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The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.
A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.
The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.
QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.
This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.
Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.
The first wall and blanket of a fusion energy reactor must maintain structural integrity and performance over long operational periods under neutron irradiation and minimize long-lived radioactive waste.
A high-strength, heat-resistant Al-Ce-Ni alloy optimized for additive manufacturing in industrial applications.
High-performance cerium-based permanent magnet materials have been developed to reduce reliance on scarce rare-earth elements.