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Media Contacts
![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.
![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.
![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.
![ORNL researchers have enabled standard raised pavement markers to transmit GPS information that helps autonomous driving features function better in remote areas or in bad weather. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/markers_0.jpg?h=804c67fb&itok=xstjOxQo)
Working with Western Michigan University and other partners, ORNL engineers are placing low-powered sensors in the reflective raised pavement markers that are already used to help drivers identify lanes. Microchips inside the markers transmit information to passing cars about the road shape to help autonomous driving features function even when vehicle cameras or remote laser sensing, called LiDAR, are unreliable because of fog, snow, glare or other obstructions.
![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.
![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.
![Robert Wagner](/sites/default/files/styles/list_page_thumbnail/public/2023-04/wagner.png?h=564c27f4&itok=cfPXByG6)
SAE International has awarded ORNL Buildings and Transportation Science Division Director Robert Wagner with the SAE Medal of Honor for his dedication and support of the organization’s mission of advancing mobility solutions.
![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.