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Media Contacts
![Quantum—Squeezed light cuts noise](/sites/default/files/styles/list_page_thumbnail/public/2019-06/Quantum-Squeezed_light_cuts_noise_0.jpg?h=557ecedc&itok=dbeUQ4mY)
Oak Ridge National Laboratory physicists studying quantum sensing, which could impact a wide range of potential applications from airport security scanning to gravitational wave measurements, have outlined in ACS Photonics the dramatic advances in the field.
![Nuclear—Tiny testing fuels](/sites/default/files/styles/list_page_thumbnail/public/2019-05/MiniFuel_2019-P03618_0.jpg?h=49ab6177&itok=VVYMAZ3E)
For the first time, Oak Ridge National Laboratory has completed testing of nuclear fuels using MiniFuel, an irradiation vehicle that allows for rapid experimentation.
![Strain-tolerant, triangular, monolayer crystals of WS2 were grown on SiO2 substrates patterned with donut-shaped pillars, as shown in scanning electron microscope (bottom) and atomic force microscope (middle) image elements.](/sites/default/files/styles/list_page_thumbnail/public/2019-06/Image%201_5.jpg?h=62c69fe2&itok=NWF1WS0c)
A team led by scientists at the Department of Energy’s Oak Ridge National Laboratory explored how atomically thin two-dimensional (2D) crystals can grow over 3D objects and how the curvature of those objects can stretch and strain the
![Veda Galigekere is leading Oak Ridge National Laboratory’s work on fast, efficient, wireless charging of electric vehicles.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P00214_0.jpg?h=9f7a701f&itok=crDMVmT6)
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.
![Pictured in this early conceptual drawing, the Translational Research Capability planned for Oak Ridge National Laboratory will follow the design of research facilities constructed during the laboratory’s modernization campaign.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/TRCimage.jpg?h=2ee3f751&itok=9rywjcFh)
OAK RIDGE, Tenn., May 7, 2019—Energy Secretary Rick Perry, Congressman Chuck Fleischmann and lab officials today broke ground on a multipurpose research facility that will provide state-of-the-art laboratory space
![Small modular reactor computer simulation](/sites/default/files/styles/list_page_thumbnail/public/2019-04/Nuclear_simulation_scale-up.jpg?h=5992a83f&itok=A0oscIPL)
In a step toward advancing small modular nuclear reactor designs, scientists at Oak Ridge National Laboratory have run reactor simulations on ORNL supercomputer Summit with greater-than-expected computational efficiency.
![Transportation Energy Data Book Edition 37](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Transportation-Logging_the_miles_ORNL_0.jpg?h=ade3edc7&itok=wGiEijHl)
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
![Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Motors_OeRSTED_0.jpg?h=af53702d&itok=mT24R4WI)
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.