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Media Contacts
![ORNL’s David Sholl is director of the new DOE Energy Earthshot Non-Equilibrium Energy Transfer for Efficient Reactions center to help decarbonize the industrial chemical industry. Credit: Genevieve Martin, ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2021-P04915.David_.Sholl_.jpg?h=c6980913&itok=qT7ZMJX2)
ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
![Connecting wires to the interface of the topological insulator and superconductor enables probing of novel electronic properties. Researchers aim for qubits based on theorized Majorana particles. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/2023-P04516.jpg?h=c6980913&itok=BoCZtfwR)
Quantum computers process information using quantum bits, or qubits, based on fragile, short-lived quantum mechanical states. To make qubits robust and tailor them for applications, researchers from the Department of Energy’s Oak Ridge National Laboratory sought to create a new material system.
![A new nanoscience study led by an ORNL quantum researcher takes a big-picture look at how scientists study materials at the smallest scales. Credit: Getty Images](/sites/default/files/styles/list_page_thumbnail/public/2023-08/QuantumTunnel_0.png?h=ae114f5c&itok=B4Rxkkvs)
A new nanoscience study led by a researcher at ORNL takes a big-picture look at how scientists study materials at the smallest scales.
![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.
![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.
![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.
![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 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.