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.

Three unused, 48,000-pound stainless steel canisters arrived at PNNL, bringing the chance to deepen research in spent nuclear fuel storage and transportation.

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

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.

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.

The PNNL-developed VOLTTRON™ software platform’s advancement has benefited from a community-driven approach. The technology has been used in buildings nationwide, including most recently on a university campus.

Five papers co-written by 23 PNNL researchers were named Superior Paper Award Winners by the Waste Management Symposia.

An international team used PNNL microscopy to answer questions about how uranium dioxide—used in nuclear power plants—might behave in long-term storage.

A new radiation-resistant material for the efficient capture of noble gases xenon and krypton makes it safer and cheaper to recycle spent nuclear fuel.

A chemistry paper on the used nuclear fuel recycling process, led by PNNL lab fellow Gregg Lumetta, ranked 18th in Scientific Reports for downloads in 2019

Nuclear Process Science Initiative researchers at PNNL gain insights into the formation and rupture of high-pressure gas bubbles in nuclear fuel.

PNNL employs deep learning strategies to advance Model Predictive Control (MPC), a highly promising solution for intelligent building operations.

PNNL’s Nuclear Process Science Initiative (NPSI) has developed a book that examines processes used to separate nuclear materials.

PNNL and Argonne researchers developed and tested a chemical process that successfully captures radioactive byproducts from used nuclear fuel so they could be sent to advanced reactors for destruction while also producing electrical power.

PNNL’s Intelligent Load Control technology manages and adjusts electricity use in buildings when there’s peak demand on the power grid.

A multi-institute research team is exploring ways to improve residential walls across America, making homes warmer and drier and delivering significant energy savings.

A PNNL technology enables automated Economic Dispatch, which coordinates the use of energy in a manner that enhances distributed generation, efficiency, renewables, and grid reliability.