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Researcher
- Andrzej Nycz
- Chris Masuo
- Peter Wang
- Alex Walters
- Brian Gibson
- Hongbin Sun
- Joshua Vaughan
- Luke Meyer
- Prashant Jain
- Udaya C Kalluri
- William Carter
- Akash Jag Prasad
- Alex Roschli
- Amit Shyam
- Brian Post
- Calen Kimmell
- Cameron Adkins
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Diana E Hun
- Gina Accawi
- Gordon Robertson
- Gurneesh Jatana
- Ian Greenquist
- Ilias Belharouak
- Isha Bhandari
- J.R. R Matheson
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- John Potter
- Liam White
- Mark M Root
- Michael Borish
- Nate See
- Nithin Panicker
- Philip Boudreaux
- Pradeep Ramuhalli
- Praveen Cheekatamarla
- Riley Wallace
- Ritin Mathews
- Ruhul Amin
- Singanallur Venkatakrishnan
- Vincent Paquit
- Vishaldeep Sharma
- Vittorio Badalassi
- Vladimir Orlyanchik
- Xiaohan Yang

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.

The invention presented here addresses key challenges associated with counterfeit refrigerants by ensuring safety, maintaining system performance, supporting environmental compliance, and mitigating health and legal risks.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

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 novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

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.

Recent advances in magnetic fusion (tokamak) technology have attracted billions of dollars of investments in startups from venture capitals and corporations to develop devices demonstrating net energy gain in a self-heated burning plasma, such as SPARC (under construction) and

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.