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Media Contacts
![TIP graphic](/sites/default/files/styles/list_page_thumbnail/public/2023-06/TIPbg_1200.png?h=da33fe38&itok=y7ggwHLV)
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
![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.
![ORNL seismic researcher Chengping Chai placed seismic sensors on the ground at various distances from an ORNL nuclear reactor to learn whether they could detect its operating state. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/2023-P03398.jpg?h=3e43625b&itok=TXK8tthh)
Like most scientists, Chengping Chai is not content with the surface of things: He wants to probe beyond to learn what’s really going on. But in his case, he is literally building a map of the world beneath, using seismic and acoustic data that reveal when and where the earth moves.
![ORNL researchers, from left, Yang Liu, Xiaohan Yang and Torik Islam, collaborated on the development of a new capability to insert multiple genes simultaneously for fast, efficient transformation of plants into better bioenergy feedstocks. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-06/Gene%20stacking%202023-P03111_0.jpg?h=c6980913&itok=RSUZXZ8U)
In a discovery aimed at accelerating the development of process-advantaged crops for jet biofuels, scientists at ORNL developed a capability to insert multiple genes into plants in a single step.
![Rigoberto Advincula](/sites/default/files/styles/list_page_thumbnail/public/2023-06/2020-P08153.jpg?h=8f9cfe54&itok=J1Xib1hr)
Rigoberto Advincula, a renowned scientist at ORNL and professor of Chemical and Biomolecular Engineering at the University of Tennessee, has won the Netzsch North American Thermal Analysis Society Fellows Award for 2023.
![Exascale Computing Project](/sites/default/files/styles/list_page_thumbnail/public/2023-05/ECP.png?h=f9180d14&itok=jDHXXWP2)
Lawrence Livermore National Laboratory’s Lori Diachin will take over as director of the Department of Energy’s Exascale Computing Project on June 1, guiding the successful, multi-institutional high-performance computing effort through its final stages.
![Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences.](/sites/default/files/styles/list_page_thumbnail/public/2023-05/Dongarra%20thumbnail.png?h=560fc75e&itok=ByoO7Sli)
Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences in recognition of his distinguished and continuing achievements in original research.
![Robert Wagner](/sites/default/files/styles/list_page_thumbnail/public/2023-04/wagner.png?h=564c27f4&itok=cfPXByG6)
SAE International has awarded ORNL Buildings and Transportation Science Division Director Robert Wagner with the SAE Medal of Honor for his dedication and support of the organization’s mission of advancing mobility solutions.
![Andrew Lupini](/sites/default/files/styles/list_page_thumbnail/public/2023-04/lupini.png?h=181bc054&itok=c-ov-WoV)
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
![An AI-generated image representing atoms and artificial neural networks. Credit: Maxim Ziatdinov, ORNL](/sites/default/files/styles/list_page_thumbnail/public/2023-04/atoms3.jpg?h=ab622562&itok=dNMzrFw8)
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.