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Researcher
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
- Kevin M Roccapriore
- Lawrence {Larry} M Anovitz
- Maxim A Ziatdinov
- Kyle Kelley
- Andrew G Stack
- Anton Ievlev
- Arpan Biswas
- Costas Tsouris
- Gerd Duscher
- Gs Jung
- Gyoung Gug Jang
- Jong K Keum
- Juliane Weber
- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Mina Yoon
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peng Yang
- Radu Custelcean
- Sai Krishna Reddy Adapa
- Sai Mani Prudhvi Valleti
- Stephen Jesse
- Sumner Harris
- Utkarsh Pratiush

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

CO2 capture by mineral looping, either using calcium or magnesium precursors requires that the materials be calcined after CO2 is captured from the atmosphere. This separates the CO2 for later sequestration and returned the starting material to its original state.

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.

Mineral looping is a promising method for direct air capture of CO2. However, reduction of sorbent reactivity after each loop is likely to be significant problems for mineral looping by MgO.

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.

A novel molecular sorbent system for low energy CO2 regeneration is developed by employing CO2-responsive molecules and salt in aqueous media where a precipitating CO2--salt fractal network is formed, resulting in solid-phase formation and sedimentation.

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.