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Media Contacts
![ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-08/lab_on_crystal2_0.png?h=bc215d7c&itok=5Zsjkf9e)
An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.
![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.
![Drawing of thin-film cathode technology](/sites/default/files/styles/list_page_thumbnail/public/2020-07/Solid%20state%20stability%20check-batteries.jpg?h=850c4449&itok=PNDLwIw7)
Oak Ridge National Laboratory scientists seeking the source of charge loss in lithium-ion batteries demonstrated that coupling a thin-film cathode with a solid electrolyte is a rapid way to determine the root cause.
![Computing – Mining for COVID-19 connections](/sites/default/files/styles/list_page_thumbnail/public/2020-05/pubmedconnections-covid-19-2_0.png?h=3dbd9eac&itok=NPdQ3tCD)
Scientists have tapped the immense power of the Summit supercomputer at Oak Ridge National Laboratory to comb through millions of medical journal articles to identify potential vaccines, drugs and effective measures that could suppress or stop the
![Batteries - The 3D connection](/sites/default/files/styles/list_page_thumbnail/public/2020-05/Batteries_3D%20story%20tip_2.jpg?h=aeb34e32&itok=puhZ_584)
Oak Ridge National Laboratory researchers have developed a thin film, highly conductive solid-state electrolyte made of a polymer and ceramic-based composite for lithium metal batteries.
![Wireless charging – Special delivery for UPS](/sites/default/files/styles/list_page_thumbnail/public/2020-05/UPS_wireless_power_story%20tip_3000.jpg?h=3748d94f&itok=Xf2MDLEi)
Researchers at Oak Ridge National Laboratory demonstrated a 20-kilowatt bi-directional wireless charging system on a UPS plug-in hybrid electric delivery truck, advancing the technology to a larger class of vehicles and enabling a new energy storage method for fleet owners and their facilities.
![Materials — Molding molecular matter](/sites/default/files/styles/list_page_thumbnail/public/2020-04/Ebeam_IMAGE_Final_0.jpg?h=c4322a57&itok=uYF8ugqx)
Scientists at Oak Ridge National Laboratory used a focused beam of electrons to stitch platinum-silicon molecules into graphene, marking the first deliberate insertion of artificial molecules into a graphene host matrix.
![ORNL researchers developed sodium-ion batteries by pairing a high-energy oxide or phosphate cathode with a hard carbon anode and achieved 100 usage cycles at a one-hour charge and discharge rate. Credit: Mengya Li/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Sodium-ion_batteries_thumb.jpg?h=d91dfa5a&itok=gPCNMJ6R)
Researchers at ORNL demonstrated that sodium-ion batteries can serve as a low-cost, high performance substitute for rechargeable lithium-ion batteries commonly used in robotics, power tools, and grid-scale energy storage.
![A new computational approach by ORNL can more quickly scan large-scale satellite images, such as these of Puerto Rico, for more accurate mapping of complex infrastructure like buildings. Credit: Maxar Technologies and Dalton Lunga/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2020-02/Puerto_Rico_Resflow9.png?h=a0a1befd&itok=5n2fss_e)
A novel approach developed by scientists at ORNL can scan massive datasets of large-scale satellite images to more accurately map infrastructure – such as buildings and roads – in hours versus days.