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Media Contacts
![ORNL’s Fernanda Santos examines a soil sample at an NGEE Arctic field site in the Alaskan tundra in June 2022. Credit: Amy Breen, University of Alaska Fairbanks.](/sites/default/files/styles/list_page_thumbnail/public/2023-08/Fernanda_Nome_June2022.jpg?h=06de31ac&itok=VGxKV_uY)
Wildfires are an ancient force shaping the environment, but they have grown in frequency, range and intensity in response to a changing climate. At ORNL, scientists are working on several fronts to better understand and predict these events and what they mean for the carbon cycle and biodiversity.
![An illustration shows how the composite is pressed into a seamless aluminum liner, which is then sealed with an aluminum powder cap. The research is sponsored by the DOE Isotope Program. Credit: Chris Orosco/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/RadiumTargetIllustration_0.png?h=cba57ff2&itok=Hhq-h9v8)
Oak Ridge National Laboratory researchers have developed a method to simplify one step of radioisotope production — and it’s faster and safer.
![TIP graphic](/sites/default/files/styles/list_page_thumbnail/public/2023-06/TIPbg_1200.png?h=da33fe38&itok=y7ggwHLV)
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
![Frontier supercomputer](/sites/default/files/styles/list_page_thumbnail/public/2023-06/Frontier-logos_0.jpg?h=c6980913&itok=yuF5A0wj)
Innovations in artificial intelligence are rapidly shaping our world, from virtual assistants and chatbots to self-driving cars and automated manufacturing.
![ORNL researchers have developed a new pressing method, shown as blue circle on right, that produces a more uniform solid electrolyte than the traditionally processed material with more voids, shown as gray circle on left. The material can be integrated into a battery system, center, for improved stability and rate performance. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/Electrolyte.StoryTip_0.png?h=b6717701&itok=PIYcf5iS)
ORNL scientists found that a small tweak created big performance improvements in a type of solid-state battery, a technology considered vital to broader electric vehicle adoption.
![Rigoberto Advincula](/sites/default/files/styles/list_page_thumbnail/public/2023-06/2020-P08153.jpg?h=8f9cfe54&itok=J1Xib1hr)
Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.
![Andrew Lupini](/sites/default/files/styles/list_page_thumbnail/public/2023-04/lupini.png?h=181bc054&itok=c-ov-WoV)
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
![An Oak Ridge National Laboratory study compared classical computing techniques for compressing data with potential quantum compression techniques. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2023-04/QuantumCompression.png?h=9fa9abd8&itok=o0n1r7et)
A study led by Oak Ridge National Laboratory researchers identifies a new potential application in quantum computing that could be part of the next computational revolution.
![Marm Dixit, a Weinberg Distinguished Staff Fellow at Oak Ridge National Laboratory, was honored for his work on imaging techniques for solid state batteries. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-04/Marm.chair__0.jpg?h=036a71b7&itok=lKca1x8Z)
Marm Dixit, a Weinberg Distinguished Staff Fellow at ORNL has received the 2023 Rosalind Franklin Young Investigator Award.
![An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-04/atoms3.jpg?h=ab622562&itok=dNMzrFw8)
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.