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Researcher
- Radu Custelcean
- Costas Tsouris
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- Bruce Moyer
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- Md Faizul Islam
- Mina Yoon
- Nance Ericson
- Pablo Moriano Salazar
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- Peeyush Nandwana
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- Polad Shikhaliev
- Rangasayee Kannan
- Santanu Roy
- Saurabh Prakash Pethe
- Shannon M Mahurin
- Subhamay Pramanik
- Sydney Murray III
- Tao Hong
- Theodore Visscher
- Tomas Grejtak
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- Uvinduni Premadasa
- Varisara Tansakul
- Vasilis Tzoganis
- Vasiliy Morozov
- Vera Bocharova
- Victor Fanelli
- Vladislav N Sedov
- Yacouba Diawara
- Yingzhong Ma
- Yiyu Wang
- Yun Liu

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

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.

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.

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.

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.

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.