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Researcher
- Alex Plotkowski
- Amit Shyam
- Anees Alnajjar
- Srikanth Yoginath
- Chad Steed
- James A Haynes
- James J Nutaro
- Junghoon Chae
- Nageswara Rao
- Peeyush Nandwana
- Pratishtha Shukla
- Sergiy Kalnaus
- Sudip Seal
- Sumit Bahl
- Travis Humble
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Annetta Burger
- Beth L Armstrong
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Craig A Bridges
- Debraj De
- Femi Omitaomu
- Gautam Malviya Thakur
- Georgios Polyzos
- Gerry Knapp
- Haowen Xu
- Harper Jordan
- Hongbin Sun
- James Gaboardi
- Jaswinder Sharma
- Jesse McGaha
- Joel Asiamah
- Joel Dawson
- Jovid Rakhmonov
- Kevin Sparks
- Liz McBride
- Mariam Kiran
- Nance Ericson
- Nancy Dudney
- Nate See
- Nicholas Richter
- Pablo Moriano Salazar
- Prashant Jain
- Rangasayee Kannan
- Ryan Dehoff
- Samudra Dasgupta
- Sheng Dai
- Sunyong Kwon
- Thien D. Nguyen
- Todd Thomas
- Tomas Grejtak
- Varisara Tansakul
- Xiuling Nie
- Ying Yang
- Yiyu Wang

In nuclear and industrial facilities, fine particles, including radioactive residues—can accumulate on the interior surfaces of ventilation ducts and equipment, posing serious safety and operational risks.

The eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

We developed and incorporated two innovative mPET/Cu and mPET/Al foils as current collectors in LIBs to enhance cell energy density under XFC conditions.

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.

A novel approach is presented herein to improve time to onset of natural convection stemming from fuel element porosity during a failure mode of a nuclear reactor.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.