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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Mike Zach
- Sergei V Kalinin
- Sergiy Kalnaus
- Andrew F May
- Anton Ievlev
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- Beth L Armstrong
- Bogdan Dryzhakov
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- Debjani Pal
- Georgios Polyzos
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- James Klett
- Jaswinder Sharma
- Jeffrey Einkauf
- Jennifer M Pyles
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- Kevin M Roccapriore
- Kuntal De
- Laetitia H Delmau
- Liam Collins
- Luke Sadergaski
- Marti Checa Nualart
- Maxim A Ziatdinov
- Nancy Dudney
- Nedim Cinbiz
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Padhraic L Mulligan
- Sandra Davern
- Stephen Jesse
- Steven Randolph
- Tony Beard
- Yongtao Liu

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

We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

The co-processing of cathode and composite electrolyte for solid state polymer batteries has been developed. A traditional uncalendared cathode of e.g.

Spherical powders applied to nuclear targetry for isotope production will allow for enhanced heat transfer properties, tailored thermal conductivity and minimize time required for target fabrication and post processing.

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.

Biocompatible nanoparticles have been developed that can trap and retain therapeutic radionuclides and their byproducts at the cancer site. This is important to maximize the therapeutic effect of this treatment and minimize associated side effects.

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.