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Media Contacts
![ORNL scientists have optimized the Pseudomonas putida bacterium to digest five of the most abundant components of lignocellulosic biomass simultaneously, supporting a highly efficient conversion process to create renewable fuels and chemicals from plants. Credit: Alli Werner/NREL,U.S. Dept of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-09/P%20Putida_1.png?h=5c41473f&itok=aqfqpwbE)
ORNL scientists have modified a single microbe to simultaneously digest five of the most abundant components of lignocellulosic biomass, a big step forward in the development of a cost-effective biochemical conversion process to turn plants into
![3D printed EMPOWER wall drawing](/sites/default/files/styles/list_page_thumbnail/public/2020-08/EMP_WALL11.jpg?h=1d9512c1&itok=3Q-UnrTY)
Oak Ridge National Laboratory researchers used additive manufacturing to build a first-of-its kind smart wall called EMPOWER.
![Drawing of skyrmions spins](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Skyrmion%20-%20v12%20%28NEW%20image%20from%20HNL%29_0.jpg?h=df0a286c&itok=qHEwvGTR)
Scientists discovered a strategy for layering dissimilar crystals with atomic precision to control the size of resulting magnetic quasi-particles called skyrmions.
![Simulation of short polymer chains](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Screen%20Shot%202020-07-27%20at%202.46.08%20PM_0.png?h=fc4031ca&itok=DVcIeNaW)
Oak Ridge National Laboratory scientists have discovered a cost-effective way to significantly improve the mechanical performance of common polymer nanocomposite materials.
![Cations between layers of MXene](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Cations_holistic_study_0.png?h=de4bb2b8&itok=gX7Dgpbe)
A team led by Oak Ridge National Laboratory developed a novel, integrated approach to track energy-transporting ions within an ultra-thin material, which could unlock its energy storage potential leading toward faster charging, longer-lasting devices.
![3D-printed 316L steel has been irradiated along with traditionally wrought steel samples. Researchers are comparing how they perform at various temperatures and varying doses of radiation. Credit: Jaimee Janiga/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2020-08/X2001337_TCR_IrradiatedMaterials_Bumpus_jnj-04.jpg?h=e3a8e2b5&itok=pXslTCBN)
It’s a new type of nuclear reactor core. And the materials that will make it up are novel — products of Oak Ridge National Laboratory’s advanced materials and manufacturing technologies.
![3D-printed intensified device](/sites/default/files/styles/list_page_thumbnail/public/2020-08/2019-P16563_0.jpg?h=036a71b7&itok=zp8oaqVN)
Oak Ridge National Laboratory researchers have designed and additively manufactured a first-of-its-kind aluminum device that enhances the capture of carbon dioxide emitted from fossil fuel plants and other industrial processes.
![William Peter](/sites/default/files/styles/list_page_thumbnail/public/2020-08/2017-P06951_0.jpg?h=c74750f6&itok=KrJNg4MJ)
The Society of Manufacturing Engineers, known as SME, has named William Peter, director of Oak Ridge National Laboratory’s Manufacturing Demonstration Facility in the Energy and Environmental Sciences Directorate, among its 2020 College of SME Fellows.
![Researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL. Credit: Luke Scime/ORNL, U.S. Dept. of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-08/Peregrine%20Chase%20Joslin_0.jpg?h=51c7b451&itok=4Hc6PNwu)
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.
![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.