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.

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.

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

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.

Pacific Northwest National Laboratory (PNNL) researchers pioneer a new tool to represent cellular response to viral infection.

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

In a new review, PNNL researchers outline how to convert stranded biomass to sustainable fuel using electrochemical reduction reactions in mini-refineries powered by renewable energy.

PNNL Lab fellow and Earth scientist Nik Qafoku earns highest recognition from the Soil Science Society of America.

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.

The three-year project funded by DOE’s Basic Energy Sciences program will focus on using electrochemistry to capture ambient carbon dioxide.

Embedding the known physics of the system to be controlled in the AI model of the system is data efficient and provides safety guarantees.

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.

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

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.

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

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

Jian Liu, a chemical engineer at PNNL, was selected as co-editor for the Elsevier book, Nanoporous Materials for Molecule Separation and Conversion.

PNNL is managing the Data Archive and Portal, which provides the wind research community with secure, timely, easy, and open access to all data brought in from research under DOE’s Atmosphere to Electrons program.