2021 marks the largest cohort of PNNL authors and co-authors to be recognized at annual Waste Management Symposia for environmental management research.
A research project that brings together mathematicians and atmospheric scientists has developed into a deep collaboration for improving atmospheric models.
With quantum chemistry, researchers led by PNNL computational scientist Simone Raugei are discovering how enzymes such as nitrogenase serve as natural catalysts that efficiently break apart molecular bonds to control energy and matter.
PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.
On the looming 10th anniversary of the Fukushima disaster at the Daiichi Power Station in Japan, PNNL looks back at the science and solidarity it has shared with Fukushima and its nuclear cleanup effort.
Beginning in 2021, PNNL chemical physicist Bruce Kay begins a three-year term as an AVS trustee, part of a six-member committee responsible for overseeing the administration of student scholarships and major society awards.
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.
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.