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Researcher
- Corson Cramer
- Steve Bullock
- Rama K Vasudevan
- Sergei V Kalinin
- Yongtao Liu
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- Lawrence {Larry} M Anovitz
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- Michael Kirka
- Nadim Hmeidat
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Peng Yang
- Sai Krishna Reddy Adapa
- Sai Mani Prudhvi Valleti
- Sana Elyas
- Stephen Jesse
- Steven Guzorek
- Sumner Harris
- Tomonori Saito
- Tony Beard
- 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 technologies provide additively manufactured thermal protection system.

This invention focuses on improving the ceramic yield of preceramic polymers by tuning the crosslinking process that occurs during vat photopolymerization (VP).

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.

Using all polymer formulations, the PIP densification is improved almost 70% over traditional preceramic polymers and PIP material leading to cost and times saving for densifying ceramic composites made from powder or fibers.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

A human-in-the-loop machine learning (hML) technology potentially enhances experimental workflows by integrating human expertise with AI automation.