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.

U.S. Secretary of Energy Jennifer M. Granholm virtually visits PNNL, one of several national lab visits she is conducting.

PNNL’s Supriya Goel has been named by Consulting-Specifying Engineer as one of 2021’s 40 outstanding nonresidential building industry professionals age 40 or younger.

When the COVID-19 pandemic halted all travel for in-person inspections, a team at PNNL knew they needed to find a way to perform assessments virtually. Their solution—a portable kit that could be shipped to locations.

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.

Vigorous and rapid air exchanges might not always be a good thing when it comes to levels of coronavirus particles in a multiroom building, according to a new modeling study.

An HVAC system energy efficiency analysis method developed by PNNL is now included in the Washington State Energy Code.

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

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

PNNL provided expert analysis and technical background for some of the most ambitious building energy efficiency codes proposed for this year's International Energy Conservation Code updates.

New approach allows nonexperts to optimize control of a building's energy systems without adding computing power or proprietary software.

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

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’s longstanding grid and buildings capabilities are driving two projects that test transactive energy concepts on a grand scale and lay the groundwork for a more efficient U.S. energy system.

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

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.