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Researcher
- Peeyush Nandwana
- Sam Hollifield
- Amit Shyam
- Blane Fillingim
- Brian Post
- Chad Steed
- Junghoon Chae
- Lauren Heinrich
- Mingyan Li
- Rangasayee Kannan
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- Andres Marquez Rossy
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- Jian Chen
- Joel Asiamah
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- Joseph Olatt
- Kevin Spakes
- Kitty K Mccracken
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mark Provo II
- Mary A Adkisson
- Mengdawn Cheng
- Nance Ericson
- Oluwafemi Oyedeji
- Oscar Martinez
- Paula Cable-Dunlap
- Peter Wang
- Raymond Borges Hink
- Rob Root
- Ryan Dehoff
- Samudra Dasgupta
- Sanjita Wasti
- Srikanth Yoginath
- Steven J Zinkle
- Tim Graening Seibert
- T Oesch
- Tomas Grejtak
- Tyler Smith
- Varisara Tansakul
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- Xiang Chen
- Yanli Wang
- Yarom Polsky
- Ying Yang
- Yiyu Wang
- Yutai Kato
- Zhili Feng

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

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.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

This work seeks to alter the interface condition through thermal history modification, deposition energy density, and interface surface preparation to prevent interface cracking.

Additive manufacturing (AM) enables the incremental buildup of monolithic components with a variety of materials, and material deposition locations.