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Media Contacts
![Researchers at Oak Ridge National Laboratory developed an eco-friendly foam insulation for improved building efficiency. Credit: Chad Malone/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-03/foam_thumbnail.png?h=b6717701&itok=O0z-knmD)
Scientists at ORNL developed a competitive, eco-friendly alternative made without harmful blowing agents.
![Researchers at ORNL designed a recyclable carbon fiber material to promote low-carbon manufacturing. Credit: Chad Malone/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-11/22-G02592_TomonoriSaito_CellReportsPysicalScienceCoverDesign_1mu.png?h=707772c7&itok=f9yiwb6p)
Oak Ridge National Laboratory scientists designed a recyclable polymer for carbon-fiber composites to enable circular manufacturing of parts that boost energy efficiency in automotive, wind power and aerospace applications.
![A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK](/sites/default/files/styles/list_page_thumbnail/public/2022-01/Observed%20data%20AI%20story%20tip.jpg?h=8e5dac0a&itok=wrAOsfIs)
Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity.
![ORNL’s green solvent enables environmentally friendly recycling of valuable Li-ion battery materials. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-06/metal_03.jpg?h=5510f2c5&itok=X9YPqOe5)
Scientists at Oak Ridge National Laboratory have developed a solvent that results in a more environmentally friendly process to recover valuable materials from used lithium-ion batteries, supports a stable domestic supply chain for new batteries
![A 3D printed turbine blade demonstrates the use of the new class of nickel-based superalloys that can withstand extreme heat environments without cracking or losing strength. Credit: ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2021-02/2019-P05612-2_0.jpg?h=cdf7d3ee&itok=XuA2HJ2w)
Oak Ridge National Laboratory researchers have demonstrated that a new class of superalloys made of cobalt and nickel remains crack-free and defect-resistant in extreme heat, making them conducive for use in metal-based 3D printing applications.
![Pella Marion](/sites/default/files/styles/list_page_thumbnail/public/2021-03/WMMPA%20Pella%20Marion%20790_Small.jpg?h=f14a4ec1&itok=ItU-Ca6U)
A new Department of Energy report produced by Oak Ridge National Laboratory details national and international trends in hydropower, including the role waterpower plays in enhancing the flexibility and resilience of the power grid.
![self-healing elastomers](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Buildings%20-%20Unbreakable%20bond-%20small.png?h=5ded6b27&itok=Du9vTz_5)
![Data collection instruments at the North Pole](/sites/default/files/styles/list_page_thumbnail/public/2020-11/49464270498_a1ff680b23_o_0.jpg?h=8afd2337&itok=zh9gntwP)
Researchers at Oak Ridge National Laboratory were part of an international team that collected a treasure trove of data measuring precipitation, air particles, cloud patterns and the exchange of energy between the atmosphere and the sea ice.
![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.