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Media Contacts
![ORNL researchers and energy storage startup Sparkz have developed a cobalt-free cathode material for use in lithium-ion batteries Credit: Ilias Belharouak/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/cobalt-sparkz_0.jpg?h=cd715a88&itok=vTU2FKUY)
Four research teams from the Department of Energy’s Oak Ridge National Laboratory and their technologies have received 2020 R&D 100 Awards.
![Smart Neighborhood homes](/sites/default/files/styles/list_page_thumbnail/public/2020-01/04.09.TD-SMartHome_0.jpg?h=5b5a5437&itok=22S5Tle1)
To better determine the potential energy cost savings among connected homes, researchers at Oak Ridge National Laboratory developed a computer simulation to more accurately compare energy use on similar weather days.
![Catherine Schuman during Hour of Code](/sites/default/files/styles/list_page_thumbnail/public/2019-12/IMG_0136_0.jpg?h=71976bb4&itok=56CtnbAH)
ORNL computer scientist Catherine Schuman returned to her alma mater, Harriman High School, to lead Hour of Code activities and talk to students about her job as a researcher.
![Motion sensing technology](/sites/default/files/styles/list_page_thumbnail/public/2019-07/Coin-spin-ORNL.jpg?h=dbfb0746&itok=LtrLTeNM)
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.
![Computing—Building a brain](/sites/default/files/styles/list_page_thumbnail/public/2019-06/CADES2019-P00182_0.jpg?h=c6980913&itok=eyahnQde)
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.
![Computing—Routing out the bugs](/sites/default/files/styles/list_page_thumbnail/public/2019-11/VA-HealthIT-2019-P04263.jpg?h=784bd909&itok=uwv091uK)
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