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Media Contacts
![A new method to control quantum states in a material is shown. The electric field induces polarization switching of the ferroelectric substrate, resulting in different magnetic and topological states. Credit: Mina Yoon, Fernando Reboredo, Jacquelyn DeMink/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/pnglbernardstorytip.png?h=d1cb525d&itok=NOT32zpa)
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
![Ashley Barker. Credit: Carlos Jones/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-05/2022-P14022.jpg?h=c6980913&itok=Su1w1TDa)
At the National Center for Computational Sciences, Ashley Barker enjoys one of the least complicated–sounding job titles at ORNL: section head of operations. But within that seemingly ordinary designation lurks a multitude of demanding roles as she oversees the complete user experience for NCCS computer systems.
![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.
![Researchers used quantum Monte Carlo calculations to accurately render the structure and electronic properties of germanium selenide, a semiconducting nanomaterial. Credit: Paul Kent/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2022-09/ECP-storytip_0.png?h=e58db2e8&itok=ZzbB2Z-f)
A multi-lab research team led by ORNL's Paul Kent is developing a computer application called QMCPACK to enable precise and reliable predictions of the fundamental properties of materials critical in energy research.
![Genetic analysis revealed connections between inflammatory activity and development of atomic dermatitis, according to researchers from the UPenn School of Medicine, the Perelman School of Medicine, and Oak Ridge National Laboratory. Credit: Kang Ko/UPenn](/sites/default/files/styles/list_page_thumbnail/public/2022-02/Graves-AD_0.jpg?h=46d8a70d&itok=77AW7Swv)
University of Pennsylvania researchers called on computational systems biology expertise at Oak Ridge National Laboratory to analyze large datasets of single-cell RNA sequencing from skin samples afflicted with atopic dermatitis.
![self-healing elastomers](/sites/default/files/styles/list_page_thumbnail/public/2021-01/Buildings%20-%20Unbreakable%20bond-%20small.png?h=5ded6b27&itok=Du9vTz_5)
![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.
![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.