Researchers at Pacific Northwest National Laboratory (PNNL) are closer to understanding how iron may pave the way for sequestration of technetium-99 contaminants in the subsurface.
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.
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.
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.
To study the impact of accelerated dryland expansion and degradation on global dryland gross primary production (GPP,) PNNL and Washington State University researchers assessed GPP data from 2000-2014 and the CMIP5 aridity index (AI).
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.
Environmental engineer Mike Truex presented an Environmental Protection Agency webinar about how conceptual site models must change as new data is acquired for remedy optimization.
