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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
- Alex Roschli
- Andrew G Stack
- Anton Ievlev
- Arpan Biswas
- Erin Webb
- Evin Carter
- Gerd Duscher
- Jeremy Malmstead
- Juliane Weber
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- Liam Collins
- Mahshid Ahmadi-Kalinina
- Marti Checa Nualart
- Mengdawn Cheng
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Paula Cable-Dunlap
- Peng Yang
- Sai Krishna Reddy Adapa
- Sai Mani Prudhvi Valleti
- Soydan Ozcan
- Stephen Jesse
- Sumner Harris
- Tyler Smith
- Utkarsh Pratiush
- Xianhui Zhao

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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.

We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.

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.