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ORNL and Caterpillar Inc. have entered into a cooperative research and development agreement, or CRADA, to investigate using methanol as an alternative fuel source for four-stroke internal combustion marine engines.
Four scientists affiliated with ORNL were named Battelle Distinguished Inventors during the lab’s annual Innovation Awards on Dec. 1 in recognition of being granted 14 or more United States patents.
ORNL is home to the world's fastest exascale supercomputer, Frontier, which was built in part to facilitate energy-efficient and scalable AI-based algorithms and simulations.
Used lithium-ion batteries from cell phones, laptops and a growing number of electric vehicles are piling up, but options for recycling them remain limited mostly to burning or chemically dissolving shredded batteries.
Researchers at ORNL have been leading a project to understand how a high-altitude electromagnetic pulse, or EMP, could threaten power plants.
Scientists at ORNL used their expertise in quantum biology, artificial intelligence and bioengineering to improve how CRISPR Cas9 genome editing tools work on organisms like microbes that can be modified to produce renewable fuels and chemicals.
ORNL has been selected to lead an Energy Earthshot Research Center, or EERC, focused on developing chemical processes that use sustainable methods instead of burning fossil fuels to radically reduce industrial greenhouse gas emissions to stem climate change and limit the crisis of a rapidly warming planet.
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
Wildfires are an ancient force shaping the environment, but they have grown in frequency, range and intensity in response to a changing climate. At ORNL, scientists are working on several fronts to better understand and predict these events and what they mean for the carbon cycle and biodiversity.
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.