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Researcher
- Andrzej Nycz
- Radu Custelcean
- Chris Masuo
- Peeyush Nandwana
- Costas Tsouris
- Peter Wang
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- Gyoung Gug Jang
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- Laetitia H Delmau
- Luke Sadergaski
- Md Faizul Islam
- Mina Yoon
- Parans Paranthaman
- Riley Wallace
- Ritin Mathews
- Ryan Dehoff
- Santanu Roy
- Saurabh Prakash Pethe
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- Subhamay Pramanik
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- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Xiaohan Yang
- Yanli Wang
- Ying Yang
- Yingzhong Ma
- Yiyu Wang
- Yutai Kato

The technologies provides for regeneration of anion-exchange resin.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

Ruthenium is recovered from used nuclear fuel in an oxidizing environment by depositing the volatile RuO4 species onto a polymeric substrate.

This invention describes a new class of amphiphilic chelators (extractants) that can selectively separate large, light rare earth elements from heavy, small rare earth elements in solvent extraction schemes.

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.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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 increasing demand for high-purity lanthanides, essential for advanced technologies such as electronics, renewable energy, and medical applications, presents a significant challenge due to their similar chemical properties.

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.

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.