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Oak Ridge National Laboratory researchers designed and field-tested an algorithm that could help homeowners maintain comfortable temperatures year-round while minimizing utility costs.
Oak Ridge National Laboratory researchers combined additive manufacturing with conventional compression molding to produce high-performance thermoplastic composites reinforced with short carbon fibers.
A team of Oak Ridge National Laboratory researchers demonstrated that an additively manufactured hot stamping die – a tool used to create car body components – cooled faster than those produced by conventional manufacturing methods.
Oak Ridge National Laboratory researchers have demonstrated that a new class of superalloys made of cobalt and nickel remains crack-free and defect-resistant in extreme heat, making them conducive for use in metal-based 3D printing applications.
The ExOne Company, the global leader in industrial sand and metal 3D printers using binder jetting technology, announced it has reached a commercial license agreement with Oak Ridge National Laboratory to 3D print parts in aluminum-infiltrated boron carbide.
The Society of Manufacturing Engineers, known as SME, has named William Peter, director of Oak Ridge National Laboratory’s Manufacturing Demonstration Facility in the Energy and Environmental Sciences Directorate, among its 2020 College of SME Fellows.
Oak Ridge National Laboratory researchers have developed artificial intelligence software for powder bed 3D printers that assesses the quality of parts in real time, without the need for expensive characterization equipment.
ORNL has licensed two additive manufacturing-related technologies that aim to streamline and ramp up production processes to Knoxville-based Magnum Venus Products, Inc., a global manufacturer of fluid movement and product solutions for industrial applications in composites and adhesives.
A multi-institutional research team found that changing environmental conditions are affecting forests around the globe, leading to increasing tree death and uncertainty about the ability of forests to recover.