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.

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.

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.

PNNL quantum computing pioneer Nathan Wiebe contributed to a Google-led quantum computing landmark study published in the journal Science.

Making sure there’s enough electricity at the lowest price is a critical endeavor undertaken daily by electricity market operators. Now, there’s an approach that provides more timely and accurate information to make day-ahead decisions.

A cadre of physical scientists, engineers and computing experts at Pacific Northwest National Laboratory is poised to participate in the launch of three new DOE Office of Science-sponsored quantum information science research centers.

Contributions from researchers across Pacific Northwest National Laboratory (PNNL) were recently recognized in the preliminary findings of a Secretary of Energy Advisory Board (SEAB) report.

Scientists at PNNL have contributed much of the nuclear science that underlies an international monitoring system designed to detect nuclear explosions worldwide. The system detects radioxenon anywhere on the planet.

PNNL materials scientist Ram Devanathan named Fellow and chemist Dave Heldebrant keynotes at the American Chemical Society (ACS) Fall 2020 meeting.

A new radiation-resistant material for the efficient capture of noble gases xenon and krypton makes it safer and cheaper to recycle spent nuclear fuel.

Ang Li and Antonino Tumeo will present hardware to balance machine learning workloads at a top computer architecture conference.

International editing team provided 15-year update, with Devanathan focused on intersection of nuclear science, materials science, and multiscale modeling.

PNNL data scientist Carlos M. Ortiz Marrero has co-edited a volume that highlights work at the intersection of quantum computation and mathematics.

Materials Scientist Arun Devaraj has been selected among 76 recipients nationwide to receive a 2020 Early Career Research Program award from the U.S. Department of Energy

PNNL quantum algorithm theorist and developer Nathan Wiebe is applying ideas from data science and gaming hacks to quantum computing

The race toward the first practical quantum computer is in full stride. Scientists at PNNL are bridging the gap between today’s fastest computers and tomorrow’s even faster quantum computers.

Researchers found that certain oxide interface configurations remain stable in extreme environments, suggesting ways to build better performing, more reliable devices for fuel cells, space-based electronics, and nuclear energy.

First-of-its-kind network analysis on a supercomputer can speed real-time applications for cybersecurity, transportation, and infectious disease tracking