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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Alexey Serov
- Jaswinder Sharma
- Kyle Kelley
- Xiang Lyu
- Alex Roschli
- Amit K Naskar
- Anton Ievlev
- Arpan Biswas
- Beth L Armstrong
- Erin Webb
- Evin Carter
- Gabriel Veith
- Georgios Polyzos
- Gerd Duscher
- Holly Humphrey
- James Szybist
- Jeremy Malmstead
- Jonathan Willocks
- Junbin Choi
- Khryslyn G Araño
- Kitty K Mccracken
- Liam Collins
- Logan Kearney
- Mahshid Ahmadi-Kalinina
- Marm Dixit
- Marti Checa Nualart
- Meghan Lamm
- Mengdawn Cheng
- Michael Toomey
- Michelle Lehmann
- Neus Domingo Marimon
- Nihal Kanbargi
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Paula Cable-Dunlap
- Ritu Sahore
- Sai Mani Prudhvi Valleti
- Soydan Ozcan
- Stephen Jesse
- Sumner Harris
- Todd Toops
- Tyler Smith
- Utkarsh Pratiush
- Xianhui Zhao

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

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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.

We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.