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Researcher
- Brian Post
- Andrzej Nycz
- Peter Wang
- Chris Masuo
- Blane Fillingim
- Peeyush Nandwana
- Srikanth Yoginath
- Sudarsanam Babu
- Thomas Feldhausen
- Ahmed Hassen
- Chad Steed
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- Joshua Vaughan
- Junghoon Chae
- Lauren Heinrich
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- Pratishtha Shukla
- Rangasayee Kannan
- Sudip Seal
- Travis Humble
- William Carter
- Yousub Lee
- Adam Stevens
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- Ali Passian
- Amit Shyam
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- Christopher Fancher
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- Debraj De
- Gautam Malviya Thakur
- Gordon Robertson
- Harper Jordan
- Isha Bhandari
- James Gaboardi
- Jay Reynolds
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- John Lindahl
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- Keju An
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- Loren L Funk
- Luke Chapman
- Mark Loguillo
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- Michael Borish
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- Pablo Moriano Salazar
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- Roger G Miller
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- Shannon M Mahurin
- Steven Guzorek
- Sydney Murray III
- Tao Hong
- Theodore Visscher
- Todd Thomas
- Tomas Grejtak
- Tomonori Saito
- Varisara Tansakul
- Vasilis Tzoganis
- Vasiliy Morozov
- Victor Fanelli
- Vladislav N Sedov
- Vlastimil Kunc
- William Peter
- Xiuling Nie
- Yacouba Diawara
- Yiyu Wang
- Yukinori Yamamoto
- Yun Liu

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

We presented a novel apparatus and method for laser beam position detection and pointing stabilization using analog position-sensitive diodes (PSDs).

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

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.

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.

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

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.