News Releases

Plasma many times hotter than the surface of the sun swirls inside of a large device. From the outside, the device looks like a metal ring surrounded by scaffolding and walkways. But inside, the device is creating the conditions needed to achieve fusion – the process that powers our sun and every star. Researchers supported by the Department of Energy’s (DOE) Office of Science are working to improve our understanding of the process of fusion with the goal of commercializing fusion energy. In particular, scientists at DOE’s Princeton Plasma Physics Laboratory (PPPL) have made a big step forward in advancing stellarators, one type of fusion device.

Four researchers from the Department of Energy’s Oak Ridge National Laboratory were recognized as Highly Cited Researchers by Clarivate, a data analytics firm that specializes in scientific and academic research; Clarivate calculates impact factor using data from Web of Science. Highly Cited Researchers rank in the top 1% by citations for their field and publication year.

Teletrix, a company specializing in radiation training tools, has transitioned from a research and development license to a commercial license for its augmented reality, or AR, platform that simulates ionizing radiation. This advanced platform, known as VIZRAD AR, was developed using technologies licensed from the Department of Energy’s Oak Ridge National Laboratory and allows users to interact with virtual radiological environments in real time. 

Seven scientists affiliated with the Department of Energy’s Oak Ridge National Laboratory have been named Battelle Distinguished Inventors in recognition of being granted 14 or more United States patents. Since Battelle began managing ORNL in 2000, 104 ORNL researchers have reached this milestone.

A team of researchers from the U. S. Department of Energy Ames National Laboratory developed a magnetocaloric heat pump that matches current vapor-compression heat pumps for weight, cost, and performance.

Berkeley Lab and several collaborating institutions have successfully demonstrated a machine-learning technique to accelerate discovery of materials for film capacitors — crucial components in electrification and renewable energy technologies. The technique was used to screen a library of nearly 50,000 chemical structures to identify a compound with record-breaking performance.