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Media Contacts
![The OpeN-AM experimental platform, installed at the VULCAN instrument, features a robotic arm that prints layers of molten metal to create complex shapes. Credit: Jill Hemman/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/Picture2.jpg?h=3c75dc16&itok=_NLdJ0Po)
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
![Innovation Crossroads cohort 7](/sites/default/files/styles/list_page_thumbnail/public/2023-08/IC-cohort7-1000px.png?h=b6717701&itok=dHzO-FYD)
Seven entrepreneurs will embark on a two-year fellowship as the seventh cohort of Innovation Crossroads kicks off this month at ORNL. Representing a range of transformative energy technologies, Cohort 7 is a diverse class of innovators with promising new companies.
![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.
![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.
![Matt Sieger. Credit: Carlos Jones/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-05/2022-P00437_0.jpg?h=c6980913&itok=bGz_GUB0)
The Oak Ridge Leadership Computing Facility’s Matt Sieger has been named the project director for the OLCF-6 effort. This next OLCF undertaking will plan and build a world-class successor to the OLCF’s still-new exascale system, Frontier.
![The Frontier supercomputer at ORNL remains in the number one spot on the May 2023 TOP500 rankings, with an updated high-performance Linpack score of 1.194 exaflops. Engineers at the Oak Ridge Leadership Computing Facility, which houses Frontier and its predecessor Summit, expect that Frontier’s speeds could ultimately top 1.4 exaflops, or 1.4 quintillion calculations per second. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-05/2022-P07496_0.jpg?h=c6980913&itok=lkvzQLQ6)
With the world’s first exascale supercomputing system now open to full user operations, research teams are harnessing Frontier’s power and speed to tackle some of the most challenging problems in modern science.
![ytterbium](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Ytterbium-176%20approved%20crop_0.jpg?h=1f8bb2ae&itok=lTsZ7UjW)
ORNL’s electromagnetic isotope separator, or EMIS, made history in 2018 when it produced 500 milligrams of the rare isotope ruthenium-96, unavailable anywhere else in the world.
![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.