Buildings use 40 percent of America’s primary energy and 75 percent of its electricity, which can jump to 80 percent when a majority of the population is at home using heating or cooling systems and the seasons reach their extremes.
ORNL researchers created and tested new wireless charging designs that may double the power density, resulting in a lighter weight system compared with existing technologies.
ORNL and The University of Toledo have entered into a memorandum of understanding for collaborative research.
Researchers at Oak Ridge National Laboratory demonstrated that metal foam enhances the evaporation process in thermal conversion systems and enables the development of compact HVAC&R units.
Quanex Building Products has signed a non-exclusive agreement to license a method to produce insulating material from ORNL. The low-cost material can be used as an additive to increase thermal insulation performance and improve energy efficiency when applied to a variety of building products.
A modern, healthy transportation system is vital to the nation’s economic security and the American standard of living. The U.S. Department of Energy’s Oak Ridge National Laboratory (ORNL) is engaged in a broad portfolio of scientific research for improved mobility
Researchers at Oak Ridge National Laboratory proved that a certain class of ionic liquids, when mixed with commercially available oils, can make gears run more efficiently with less noise and better durability.
A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
An online tool developed by researchers at Oak Ridge National Laboratory provides architects and engineers a fast and efficient way to assess the performance of a building’s envelope design before construction begins.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.