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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Kyle Kelley
- Maxim A Ziatdinov
- Olga S Ovchinnikova
- Singanallur Venkatakrishnan
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- Kashif Nawaz
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- Vincent Paquit
- An-Ping Li
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- Anton Ievlev
- Arpan Biswas
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- Costas Tsouris
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- Gerd Duscher
- Gina Accawi
- Gs Jung
- Gurneesh Jatana
- Gyoung Gug Jang
- Hoyeon Jeon
- Huixin (anna) Jiang
- Ilia N Ivanov
- Ivan Vlassiouk
- Jamieson Brechtl
- Jewook Park
- Jiheon Jun
- Jong K Keum
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marie Romedenne
- Mark M Root
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Michael Kirka
- Mina Yoon
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- Nolan Hayes
- Obaid Rahman
- Ondrej Dyck
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- Saban Hus
- Sai Mani Prudhvi Valleti
- Sally Ghanem
- Steven Randolph
- Sumner Harris
- Utkarsh Pratiush
- Yong Chae Lim
- Zhili Feng
- Zhiming Gao

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

Dual-GP addresses limitations in traditional GPBO-driven autonomous experimentation by incorporating an additional surrogate observer and allowing human oversight, this technique improves optimization efficiency via data quality assessment and adaptability to unanticipated exp

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

A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

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

Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).

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

Scanning transmission electron microscopes are useful for a variety of applications. Atomic defects in materials are critical for areas such as quantum photonics, magnetic storage, and catalysis.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.