches to developing new solutions for analyzing graphs and sparse data; PNNL has placed a winner in each year.

In a new video series this fall, PNNL is highlighting six scientific and technical experts in the national security domain. Each was promoted to Scientist and Engineer Level 5, one of PNNL’s most senior research roles.

James A. Ang, a PNNL computing expert, was recently invited to moderate a panel in a virtual workshop focused on federally funded research and development on software for heterogeneous computing.

Infusing data science and artificial intelligence into electron microscopy could advance energy storage, quantum information science, and materials design.

NIH awarded $1.7 million to researchers from PNNL, WSU, and NREL to continue fundamental research into catalytic bias—a phenomenon in the protein environment that shifts the direction and speed of an enzyme’s catalytic reaction.

Today’s critical infrastructure systems are increasingly vulnerable to attacks that could cripple civil society, according to cybersecurity experts.

PNNL and the Georgia Institute of Technology vow to collaborate more impactfully and more often in a new MOU announced October 23, 2020.

Tracking down nefarious users is just one example of work at PNNL’s Center for Advanced Technology Evaluation, a computing proving ground supported by DOE’s Advanced Scientific Computing Research program.

Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.