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Researcher
- Ryan Dehoff
- Kyle Kelley
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- Ahmed Hassen
- Akash Jag Prasad
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- Patxi Fernandez-Zelaia
- Peeyush Nandwana
- Philip Bingham
- Rangasayee Kannan
- Roger G Miller
- Sarah Graham
- Singanallur Venkatakrishnan
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- Sudarsanam Babu
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- Vlastimil Kunc
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- Yongtao Liu
- Yukinori Yamamoto
- Zackary Snow

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.

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

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.

High strength, oxidation resistant refractory alloys are difficult to fabricate for commercial use in extreme environments.

In manufacturing parts for industry using traditional molds and dies, about 70 percent to 80 percent of the time it takes to create a part is a result of a relatively slow cooling process.

This technology combines 3D printing and compression molding to produce high-strength, low-porosity composite articles.

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

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.