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Media Contacts
![Oak Ridge National Laboratory researchers used an invertible neural network, a type of artificial intelligence that mimics the human brain, to select the most suitable materials for desired properties, such as flexibility or heat resistance, with high chemical accuracy. The study could lead to more customizable materials design for industry.](/sites/default/files/styles/list_page_thumbnail/public/2022-04/CCSD_NeuralNetworkBanner.png?h=b16f811b&itok=fxqDEvs_)
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
![This image illustrates lattice distortion, strain, and ion distribution in metal halide perovskites, which can be induced by external stimuli such as light and heat. Image credit: Stephen Jesse/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2022-03/FerroicHalidePerovskite.jpg?h=b803af89&itok=eBzxpb4b)
A study by researchers at the ORNL takes a fresh look at what could become the first step toward a new generation of solar batteries.
![ORNL’s Joseph Lukens runs experiments in an optics lab. Credit: Jason Richards/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-03/2017-P08409.jpg?h=3c3b5e37&itok=vGSsxt7p)
Scientists’ increasing mastery of quantum mechanics is heralding a new age of innovation. Technologies that harness the power of nature’s most minute scale show enormous potential across the scientific spectrum
![A zoomed in view of downtown Chattanooga’s sensors, which allowed the researchers to create building occupancy schedules that could enable improved energy efficiency and faster emergency responses. Credit: Andy Berres/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-03/Voronoi%20View.png?h=820abd6c&itok=cesW_DEh)
Every day, hundreds of thousands of commuters across the country travel from houses, apartments and other residential spaces to commercial buildings — from offices and schools to gyms and grocery stores.
![An international team of researchers used Summit to model spin, charge and pair-density waves in cuprates, a type of copper alloy, to explore the materials’ superconducting properties. The results revealed new insights into the relationships between these dynamics as superconductivity develops. Credit: Jason Smith/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2022-02/MaierSpinBanner.png?h=ae114f5c&itok=rdZETb8v)
A study led by researchers at ORNL used the nation’s fastest supercomputer to close in on the answer to a central question of modern physics that could help conduct development of the next generation of energy technologies.
![Mars Rover 2020](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Mars_0.jpg?h=c44fcfa1&itok=gSstQOJO)
More than 50 current employees and recent retirees from ORNL received Department of Energy Secretary’s Honor Awards from Secretary Jennifer Granholm in January as part of project teams spanning the national laboratory system. The annual awards recognized 21 teams and three individuals for service and contributions to DOE’s mission and to the benefit of the nation.
![QLAN submit - A team from the U.S. Department of Energy’s Oak Ridge National Laboratory, Stanford University and Purdue University developed and demonstrated a novel, fully functional quantum local area network, or QLAN, to enable real-time adjustments to information shared with geographically isolated systems at ORNL using entangled photons passing through optical fiber. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/QLAN%20submit_0.jpg?h=cd715a88&itok=JV1MjQHH)
A rapidly emerging consensus in the scientific community predicts the future will be defined by humanity’s ability to exploit the laws of quantum mechanics.
![An ORNL-led team studied the SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects. Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/sars_cov_2_bk.png?h=05c2797f&itok=jQ2D9aTr)
To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from ORNL developed a novel technique.
![This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography. Credit: Ada Sedova/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/thermosipho_collabfold2_0.jpg?h=3432ff3c&itok=4xhLbjKZ)
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.
![Using quantum Monte Carlo methods, the researchers simulated bulk VO2. Yellow and turquoise represent changes in electron density between the excited and ground states of a compound composed of oxygen, in red, and vanadium, in blue, which allowed them to evaluate how an oxygen vacancy, in white, can alter the compound’s properties. Credit: Panchapakesan Ganesh/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-01/image001_0.png?h=11d99c73&itok=sdREw4na)
Neuromorphic devices — which emulate the decision-making processes of the human brain — show great promise for solving pressing scientific problems, but building physical systems to realize this potential presents researchers with a significant