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In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.
Silicon nitride fiber is a critical material mainly used in the aerospace industry but has many applications. This fiber is prized for its properties, as it is transparent to electromagnetic radiation but allows signals to go through it.
This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.
This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.
The described concept provides a predictive technology solution to increase the safety of platooning vehicles.
Through new chemistry, materials, and processes, ORNL researchers are developing a highly compact and energy efficient carbon capture technology, which can enable wide-spread implementation in a cost effective manner.