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Media Contacts
In a game-changing study, ORNL scientists developed a deep learning model — a type of artificial intelligence that mimics human brain function — to analyze high-speed videos of plasma plumes during a process called pulsed laser deposition.
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.
Researchers at ORNL have demonstrated that small molecular tweaks to surfaces can improve absorption technology for direct air capture of carbon dioxide. The team added a charged polymer layer to an amino acid solution, and then, through spectroscopy and simulation, found that the charged layer can hold amino acids at its surface.
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.
An Oak Ridge National Laboratory team revealed how chemical species form in a highly reactive molten salt mixture of aluminum chloride and potassium chloride by unraveling vibrational signatures and observing ion exchanges.
Oak Ridge National Laboratory scientists ingeniously created a sustainable, soft material by combining rubber with woody reinforcements and incorporating “smart” linkages between the components that unlock on demand.
An international team using neutrons set the first benchmark (one nanosecond) for a polymer-electrolyte and lithium-salt mixture. Findings could produce safer, more powerful lithium batteries.
A team of researchers at ORNL demonstrated that a light-duty passenger electric vehicle can be wirelessly charged at 100-kW with 96% efficiency using polyphase electromagnetic coupling coils with rotating magnetic fields.
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.