OpenCGRA expedites the design-prototype cycle of computer architecture development.

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.

One year ago, Verizon announced a partnership that made PNNL the U.S. Department of Energy’s first national laboratory with Verizon 5G ultra-wideband wireless technology.

PNNL highlights four researchers whose joint appointments are creating new and diverse opportunities for expanding knowledge and scientific impact across institutions.

Sentry-SECURE is a new communication and response platform developed by PNNL, VPI, and Microsoft Azure that rapidly and securely transfers radiological alarm data through the cloud.

Tools being developed at PNNL are helping the nation plan for, respond to and recover from severe storms and wildfires that could threaten critical energy systems.

George Karniadakis receives award highlighting 30 years of work developing computational methods to solve real-world problems.

PNNL designed a free, web-based tool to visually explore the National Response Framework.

The Federal Laboratory Consortium for Technology Transfer has given three national awards to PNNL technology teams.

Ann Lesperance, national security advisor, joins the National Academies of Sciences, Engineering, and Medicine Committee on Applied Research Topics for Hazard Mitigation and Resilience.

A recent edition of the Infrastructure Resilience Research Group Journal featured an article written by PNNL researchers Rob Siefken and Jake Burns about “Design Basis Threat and the Low Threat Environment.”

Connected moments math shortcut shaves time and cost of quantum calculations while maintaining accuracy.

Researchers at PNNL revisit a disaster recovery framework for relevance to COVID-19 pandemic.

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.

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.

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.