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Researcher
- Ilias Belharouak
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Alexey Serov
- Ali Abouimrane
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- Xiang Lyu
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- Beth L Armstrong
- David L Wood III
- Gabriel Veith
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- Gerd Duscher
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- Hongbin Sun
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- Mahshid Ahmadi-Kalinina
- Mark Provo II
- Marti Checa Nualart
- Meghan Lamm
- Michael Toomey
- Michelle Lehmann
- Nance Ericson
- Neus Domingo Marimon
- Nihal Kanbargi
- Olga S Ovchinnikova
- Paul Groth
- Pradeep Ramuhalli
- Ritu Sahore
- Rob Root
- Sai Mani Prudhvi Valleti
- Sam Hollifield
- Stephen Jesse
- Sumner Harris
- Todd Toops
- Utkarsh Pratiush
- Yaocai Bai
- Zhijia Du

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

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

An electrochemical cell has been specifically designed to maximize CO2 release from the seawater while also not changing the pH of the seawater before returning to the sea.

The ORNL invention addresses the challenge of poor mechanical properties of dry processed electrodes, improves their electrical properties, while improving their electrochemical performance.

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

Hydrogen is in great demand, but production relies heavily on hydrocarbons utilization. This process contributes greenhouse gases release into the atmosphere.

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.

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

The scanning transmission electron microscope (STEM) provides unprecedented spatial resolution and is critical for many applications, primarily for imaging matter at the atomic and nanoscales and obtaining spectroscopic information at similar length scales.