![White car (Porsche Taycan) with the hood popped is inside the building with an american flag on the wall.](/sites/default/files/styles/featured_square_large/public/2024-06/2024-P09317.jpg?h=8f9cfe54&itok=m6sQhZRq)
Filter News
Area of Research
- Advanced Manufacturing (2)
- Biology and Environment (30)
- Biology and Soft Matter (1)
- Clean Energy (121)
- Computational Engineering (1)
- Computer Science (7)
- Electricity and Smart Grid (3)
- Functional Materials for Energy (1)
- Fusion and Fission (8)
- Materials (71)
- Materials for Computing (12)
- National Security (35)
- Neutron Science (13)
- Nuclear Science and Technology (1)
- Quantum information Science (4)
- Sensors and Controls (1)
- Supercomputing (36)
- Transportation Systems (2)
News Topics
- (-) Chemical Sciences (63)
- (-) Cybersecurity (35)
- (-) Grid (62)
- (-) Machine Learning (47)
- (-) Microscopy (51)
- (-) Net Zero (13)
- (-) Transportation (97)
- 3-D Printing/Advanced Manufacturing (121)
- Advanced Reactors (34)
- Artificial Intelligence (91)
- Big Data (53)
- Bioenergy (91)
- Biology (98)
- Biomedical (58)
- Biotechnology (22)
- Buildings (57)
- Clean Water (29)
- Climate Change (99)
- Composites (26)
- Computer Science (187)
- Coronavirus (46)
- Critical Materials (26)
- Decarbonization (79)
- Education (4)
- Element Discovery (1)
- Emergency (2)
- Energy Storage (108)
- Environment (194)
- Exascale Computing (37)
- Fossil Energy (5)
- Frontier (42)
- Fusion (54)
- High-Performance Computing (84)
- Hydropower (11)
- Irradiation (3)
- Isotopes (53)
- ITER (7)
- Materials (144)
- Materials Science (140)
- Mathematics (7)
- Mercury (12)
- Microelectronics (3)
- Molten Salt (8)
- Nanotechnology (60)
- National Security (61)
- Neutron Science (131)
- Nuclear Energy (108)
- Partnerships (44)
- Physics (61)
- Polymers (33)
- Quantum Computing (34)
- Quantum Science (69)
- Renewable Energy (2)
- Security (24)
- Simulation (47)
- Software (1)
- Space Exploration (25)
- Statistics (3)
- Summit (57)
- Sustainable Energy (125)
- Transformational Challenge Reactor (7)
Media Contacts
![Veda Galigekere is leading Oak Ridge National Laboratory’s work on fast, efficient, wireless charging of electric vehicles.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P00214_0.jpg?h=9f7a701f&itok=crDMVmT6)
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
![Low-cost, compact, printed sensor that can collect and transmit data on electrical appliances for better load monitoring](/sites/default/files/styles/list_page_thumbnail/public/2019-03/2019-P01301_0.jpg?h=c6980913&itok=y0S4bq0p)
Scientists at Oak Ridge National Laboratory have developed a low-cost, printed, flexible sensor that can wrap around power cables to precisely monitor electrical loads from household appliances to support grid operations.
![ORNL researcher Karren More has been elected fellow of the Microscopy Society of America.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/K_More_th.jpg?h=655057a4&itok=53tPHa-r)
OAK RIDGE, Tenn., March 22, 2019 – Karren Leslie More, a researcher at the Department of Energy’s Oak Ridge National Laboratory, has been elected fellow of the Microscopy Society of America (MSA) professional organization.
![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.
![To develop complex materials with superior properties, Vera Bocharova uses diverse methods including broadband dielectric spectroscopy. Credit: Oak Ridge National Laboratory, U.S. Dept. of Energy; photographer Jason Richards](/sites/default/files/styles/list_page_thumbnail/public/2019-02/2016-p05202.jpg?h=b6236d98&itok=w-Sd8giq)
Vera Bocharova at the Department of Energy’s Oak Ridge National Laboratory investigates the structure and dynamics of soft materials—polymer nanocomposites, polymer electrolytes and biological macromolecules—to advance materials and technologies for energy, medicine and other applications.
![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.
OAK RIDGE, Tenn., Feb. 12, 2019—A team of researchers from the Department of Energy’s Oak Ridge and Los Alamos National Laboratories has partnered with EPB, a Chattanooga utility and telecommunications company, to demonstrate the effectiveness of metro-scale quantum key distribution (QKD).
![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.
![ORNL alanine_graphic.jpg ORNL alanine_graphic.jpg](/sites/default/files/styles/list_page_thumbnail/public/ORNL%20alanine_graphic.jpg?itok=iRLfcOw-)
OAK RIDGE, Tenn., Jan. 31, 2019—A new electron microscopy technique that detects the subtle changes in the weight of proteins at the nanoscale—while keeping the sample intact—could open a new pathway for deeper, more comprehensive studies of the basic building blocks of life.