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Moe Khaleel, left, associate laboratory director for national security sciences, and Maurice Singleton, chief executive officer of U2opia Technology, celebrate the partnership between Oak Ridge National Laboratory and U2opia Technology. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

U2opia Technology has licensed Situ and Heartbeat, a package of technologies from the Department of Energy’s Oak Ridge National Laboratory that offer a new method for advanced cybersecurity monitoring in real time. 

Wang, Cook and Uddin portraits side by side

Three transportation researchers at the Department of Energy’s Oak Ridge National Laboratory have been elevated to senior member grade of the Institute of Electrical and Electronics Engineers, or IEEE.

Researchers from ORNL and Western Michigan University prepare for a Chattanooga-based demonstration of a self-driving car using chip-enabled raised pavement markers for navigation.

ORNL has partnered with Western Michigan University to advance intelligent road infrastructure through the development of new chip-enabled raised pavement markers. These innovative markers transmit lane-keeping information to passing vehicles, enhancing safety and enabling smarter driving in all weather conditions.

ORNL researchers demonstrated the use of drones equipped with cameras and other sensors to check power lines at an EPB of Chattanooga training center for electrical line workers.

Researchers at ORNL recently demonstrated an automated drone-inspection technology at EPB of Chattanooga that will allow utilities to more quickly and easily check remote power lines for malfunctions, catching problems before outages occur.

Debjani Singh

Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.

Dmytro Bykov, left, and Hector Corzo participate in a value proposition development exercise as part Energy I-Corps

Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.

This photo is of a male scientist sitting at a desk working with materials, wearing protective glasses.

Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid. 

Image is of woman with dark hair crossing her arms and posting for a photo in front of a blue backdrop. She is wearing a black shirt with a tan cardigan.

Researcher Rocio Uria-Martinez was named one of four “Women with Hydro Vision” at this year’s HYDROVISION International 2024 conference taking place in Denver this week. Awarded by a committee of industry peers, the honor recognizes women who use their unique talents and vision to improve and advance the worldwide hydropower industry. 

This photo is of four men standing in front of a wall of monitors that are showing a tree looking image.

To better predict long-term flooding risk, scientists at the Department of Energy’s Oak Ridge National Laboratory developed a 3D modeling framework that captures the complex dynamics of water as it flows across the landscape. The framework seeks to provide valuable insights into which communities are most vulnerable as the climate changes, and was developed for a project that’s assessing climate risk and mitigation pathways for an urban area along the Southeast Texas coast.

Digital image of molecules would look like. There are 10 clusters of these shapes in grey, red and blue with a teal blue background

Oak Ridge National Laboratory scientists have developed a method leveraging artificial intelligence to accelerate the identification of environmentally friendly solvents for industrial carbon capture, biomass processing, rechargeable batteries and other applications.