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Media Contacts
An Oak Ridge National Laboratory team developed a novel technique using sensors to monitor seismic and acoustic activity and machine learning to differentiate operational activities at facilities from “noise” in the recorded data.
A team of researchers has developed a novel, machine learning–based technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.
Several electrolyte and thin-film coating technologies, developed at Oak Ridge National Laboratory, have been licensed by BTRY, a battery technology company based in Virginia, to make batteries with increased energy density, at lower cost, and with an improved safety profile in crashes.
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.
ORNL scientists had a problem mapping the genomes of bacteria to better understand the origins of their physical traits and improve their function for bioenergy production.
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
Ten scientists from the Department of Energy’s Oak Ridge National Laboratory are among the world’s most highly cited researchers, according to a bibliometric analysis conducted by the scientific publication analytics firm Clarivate.
Analytical chemists at ORNL have developed a rapid way to measure isotopic ratios of uranium and plutonium collected on environmental swipes, which could help International Atomic Energy Agency analysts detect the presence of undeclared nuclear
Pengfei Cao, a polymer chemist at ORNL, has been chosen to receive a 2021 Young Investigator Award from the Polymeric Materials: Science and Engineering Division of the American Chemical Society, or ACS PMSE.