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Media Contacts
![Transportation Energy Data Book Edition 37](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Transportation-Logging_the_miles_ORNL_0.jpg?h=ade3edc7&itok=wGiEijHl)
Oak Ridge National Laboratory’s latest Transportation Energy Data Book: Edition 37 reports that the number of vehicles nationwide is growing faster than the population, with sales more than 17 million since 2015, and the average household vehicle travels more than 11,000 miles per year.
![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.
![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.
![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.
![2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg 2018-P07635 BL-6 user - Univ of Guelph-6004R_sm[2].jpg](/sites/default/files/styles/list_page_thumbnail/public/2018-P07635%20BL-6%20user%20-%20Univ%20of%20Guelph-6004R_sm%5B2%5D.jpg?itok=DUdZNt_q)
A team of scientists, led by University of Guelph professor John Dutcher, are using neutrons at ORNL’s Spallation Neutron Source to unlock the secrets of natural nanoparticles that could be used to improve medicines.
![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.
![Researchers 3D printed molds for precasting concrete using the Big Area Additive Manufacturing, or BAAM™, system at DOE’s Manufacturing Demonstration Facility at ORNL. Complex, durable mold designs can be produced in less time than traditional wood or fib Researchers 3D printed molds for precasting concrete using the Big Area Additive Manufacturing, or BAAM™, system at DOE’s Manufacturing Demonstration Facility at ORNL. Complex, durable mold designs can be produced in less time than traditional wood or fib](/sites/default/files/styles/list_page_thumbnail/public/news/images/02%20-%203D-printed_precast_concrete_molds.gif?itok=nni1l9l2)
The construction industry may soon benefit from 3D printed molds to make concrete facades, promising lower cost and production time. Researchers at Oak Ridge National Laboratory are evaluating the performance of 3D printed molds used to precast concrete facades in a 42-story buildin...
![3D printed permanent magnets with increased density were made from an improved mixture of materials, which could lead to longer lasting, better performing magnets for electric motors, sensors and vehicle applications. Credit: Jason Richards/Oak Ridge Nati 3D printed permanent magnets with increased density were made from an improved mixture of materials, which could lead to longer lasting, better performing magnets for electric motors, sensors and vehicle applications. Credit: Jason Richards/Oak Ridge Nati](/sites/default/files/styles/list_page_thumbnail/public/news/images/06%20-%203D-printed_permament_magnet.jpg?itok=q28pGVEm)
Oak Ridge National Laboratory scientists have improved a mixture of materials used to 3D print permanent magnets with increased density, which could yield longer lasting, better performing magnets for electric motors, sensors and vehicle applications. Building on previous research, ...