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Media Contacts
![ORNL biogeochemist Teri O’Meara is focused on improving how coastal systems are represented in global climate models, enabling better predictions about the future of these critical ecosystems. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-03/2022-P00647_0.jpg?h=8f9cfe54&itok=0G7wpXG6)
Surrounded by the mountains of landlocked Tennessee, Oak Ridge National Laboratory’s Teri O’Meara is focused on understanding the future of the vitally important ecosystems lining the nation’s coasts.
![A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK](/sites/default/files/styles/list_page_thumbnail/public/2022-01/Observed%20data%20AI%20story%20tip.jpg?h=8e5dac0a&itok=wrAOsfIs)
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.
![The Energy Exascale Earth System Model project reliably simulates aspects of earth system variability and projects decadal changes that will critically impact the U.S. energy sector in the future. A new version of the model delivers twice the performance of its predecessor. Credit: E3SM, Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/E3SM_0.jpg?h=d5571230&itok=lKS66vCl)
A new version of the Energy Exascale Earth System Model, or E3SM, is two times faster than an earlier version released in 2018.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
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.
![Santa Jansone-Popova, left, and Ilja Popovs quantify rare-earth element concentrations in liquid samples using a spectroscopy instrument. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-11/2021-P08288_0.jpg?h=10d202d3&itok=5CV3V1zL)
A new technology for rare-earth elements chemical separation has been licensed to Marshallton Research Laboratories, a North Carolina-based manufacturer of organic chemicals for a range of industries.
![U.S. Secretary of Energy Granholm tours ORNL’s world-class science facilities](/sites/default/files/styles/list_page_thumbnail/public/2021-11/2021-P09409.jpg?h=036a71b7&itok=C8b0_-Vk)
Energy Secretary Jennifer Granholm visited ORNL on Nov. 22 for a two-hour tour, meeting top scientists and engineers as they highlighted projects and world-leading capabilities that address some of the country’s most complex research and technical challenges.
![Automated disassembly line aims to make battery recycling safer, faster](/sites/default/files/styles/list_page_thumbnail/public/2021-08/disassembly.jpg?h=4e81470f&itok=Eg_1yckZ)
Researchers at ORNL have developed a robotic disassembly system for spent electric vehicle battery packs to safely and efficiently recycle and reuse critical materials while reducing toxic waste.
![Benjamin Sulman, a scientist in ORNL’s Environmental Sciences Division, creates Earth system models that simulate how plants, microbes and soils interact and influence the cycling of carbon, water and nutrients in their environment. His work aims to helps researchers across disciplines better understand complex, rapidly changing ecosystems, including coastal wetlands and Arctic permafrost soils. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/2020-P17155.jpg?h=8f9cfe54&itok=6M4vpxvC)
As rising global temperatures alter ecosystems worldwide, the need to accurately simulate complex environmental processes under evolving conditions is more urgent than ever.
![ORNL’s green solvent enables environmentally friendly recycling of valuable Li-ion battery materials. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/metal_03.jpg?h=5510f2c5&itok=X9YPqOe5)
Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries
![Oak Ridge National Laboratory’s MENNDL AI software system can design thousands of neural networks in a matter of hours. One example uses a driving simulator to evaluate a network’s ability to perceive objects under various lighting conditions. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-04/CARLA%20MENNDL%20sim001_1.png?h=e2caa22a&itok=tvE9seMo)
The Department of Energy’s Oak Ridge National Laboratory has licensed its award-winning artificial intelligence software system, the Multinode Evolutionary Neural Networks for Deep Learning, to General Motors for use in vehicle technology and design.