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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Kyle Kelley
- Alexander I Kolesnikov
- Anton Ievlev
- Arpan Biswas
- Bekki Mills
- Diana E Hun
- Easwaran Krishnan
- Gerd Duscher
- James Manley
- Jamieson Brechtl
- Joe Rendall
- John Wenzel
- Karen Cortes Guzman
- Kashif Nawaz
- Kuma Sumathipala
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Mark Loguillo
- Marti Checa Nualart
- Matthew B Stone
- Mengjia Tang
- Muneeshwaran Murugan
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Tomonori Saito
- Utkarsh Pratiush
- Victor Fanelli
- Zoriana Demchuk

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

Estimates based on the U.S. Department of Energy (DOE) test procedure for water heaters indicate that the equivalent of 350 billion kWh worth of hot water is discarded annually through drains, and a large portion of this energy is, in fact, recoverable.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

Neutron scattering experiments cover a large temperature range in which experimenters want to test their samples.

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.

The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.

Neutron beams are used around the world to study materials for various purposes.

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.