OAK RIDGE, Tenn., Dec. 12, 2019 — Oak Ridge National Laboratory and five leading building equipment industries will collaborate to improve the energy performance of heating, air conditioning and ventilation systems and investigate climate-friendly alternative refrigerants.
Students often participate in internships and receive formal training in their chosen career fields during college, but some pursue professional development opportunities even earlier.
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.
A joint research team from Google Inc., NASA Ames Research Center, and the Department of Energy’s Oak Ridge National Laboratory has demonstrated that a quantum computer can outperform a classical computer
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.
Processes like manufacturing aircraft parts, analyzing data from doctors’ notes and identifying national security threats may seem unrelated, but at the U.S. Department of Energy’s Oak Ridge National Laboratory, artificial intelligence is improving all of these tasks.
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 team including Oak Ridge National Laboratory and University of Tennessee researchers demonstrated a novel 3D printing approach called Z-pinning that can increase the material’s strength and toughness by more than three and a half times compared to conventional additive manufacturing processes.
Artificial intelligence (AI) techniques have the potential to support medical decision-making, from diagnosing diseases to prescribing treatments. But to prioritize patient safety, researchers and practitioners must first ensure such methods are accurate.