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Researcher
- Peeyush Nandwana
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Adam Willoughby
- Amit Shyam
- Blane Fillingim
- Brian Post
- Bruce A Pint
- Kyle Kelley
- Lauren Heinrich
- Rangasayee Kannan
- Rishi Pillai
- Sudarsanam Babu
- Thomas Feldhausen
- Yousub Lee
- Alex Plotkowski
- Andres Marquez Rossy
- Anton Ievlev
- Arpan Biswas
- Brandon Johnston
- Bryan Lim
- Charles Hawkins
- Christopher Fancher
- Gerd Duscher
- Gordon Robertson
- Jay Reynolds
- Jeff Brookins
- Jiheon Jun
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marie Romedenne
- Marti Checa Nualart
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peter Wang
- Priyanshi Agrawal
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Steven J Zinkle
- Sumner Harris
- Tim Graening Seibert
- Tomas Grejtak
- Utkarsh Pratiush
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yanli Wang
- Ying Yang
- Yiyu Wang
- Yong Chae Lim
- Yutai Kato
- Zhili Feng

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 lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

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.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

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).

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.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.