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Media Contacts
![As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/PowerOutageTweets_map_0.png?h=6448fdc1&itok=AUit-O2Y)
Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.
![Laminations such as these are compiled to form the core of modern electric vehicle motors. ORNL has developed a software toolkit to speed the development of new motor designs and to improve the accuracy of their real-world performance.](/sites/default/files/styles/list_page_thumbnail/public/2019-02/Motors_OeRSTED_0.jpg?h=af53702d&itok=mT24R4WI)
Oak Ridge National Laboratory scientists have created open source software that scales up analysis of motor designs to run on the fastest computers available, including those accessible to outside users at the Oak Ridge Leadership Computing Facility.
![Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w Researchers used machine learning methods on the ORNL Compute and Data Environment for Science, or CADES, to map vegetation communities in the Kougarok Watershed on the Seward Peninsula of Alaska. The colors denote different types of vegetation, such as w](/sites/default/files/styles/list_page_thumbnail/public/rs2019_highlight_plot_3d.png?itok=5bROV_ys)
A team of scientists led by Oak Ridge National Laboratory used machine learning methods to generate a high-resolution map of vegetation growing in the remote reaches of the Alaskan tundra.
![ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La ORNL scientists used commuting behavior data from East Tennessee to demonstrate how machine learning models can easily accept new data, quickly re-train themselves and update predictions about commuting patterns. Credit: April Morton/Oak Ridge National La](/sites/default/files/styles/list_page_thumbnail/public/study_area_one_dest_2.jpg?itok=2cWFkQvW)
Oak Ridge National Laboratory geospatial scientists who study the movement of people are using advanced machine learning methods to better predict home-to-work commuting patterns.
![Nuclear—Deep space travel Nuclear—Deep space travel](/sites/default/files/styles/list_page_thumbnail/public/Screen%20Shot%202018-12-19%20at%2010.29.32%20AM.png?itok=hq0dlVIf)
By automating the production of neptunium oxide-aluminum pellets, Oak Ridge National Laboratory scientists have eliminated a key bottleneck when producing plutonium-238 used by NASA to fuel deep space exploration.
![Supercomputing-Memory_boost1.jpg Supercomputing-Memory_boost1.jpg](/sites/default/files/styles/list_page_thumbnail/public/Supercomputing-Memory_boost1.jpg?itok=dDR8CnYC)
Scientists at Oak Ridge National Laboratory and Hypres, a digital superconductor company, have tested a novel cryogenic, or low-temperature, memory cell circuit design that may boost memory storage while using less energy in future exascale and quantum computing applications.
![Picture2.png Picture2.png](/sites/default/files/styles/list_page_thumbnail/public/Picture2_1.png?itok=IV4n9XEh)
Oak Ridge National Laboratory scientists studying fuel cells as a potential alternative to internal combustion engines used sophisticated electron microscopy to investigate the benefits of replacing high-cost platinum with a lower cost, carbon-nitrogen-manganese-based catalyst.
![X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg X1800-REED-Maritime Risk Symposium 2018 logo-AM V5-01.jpg](/sites/default/files/styles/list_page_thumbnail/public/X1800-REED-Maritime%20Risk%20Symposium%202018%20logo-AM%20V5-01.jpg?itok=_AN4HV63)
Thought leaders from across the maritime community came together at Oak Ridge National Laboratory to explore the emerging new energy landscape for the maritime transportation system during the Ninth Annual Maritime Risk Symposium.
![Autonomous_vehicle_simulation_ORNL.jpg Autonomous_vehicle_simulation_ORNL.jpg](/sites/default/files/styles/list_page_thumbnail/public/Autonomous_vehicle_simulation_ORNL.jpg?itok=2pnITULi)
Self-driving cars promise to keep traffic moving smoothly and reduce fuel usage, but proving those advantages has been a challenge with so few connected and automated vehicles, or CAVs, currently on the road.
![Physics_silicon-detectors.jpg](/sites/default/files/styles/list_page_thumbnail/public/Physics_silicon-detectors.jpg?h=c920d705&itok=Q1fP5ZTi)
Physicists turned to the “doubly magic” tin isotope Sn-132, colliding it with a target at Oak Ridge National Laboratory to assess its properties as it lost a neutron to become Sn-131.