PNNL researchers investigate the environmental conditions, from soil moisture to surface temperature, that lead to wildfire.

New biogeochemical modeling uses high-resolution mass spectrometry data to reveal how organic matter thermodynamics affect ecosystems across scales.

The map fills in a portion of the study site missing from sampling studies and enables a better understanding of hydrological dynamics in a complex river corridor.

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.

This committee represents the country’s soil science community in the International Union of Soil Sciences, advises The National Academies, and communicates with professional societies and organizations.

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.

Ecosystem feedback fire model opens new investigative pathways into impacts of fire on future climate.

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.

A small collection of naturally interacting soil microbes could enable new studies of community interactions and metabolism.

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.

Community Land Model 5.0 can represent how irrigation influences water, carbon, and nitrogen budgets throughout a highly managed semiarid watershed.

Soil microbial communities produced more water retaining molecules when enriched with insoluble organic carbon, chitin, compared to a soluble carbon source, N-acetylglucosamine.

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 recognizes researchers during National Postdoc Appreciation Week.

PNNL’s Heida Diefenderfer was recently appointed to a National Academies of Sciences, Engineering, and Medicine committee that will assess long-term environmental trends in the Gulf of Mexico region.

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.