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Media Contacts
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.
As rising global temperatures alter ecosystems worldwide, the need to accurately simulate complex environmental processes under evolving conditions is more urgent than ever.
Six science and technology innovators from across the United States will join the fifth cohort of Oak Ridge National Laboratory’s Innovation Crossroads program in June.
Researchers at Oak Ridge National Laboratory have developed a novel envelope system that diverts heat or coolness away from a building and stores it for future use.
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
Consumer buy-in is key to the future of a decarbonized transportation sector in which electric vehicles largely replace today’s conventionally fueled cars and trucks.
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.
In his career focused on energy storage science, Jianlin Li has learned that discovering new ways to process and assemble batteries is just as important as the development of new materials.
Through a consortium of Department of Energy national laboratories, ORNL scientists are applying their expertise to provide solutions that enable the commercialization of emission-free hydrogen fuel cell technology for heavy-duty
Scientists at Oak Ridge National Laboratory have devised a method to identify the unique chemical makeup of every lithium-ion battery around the world, information that could accelerate recycling, recover critical materials and resolve a growing waste stream.