Long-term PNNL support has helped enable the continued success of the Chesapeake Large-Scale Analytics Conference.

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.

Two PNNL researchers, one a world-leading authority on microorganisms, the other an expert on coastal ecosystem restoration, have been elected fellows of the American Association for the Advancement of Science.

Clarivate Analytics recently unveiled its 2020 list of Highly Cited Researchers. The list named 17 PNNL scientists for their influential and oft-referenced work.

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.

The project received an Innovative and Novel Computational Impact on Theory and Experiment (INCITE) award, a highly competitive U.S. Department of Energy Office of Science program.

PNNL data scientists Ján Drgoňa and Draguna Vrabie are working to reduce deployment costs of advanced energy control systems for buildings.

Researchers developed a new tool that combines artificial intelligence and microscopy data to rapidly test new materials for fusion reactor use.

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.

Researchers at PNNL have developed a bacteria testing system called OmniScreen that combines biological and synthetic chemistry with machine learning to hunt down pathogens before they strike.

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

PNNL researchers are looking for protein signatures that could provide information about how the body's immune system responds to COVID-19.

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.

A zoonotic coronavirus known as SADS-CoV that has killed many pigs has the ability to infect human cells, surprising scientists.

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.