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Researcher
- Andrzej Nycz
- Chris Masuo
- Peter Wang
- Alex Walters
- Venkatakrishnan Singanallur Vaidyanathan
- Vincent Paquit
- Amir K Ziabari
- Brian Gibson
- Diana E Hun
- Joshua Vaughan
- Luke Meyer
- Philip Bingham
- Philip Boudreaux
- Ryan Dehoff
- Soydan Ozcan
- Stephen M Killough
- Udaya C Kalluri
- William Carter
- Xianhui Zhao
- Akash Jag Prasad
- Alex Roschli
- Amit Shyam
- Brian Post
- Bryan Maldonado Puente
- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Corey Cooke
- Dali Wang
- Erin Webb
- Evin Carter
- Gina Accawi
- Gordon Robertson
- Gurneesh Jatana
- Halil Tekinalp
- J.R. R Matheson
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jeremy Malmstead
- Jesse Heineman
- Jian Chen
- John Holliman II
- John Potter
- Kitty K Mccracken
- Mark M Root
- Mengdawn Cheng
- Michael Kirka
- Nolan Hayes
- Obaid Rahman
- Oluwafemi Oyedeji
- Paula Cable-Dunlap
- Riley Wallace
- Ritin Mathews
- Ryan Kerekes
- Sally Ghanem
- Sanjita Wasti
- Tyler Smith
- Vladimir Orlyanchik
- Wei Zhang
- Xiaohan Yang
- Zhili Feng

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

How fast is a vehicle traveling? For different reasons, this basic question is of interest to other motorists, insurance companies, law enforcement, traffic planners, and security personnel. Solutions to this measurement problem suffer from a number of constraints.

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

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.

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.