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Media Contacts
![Elizabeth Herndon uses spectroscopic techniques at ORNL to analyze the chemical composition of leaves and other environmental samples to better understand the soil carbon cycle. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-04/herndon1_0.jpg?h=e9eb73b3&itok=7hv7ziII)
ORNL biogeochemist Elizabeth Herndon is working with colleagues to investigate a piece of the puzzle that has received little attention thus far: the role of manganese in the carbon cycle.
![Cations between layers of MXene](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Cations_holistic_study_0.png?h=de4bb2b8&itok=gX7Dgpbe)
A team led by Oak Ridge National Laboratory developed a novel, integrated approach to track energy-transporting ions within an ultra-thin material, which could unlock its energy storage potential leading toward faster charging, longer-lasting devices.
![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