Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.
PNNL’s energy-efficient dehumidifier may reduce energy consumption by up to 50% in residential A/C systems and increase the range of electric vehicles by up to 75%. The system has been licensed to Montana Technologies.
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.
Svitlana Volkova, chief scientist for decision intelligence and analytics at PNNL, was invited as a panelist at the SIAM International Conference on Data Mining
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.
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.
PNNL data scientists Svitlana Volkova and Emily Saldanha, along with former PNNL intern Pamela Bilo Thomas, will publish their research on online information spread in Nature's Scientific Reports.
A new study projects that electricity demand tied to cooling U.S. buildings will grow as peak temperatures rise, and so too would the need for an expanded power sector.
Michael Henry, a senior data scientist at PNNL, has accepted a joint appointment at the Texas A&M University RELLIS Center for Applied Research and Experiential Learning.
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.
PNNL data scientists Henry Kvinge and Ted Fujimoto presented their research on few-shot learning and reinforcement learning, respectively, at workshops during the 2021 AAAI Conference on Artificial Intelligence.
As a member of the NAM board of directors, Brett Jefferson, PNNL data scientist, will help lead the professional association’s mission to advance mathematical excellence of underrepresented minorities.
PNNL-developed Water Balance Tool estimates consumption for major water end-uses. Understanding the breakout of water use identifies water efficiency opportunities and allows facility managers to spot potential system losses.
