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Researcher
- Andrzej Nycz
- Chris Masuo
- Peter Wang
- Alex Walters
- Ali Riza Ekti
- Brian Gibson
- Eddie Lopez Honorato
- Joshua Vaughan
- Luke Meyer
- Raymond Borges Hink
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- Akash Jag Prasad
- Amit Shyam
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- Calen Kimmell
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- Chelo Chavez
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- Emilio Piesciorovsky
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- Isabelle Snyder
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- Jeff Brookins
- Jesse Heineman
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- Joseph Olatt
- Keith Carver
- Kunal Mondal
- Mahim Mathur
- Matt Kurley III
- Mingyan Li
- Mostak Mohammad
- Nils Stenvig
- Omer Onar
- Oscar Martinez
- Ozgur Alaca
- Peter L Fuhr
- Richard Howard
- Riley Wallace
- Ritin Mathews
- Rodney D Hunt
- Sam Hollifield
- Thomas Butcher
- Vincent Paquit
- Vladimir Orlyanchik
- Xiaohan Yang
- Yarom Polsky

This technology can help to increase number of application areas of Wireless Power Transfer systems. It can be applied to consumer electronics, defense industry, automotive industry etc.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

A pressure burst feature has been designed and demonstrated for relieving potentially hazardous excess pressure within irradiation capsules used in the ORNL High Flux Isotope Reactor (HFIR).

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.

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

Sintering additives to improve densification and microstructure control of UN provides a facile approach to producing high quality nuclear fuels.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Creating a framework (method) for bots (agents) to autonomously, in real time, dynamically divide and execute a complex manufacturing (or any suitable) task in a collaborative, parallel-sequential way without required human interaction.

Materials produced via additive manufacturing, or 3D printing, can experience significant residual stress, distortion and cracking, negatively impacting the manufacturing process.

In additive printing that utilizes multiple robotic agents to build, each agent, or “arm”, is currently limited to a prescribed path determined by the user.