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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Andrzej Nycz
- Anees Alnajjar
- Chris Masuo
- Kyle Kelley
- Luke Meyer
- William Carter
- Alexander I Kolesnikov
- Alexei P Sokolov
- Alex Walters
- Anton Ievlev
- Arpan Biswas
- Bekki Mills
- Bruce Hannan
- Craig A Bridges
- Dave Willis
- Gerd Duscher
- John Wenzel
- Joshua Vaughan
- Keju An
- Liam Collins
- Loren L Funk
- Luke Chapman
- Mahshid Ahmadi-Kalinina
- Mariam Kiran
- Mark Loguillo
- Marti Checa Nualart
- Matthew B Stone
- Nageswara Rao
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peter Wang
- Polad Shikhaliev
- Sai Mani Prudhvi Valleti
- Shannon M Mahurin
- Sheng Dai
- Stephen Jesse
- Sumner Harris
- Sydney Murray III
- Tao Hong
- Theodore Visscher
- Tomonori Saito
- Utkarsh Pratiush
- Vasilis Tzoganis
- Vasiliy Morozov
- Victor Fanelli
- Vladislav N Sedov
- Yacouba Diawara
- Yun Liu

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

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

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

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

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

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.

Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.

Neutron beams are used around the world to study materials for various purposes.

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