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Media Contacts
A team of researchers at Oak Ridge National Laboratory have demonstrated that designed synthetic polymers can serve as a high-performance binding material for next-generation lithium-ion batteries.
In the shifting landscape of global manufacturing, American ingenuity is once again giving U.S companies an edge with radical productivity improvements as a result of advanced materials and robotic systems developed at the Department of Energy’s Manufacturing Demonstration Facility (MDF) at Oak Ridge National Laboratory.
Scientists have discovered a way to alter heat transport in thermoelectric materials, a finding that may ultimately improve energy efficiency as the materials
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
An ORNL-led team's observation of certain crystalline ice phases challenges accepted theories about super-cooled water and non-crystalline ice. Their findings, reported in the journal Nature, will also lead to better understanding of ice and its various phases found on other planets, moons and elsewhere in space.
OAK RIDGE, Tenn., May 8, 2019—Oak Ridge National Laboratory and Lincoln Electric (NASDAQ: LECO) announced their continued collaboration on large-scale, robotic additive manufacturing technology at the Department of Energy’s Advanced Manufacturing InnovationXLab Summit.
A novel additive manufacturing method developed by researchers at Oak Ridge National Laboratory could be a promising alternative for low-cost, high-quality production of large-scale metal parts with less material waste.
When Scott Smith looks at a machine tool, he thinks not about what the powerful equipment used to shape metal can do – he’s imagining what it could do with the right added parts and strategies. As ORNL’s leader for a newly formed group, Machining and Machine Tool Research, Smith will have the opportunity to do just that.
Scientists at Oak Ridge National Laboratory have developed a low-cost, printed, flexible sensor that can wrap around power cables to precisely monitor electrical loads from household appliances to support grid operations.
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.