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Researcher
- Amit Shyam
- Beth L Armstrong
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Alex Plotkowski
- Jun Qu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Corson Cramer
- James A Haynes
- Kyle Kelley
- Meghan Lamm
- Peeyush Nandwana
- Rangasayee Kannan
- Ryan Dehoff
- Steve Bullock
- Sumit Bahl
- Tomas Grejtak
- Adam Stevens
- Alice Perrin
- Andres Marquez Rossy
- Anton Ievlev
- Arpan Biswas
- Ben Lamm
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- Bryan Lim
- Christopher Fancher
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- David J Mitchell
- Dean T Pierce
- Ethan Self
- Gabriel Veith
- Gerd Duscher
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- Gordon Robertson
- James Klett
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- Jeff Brookins
- Jordan Wright
- Jovid Rakhmonov
- Khryslyn G Araño
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marm Dixit
- Marti Checa Nualart
- Matthew S Chambers
- Michael Kirka
- Nancy Dudney
- Neus Domingo Marimon
- Nicholas Richter
- Olga S Ovchinnikova
- Peter Wang
- Roger G Miller
- Sai Mani Prudhvi Valleti
- Sarah Graham
- Sergiy Kalnaus
- Shajjad Chowdhury
- Stephen Jesse
- Sudarsanam Babu
- Sumner Harris
- Sunyong Kwon
- Tolga Aytug
- Trevor Aguirre
- Utkarsh Pratiush
- William Peter
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

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

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

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 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.

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.

Using all polymer formulations, the PIP densification is improved almost 70% over traditional preceramic polymers and PIP material leading to cost and times saving for densifying ceramic composites made from powder or fibers.

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