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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.
![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.
![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.
![The hybrid inverter developed by ORNL is an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and interact efficiently with the utility power grid. Credit: Carlos Jones, ORNL/U.S. Dept of Energy.](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2020-P09169.jpg?h=42d56c10&itok=Yb1_gWYE)
ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.
![Sergei Kalinin](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2019-P00126_0.png?h=5969a3b5&itok=66cucDCt)
Five researchers at the Department of Energy’s Oak Ridge National Laboratory have been named ORNL Corporate Fellows in recognition of significant career accomplishments and continued leadership in their scientific fields.
![An organic solvent and water separate and form nanoclusters on the hydrophobic and hydrophilic sections of plant material, driving the efficient deconstruction of biomass. Credit: Michelle Lehman/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-07/THF_high_res.gif?h=5a472534&itok=5peedFnF)
Scientists at ORNL used neutron scattering and supercomputing to better understand how an organic solvent and water work together to break down plant biomass, creating a pathway to significantly improve the production of renewable
![Burak Ozpineci](/sites/default/files/styles/list_page_thumbnail/public/2020-07/2016-P07072_0.jpg?h=a31ffb6c&itok=dsHTBEvN)
Burak Ozpineci of the Electrical and Electronics Systems Research Division at Oak Ridge National Laboratory has won the 2020 IEEE Power Electronics Society Vehicle and Transportation Systems Achievement Award.
![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.