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Researcher
- Ilias Belharouak
- Peeyush Nandwana
- Ali Abouimrane
- Amit Shyam
- Blane Fillingim
- Brian Post
- Chad Steed
- Junghoon Chae
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- Sam Hollifield
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- Yousub Lee
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- Andres Marquez Rossy
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- Bruce A Pint
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- David L Wood III
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- Hongbin Sun
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- Junbin Choi
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- Luke Koch
- Lu Yu
- Mahim Mathur
- Marm Dixit
- Mary A Adkisson
- Oscar Martinez
- Peter Wang
- Pradeep Ramuhalli
- Ryan Dehoff
- Samudra Dasgupta
- Steven J Zinkle
- Tim Graening Seibert
- T Oesch
- Tomas Grejtak
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- 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.

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.

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.