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.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.
Oak Ridge National Laboratory is training next-generation cameras called dynamic vision sensors, or DVS, to interpret live information—a capability that has applications in robotics and could improve autonomous vehicle sensing.
A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns
In Hong Wang’s world, nothing is beyond control. Before joining Oak Ridge National Laboratory as a senior distinguished researcher in transportation systems, he spent more than three decades studying the control of complex industrial systems in the United Kingdom.
Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.
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.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
Oak Ridge National Laboratory is using artificial intelligence to analyze data from published medical studies associated with bullying to reveal the potential of broader impacts, such as mental illness or disease.