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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Blane Fillingim
- Brian Post
- Costas Tsouris
- Kyle Kelley
- Lauren Heinrich
- Olga S Ovchinnikova
- Peeyush Nandwana
- Sudarsanam Babu
- Thomas Feldhausen
- Vincent Paquit
- Yousub Lee
- Akash Jag Prasad
- Alexander I Wiechert
- Anton Ievlev
- Arpan Biswas
- Calen Kimmell
- Canhai Lai
- Chris Tyler
- Clay Leach
- Debangshu Mukherjee
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- James Haley
- James Parks II
- Jaydeep Karandikar
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Md Inzamam Ul Haque
- Neus Domingo Marimon
- Radu Custelcean
- Ramanan Sankaran
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Utkarsh Pratiush
- Vimal Ramanuj
- Vladimir Orlyanchik
- Wenjun Ge
- Zackary Snow

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

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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.

Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.

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.

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.