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An Oak Ridge National Laboratory-developed advanced manufacturing technology, AMCM, was recently licensed by Orbital Composites and enables the rapid production of composite-based components, which could accelerate the decarbonization of vehicles
Oak Ridge National Laboratory researchers have conducted a comprehensive life cycle, cost and carbon emissions analysis on 3D-printed molds for precast concrete and determined the method is economically beneficial compared to conventional wood molds.
An advance in a topological insulator material — whose interior behaves like an electrical insulator but whose surface behaves like a conductor — could revolutionize the fields of next-generation electronics and quantum computing, according to scientists at ORNL.
A new report published by ORNL assessed how advanced manufacturing and materials, such as 3D printing and novel component coatings, could offer solutions to modernize the existing fleet and design new approaches to hydropower.
A study by Oak Ridge National Laboratory researchers has demonstrated how satellites could enable more efficient, secure quantum networks.
Critical Materials Institute researchers at Oak Ridge National Laboratory and Arizona State University studied the mineral monazite, an important source of rare-earth elements, to enhance methods of recovering critical materials for energy, defense and manufacturing applications.
ORNL researchers have identified a mechanism in a 3D-printed alloy – termed “load shuffling” — that could enable the design of better-performing lightweight materials for vehicles.
While Tsouris’ water research is diverse in scope, its fundamentals are based on basic science principles that remain largely unchanged, particularly in a mature field like chemical engineering.
Researchers demonstrated that an additively manufactured hot stamping die can withstand up to 25,000 usage cycles, proving that this technique is a viable solution for production.
In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly.