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Joon-Seok Kim Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Researchers at ORNL are using a machine-learning model to answer ‘what if’ questions stemming from major events that impact large numbers of people. By simulating an event, such as extreme weather, researchers can see how people might respond to adverse situations, and those outcomes can be used to improve emergency planning.

Quietly making noise: Measuring differential privacy could balance meaningful analytics and identity protection

To balance personal safety and research innovation, researchers at ORNL are employing a mathematical technique known as differential privacy to provide data privacy guarantees.

The AI for Energy Report provides a framework for using AI to accelerate decarbonization of the U.S. economy. Credit: Argonne National Laboratory

Groundbreaking report provides ambitious framework for accelerating clean energy deployment while minimizing risks and costs in the face of climate change.

The transportation and industrial sectors together account for more than 50% of the country’s carbon footprint. Defossilization could help reduce new emissions from these and other difficult-to-electrify segments of the U.S. economy.

Scientists at Oak Ridge National Laboratory and six other Department of Energy national laboratories have developed a United States-based perspective for achieving net-zero carbon emissions. 

Oak Ridge National Laboratory’s Sachin Nimbalkar, left, and Thomas Wenning guide energy-saving training activities for industry during Energy Bootcamps, hosted by DOE’s Better Plants program. Credit: ORNL, U.S. Dept. of Energy

Helping hundreds of manufacturing industries and water-power facilities across the U.S. increase energy efficiency requires a balance of teaching and training, blended with scientific guidance and technical expertise. It’s a formula for success that ORNL researchers have been providing to DOE’s Better Plants Program for more than a decade.

As a chemical engineer focusing on low-carbon energy sources like hydrogen, Cheekatamarla’s research at ORNL supports the deployment of clean energy technologies in buildings and industries. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Cheekatamarla is a researcher in the Multifunctional Equipment Integration group with previous experience in product deployment. He is researching alternative energy sources such as hydrogen for cookstoves and his research supports the decarbonization of building technologies. 

SOS26 attendees standing in front of the Kennedy Space Center on Merrit Island, Florida the night of their dinner reception provided by the conference sponsors. The keynote speaker was Rupak Biswas from NASA. Credit: Judy Potok/ORNL, U.S. Dept. of Energy

Held in Cocoa Beach, Florida from March 11 to 14, researchers across the computing and data spectra participated in sessions developed by staff members from the Department of Energy’s Oak Ridge National Laboratory, or ORNL, Sandia National Laboratories and the Swiss National Supercomputing Centre. 

Shift Thermal co-founders Mitchell Ishamel, left, and Levon Atoyan stand in front of one of the company’s ice thermal energy storage modules, which will be submitted to independent measurement and validation testing in May. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Shift Thermal, a member of Innovation Crossroads’ first cohort of fellows, is commercializing advanced ice thermal energy storage for HVAC, shifting the cooling process to be more sustainable, cost-effective and resilient. Shift Thermal wants to enable a lower-cost, more-efficient thermal energy storage method to provide long-duration resilient cooling when the electric grid is down. 

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Three ORNL intellectual property projects with industry partners have advanced in DOE's Office of Technology Transitions Making Advanced Technology Commercialization Harmonized, or Lab MATCH, prize, which encourages entrepreneurs to find actionable pathways that bring lab-developed intellectual property to market. 

ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy

In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.