ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
A research team from the Department of Energy’s Oak Ridge and Lawrence Livermore national laboratories won the first Best Open-Source Contribution Award for its paper at the 37th IEEE International Parallel and Distributed Processing Symposium.
ORNL researchers, in collaboration with Enginuity Power Systems, demonstrated that a micro combined heat and power prototype, or mCHP, with a piston engine can achieve an overall energy efficiency greater than 93%.
Zheng Gai, a senior staff scientist at ORNL’s Center for Nanophase Materials Sciences, has been selected as editor-in-chief of the Spin Crossover and Spintronics section of Magnetochemistry.
Jordan Hachtel, a research scientist at ORNL’s Center for Nanophase Materials, has been elected to the Board of Directors for the Microanalysis Society.
Oak Ridge National Laboratory researchers demonstrated that microchannel heat exchangers in heating, ventilation and air conditioning units can keep refrigerants evenly and continually distributed by inserting a device called a piezoelectric-driven
Oak Ridge National Laboratory researchers demonstrated that an electrochemical sensor paired with a transmitter not only detects propane leaks within seconds, but it can also send a signal to alert emergency services.
A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
Oak Ridge National Laboratory, University of Tennessee and University of Central Florida researchers released a new high-performance computing code designed to more efficiently examine power systems and identify electrical grid disruptions, such as