Researchers from PNNL have been assessing installation and use of electric heat pumps in an Alaskan community that relies on fuel oil for heat. The resulting information could advance electrification in cold rural areas across the nation.

Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

DOE Integrated Lighting Campaign organizers introduce new recognition categories in horticulture, innovative financing, and energy equity.

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

PNNL will play a key role in advancing Connected Communities made up of efficient homes and buildings that communicate with the grid to produce energy and environmental benefits.

Researchers to design their own computer accelerators for faster analysis of large datasets.

The first customized resource of its kind, H-BEST analyzes the indoor environmental quality profile for buildings and helps its users identify the costs and benefits of improvements.

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.

Risk analysis on the plutonium-fueled power system that supplies electricity to the Mars rover answered the “what if” nuclear safety questions for NASA.

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 researchers are using explainable artificial intelligence to develop new ways to understand and interpret data for national security.

Explainable artificial intelligence—understanding and explaining the reasoning behind AI decisions—is a necessity for national security.

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

Explainable AI helps scientists understand and untangle the threads of information that the system uses to make choices or recommendations.

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.

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.