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Researcher
- Ilias Belharouak
- Peeyush Nandwana
- Ali Abouimrane
- Amit Shyam
- Andrzej Nycz
- Blane Fillingim
- Brian Post
- Chris Masuo
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- Ryan Dehoff
- Steven J Zinkle
- Theodore Visscher
- Tim Graening Seibert
- Tomas Grejtak
- Vladislav N Sedov
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yacouba Diawara
- Yanli Wang
- Yaocai Bai
- Ying Yang
- Yiyu Wang
- Yutai Kato
- Zhijia Du

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.

ORNL has developed a large area thermal neutron detector based on 6LiF/ZnS(Ag) scintillator coupled with wavelength shifting fibers. The detector uses resistive charge divider-based position encoding.

The ORNL invention addresses the challenge of poor mechanical properties of dry processed electrodes, improves their electrical properties, while improving their electrochemical performance.

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.

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.