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Media Contacts
![ORNL researchers are demonstrating an automation system for this portable system, currently based in Colorado, for treatment of non-traditional water sources to drinking water standards. Credit: Tzahi Cath/Colorado School of Mines](/sites/default/files/styles/list_page_thumbnail/public/2023-09/NAWI_comp01_0.jpg?h=d1cb525d&itok=I2fCHpSN)
Researchers at ORNL are developing advanced automation techniques for desalination and water treatment plants, enabling them to save energy while providing affordable drinking water to small, parched communities without high-quality water supplies.
![The DEMAND single crystal diffractometer at the High Flux Isotope Reactor, or HFIR, is the latest neutron instrument at the Department of Energy’s Oak Ridge National Laboratory to be equipped with machine learning-assisted software, called ReTIA. Credit: Jeremy Rumsey/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-09/DEMAND%20thumbnail%20image_0.jpg?h=c673cd1c&itok=5YAVwaP6)
Neutron experiments can take days to complete, requiring researchers to work long shifts to monitor progress and make necessary adjustments. But thanks to advances in artificial intelligence and machine learning, experiments can now be done remotely and in half the time.
![ORNL Vehicle Power Electronics Research group R&D Associate Subho Mukherjee has been elevated to the senior member grade IEEE. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/2019-P01533.jpg?h=4d0d7e9c&itok=FIWOFo8C)
Subho Mukherjee, an R&D associate in the Vehicle Power Electronics Research group at the Department of Energy’s Oak Ridge National Laboratory, has been elevated to the grade of senior member of the Institute of Electrical and Electronics Engineers.
![ZEISS Head of Additive Manufacturing Technology Claus Hermannstaedter, left, and ORNL Interim Associate Laboratory Director for Energy Science and Technology Rick Raines sign a licensing agreement that allows ORNL’s machine-learning algorithm, Simurgh, to be used for rapid evaluations of 3D-printed components with industrial X-ray computed tomography, or CT. Using machine learning in CT scanning is expected to reduce the time and cost of inspections of 3D-printed parts by more than ten times.](/sites/default/files/styles/list_page_thumbnail/public/2023-08/ZEISS%20signing%20handshake_0.jpg?h=c6980913&itok=4J8nVrPc)
A licensing agreement between the Department of Energy’s Oak Ridge National Laboratory and research partner ZEISS will enable industrial X-ray computed tomography, or CT, to perform rapid evaluations of 3D-printed components using ORNL’s machine
![AIRES 4 attendees hailing from seven national laboratories and from academia met to discuss robust engineering for digital twins. Credit: Pradeep Ramuhalli/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-08/aires_attendees_0.jpg?h=9fc2b970&itok=20wrmyuA)
ORNL hosted its fourth Artificial Intelligence for Robust Engineering and Science, or AIRES, workshop from April 18-20. Over 100 attendees from government, academia and industry convened to identify research challenges and investment areas, carving the future of the discipline.
![Yarom Polsky studio portrait](/sites/default/files/styles/list_page_thumbnail/public/2023-07/Yarom%20Polsky_0.jpg?h=0e6c7b49&itok=9H4BJ5Wm)
Yarom Polsky, director of the Manufacturing Science Division, or MSD, at the Department of Energy’s Oak Ridge National Laboratory, has been elected a Fellow of the American Society of Mechanical Engineers, or ASME.
![Clouds of gray smoke in the lower left are funneled northward from wildfires in Western Canada, reaching the edge of the sea ice covering the Arctic Ocean. A second path of thick smoke is visible at the top center of the image, emanating from wildfires in the boreal areas of Russia’s Far East, in this image captured on July 13, 2023. Credit: NASA MODIS](/sites/default/files/styles/list_page_thumbnail/public/2023-07/NASA%20Arctic%20Circle%20wildfire%20smoke_image07182023_1km_1.jpg?h=dbdc3f84&itok=oHQVs6Bn)
Wildfires have shaped the environment for millennia, but they are increasing in frequency, range and intensity in response to a hotter climate. The phenomenon is being incorporated into high-resolution simulations of the Earth’s climate by scientists at the Department of Energy’s Oak Ridge National Laboratory, with a mission to better understand and predict environmental change.
![ORNL researchers used geotagged photos to map crude oil train routes in the U.S. The mapping gives transportation planners insight into understanding potential impacts along the routes. Credit: ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-07/trainMap%5B69%5D.png?h=804c67fb&itok=LM393FRy)
Oak Ridge National Laboratory researchers used images from a photo-sharing website to identify crude oil train routes across the nation to provide data that could help transportation planners better understand regional impacts.
![ORNL researchers have enabled standard raised pavement markers to transmit GPS information that helps autonomous driving features function better in remote areas or in bad weather. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/markers_0.jpg?h=804c67fb&itok=xstjOxQo)
Working with Western Michigan University and other partners, ORNL engineers are placing low-powered sensors in the reflective raised pavement markers that are already used to help drivers identify lanes. Microchips inside the markers transmit information to passing cars about the road shape to help autonomous driving features function even when vehicle cameras or remote laser sensing, called LiDAR, are unreliable because of fog, snow, glare or other obstructions.
![CFM’s RISE open fan engine architecture. Image: GE Aerospace](/sites/default/files/styles/list_page_thumbnail/public/2023-06/02-CFM_RISE_Program_Open_Fan%5B1%5D_0.jpg?h=790be497&itok=Ulzp5W_p)
To support the development of a revolutionary new open fan engine architecture for the future of flight, GE Aerospace has run simulations using the world’s fastest supercomputer capable of crunching data in excess of exascale speed, or more than a quintillion calculations per second.