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Researcher
- Kyle Kelley
- Rama K Vasudevan
- Adam Willoughby
- Rishi Pillai
- Sergei V Kalinin
- Vincent Paquit
- Akash Jag Prasad
- Anton Ievlev
- Bogdan Dryzhakov
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- Costas Tsouris
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- Jiheon Jun
- Kevin M Roccapriore
- Liam Collins
- Marie Romedenne
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- Neus Domingo Marimon
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- Priyanshi Agrawal
- Ryan Dehoff
- Stephen Jesse
- Steven Randolph
- Vladimir Orlyanchik
- Yong Chae Lim
- Yongtao Liu
- Zackary Snow
- Zhili Feng

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

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

Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

Sensing of additive manufacturing processes promises to facilitate detailed quality inspection at scales that have seldom been seen in traditional manufacturing processes.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

The technology provides a transformational approach to digitally manufacture structural alloys with co- optimized strength and environmental resistance

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

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.