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Media Contacts
![ORNL researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites, demonstrating the potential for the use of large-scale multimaterial preforms to create molded composites. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/compressionMold01.jpg?h=985dab9b&itok=4DgnSlRM)
Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.
![self-healing elastomers](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Buildings%20-%20Unbreakable%20bond-%20small.png?h=5ded6b27&itok=Du9vTz_5)
![An X-ray CT image of a 3D-printed metal turbine blade was reconstructed using ORNL’s neural network and advanced algorithms. Credit: Amir Ziabari/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Manufacturing%20-%20Defect%20detection%202_0.jpg?h=259e5a75&itok=CwpLQv6U)
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
![A Co-Optima research team led by Oak Ridge National Laboratory’s Jim Szybist in collaboration with Argonne, Sandia and the National Renewable Energy Laboratory, created a merit function tool that evaluates six fuel properties and their impact on engine performance, giving the scientific community a guide to quickly evaluate biofuels. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-12/2017-P08539-2_0.jpg?h=b6236d98&itok=h0OT2BqC)
As ORNL’s fuel properties technical lead for the U.S. Department of Energy’s Co-Optimization of Fuel and Engines, or Co-Optima, initiative, Jim Szybist has been on a quest for the past few years to identify the most significant indicators for predicting how a fuel will perform in engines designed for light-duty vehicles such as passenger cars and pickup trucks.
![ORNL researchers in advanced manufacturing, materials science and engineering collaborated to produce face shields and reusable mask molds so that industry can quickly mass produce. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-05/MDF_group_shot.jpg?h=5e9da067&itok=hx6y5O6o)
The University of Texas at San Antonio (UTSA) has formally launched the Cybersecurity Manufacturing Innovation Institute (CyManII), a $111 million public-private partnership.
![These fuel assembly brackets, manufactured by ORNL in partnership with Framatome and Tennessee Valley Authority, are the first 3D-printed safety-related components to be inserted into a nuclear power plant. Credit: Fred List/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-10/FramatomeCB1.jpg?h=7c790887&itok=oVGkqZYZ)
The Transformational Challenge Reactor, or TCR, a microreactor built using 3D printing and other new advanced technologies, could be operational by 2024.
![Unique imaging capabilities yield new knowledge, growth for bioeconomy](/sites/default/files/styles/list_page_thumbnail/public/2020-08/2020-p00914_0.jpg?h=8f9cfe54&itok=LU-qd6IM)
Scientists at the Department of Energy’s Oak Ridge National Laboratory have a powerful new tool in the quest to produce better plants for biofuels, bioproducts and agriculture.
![Cars and coronavirus](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Transportation-Gauging_pandemic_impact_ORNL_0.jpg?h=4a7d1ed4&itok=Xqx4kknO)
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
![Map with focus on sub-saharan Africa](/sites/default/files/styles/list_page_thumbnail/public/2020-07/firms3-Africa-NASA_0.jpg?h=27f1d52b&itok=G8uUS5cH)
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
![Colorized micrograph of lily pollen](/sites/default/files/styles/list_page_thumbnail/public/2020-07/Lily_CH%20and%20CO_1.png?h=436b82d4&itok=lntoWKVr)
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.