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Researcher
- Vivek Sujan
- Beth L Armstrong
- Adam Siekmann
- Jun Qu
- Omer Onar
- Subho Mukherjee
- Yong Chae Lim
- Zhili Feng
- Alex Plotkowski
- Amit Shyam
- Corson Cramer
- Erdem Asa
- Isabelle Snyder
- James A Haynes
- Jian Chen
- Meghan Lamm
- Rangasayee Kannan
- Shajjad Chowdhury
- Steve Bullock
- Sumit Bahl
- Tomas Grejtak
- Wei Zhang
- Adam Stevens
- Alice Perrin
- Ben Lamm
- Brian Post
- Bryan Lim
- Christopher Ledford
- Dali Wang
- David J Mitchell
- Ethan Self
- Gabriel Veith
- Gerry Knapp
- Hyeonsup Lim
- James Klett
- Jiheon Jun
- Jordan Wright
- Jovid Rakhmonov
- Khryslyn G Araño
- Marm Dixit
- Matthew S Chambers
- Michael Kirka
- Nancy Dudney
- Nicholas Richter
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Sergiy Kalnaus
- Sudarsanam Babu
- Sunyong Kwon
- Tolga Aytug
- Trevor Aguirre
- William Peter
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

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.

The growing demand for electric vehicles (EVs) has necessitated significant advancements in EV charging technologies to ensure efficient and reliable operation.

The growing demand for renewable energy sources has propelled the development of advanced power conversion systems, particularly in applications involving fuel cells.

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.

This invention presents a multiport converter (MPC) based power supply to charge the 12 V and 24 V auxiliary batteries in heavy duty (HD) fuel cell (FC) electric vehicle (EV) power train.

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.