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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Alex Plotkowski
- Amit Shyam
- Kevin M Roccapriore
- Maxim A Ziatdinov
- James A Haynes
- Kyle Kelley
- Sumit Bahl
- Aaron Myers
- Alice Perrin
- Andres Marquez Rossy
- Anton Ievlev
- Arpan Biswas
- Eve Tsybina
- Gerd Duscher
- Gerry Knapp
- Jovid Rakhmonov
- Justin Cazares
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Matt Larson
- Neus Domingo Marimon
- Nicholas Richter
- Olga S Ovchinnikova
- Peeyush Nandwana
- Ryan Dehoff
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Sunyong Kwon
- Utkarsh Pratiush
- Viswadeep Lebakula
- Ying Yang

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 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.

Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.

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.

MAPSTER is a lightweight software package that automatically searches deployed laptops for geospatial data and complies metadata (GPS coordinates, file size, etc) at a central checkpoint.

In scientific research and industrial applications, selecting the most accurate model to describe a relationship between input parameters and target characteristics of experiments is crucial.