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- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Maxim A Ziatdinov
- Kyle Kelley
- Rob Moore II
- Anton Ievlev
- Arpan Biswas
- Gerd Duscher
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- Jamieson Brechtl
- Kai Li
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- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Matthew Brahlek
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Utkarsh Pratiush
- Xiaobing Liu

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 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.

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.

Moisture management accounts for over 40% of the energy used by buildings. As such development of energy efficient and resilient dehumidification technologies are critical to decarbonize the building energy sector.

Molecular Beam Epitaxy is a traditional technique for the synthesis of thin film materials used in the semiconducting and microelectronics industry. In its essence, the MBE technique heats crucibles filled with ultra-pure atomic elements under ultra high vacuum condition

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.

This invention presents technologies for characterizing physical properties of a sample's surface by combining image processing with machine learning techniques.