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Researcher
- Ilias Belharouak
- Alex Plotkowski
- Amit Shyam
- Anees Alnajjar
- Srikanth Yoginath
- Yong Chae Lim
- Zhili Feng
- Ali Abouimrane
- Georgios Polyzos
- James A Haynes
- James J Nutaro
- Jaswinder Sharma
- Jian Chen
- Nageswara Rao
- Peeyush Nandwana
- Pratishtha Shukla
- Rangasayee Kannan
- Ruhul Amin
- Ryan Dehoff
- Sergiy Kalnaus
- Sudip Seal
- Sumit Bahl
- Wei Zhang
- Adam Stevens
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Beth L Armstrong
- Brian Post
- Bryan Lim
- Craig A Bridges
- Dali Wang
- David L Wood III
- Femi Omitaomu
- Gerry Knapp
- Haowen Xu
- Harper Jordan
- Hongbin Sun
- Jiheon Jun
- Joel Asiamah
- Joel Dawson
- Jovid Rakhmonov
- Junbin Choi
- Lu Yu
- Mariam Kiran
- Marm Dixit
- Nance Ericson
- Nancy Dudney
- Nicholas Richter
- Pradeep Ramuhalli
- Priyanshi Agrawal
- Roger G Miller
- Sarah Graham
- Sheng Dai
- Sudarsanam Babu
- Sunyong Kwon
- Tomas Grejtak
- Varisara Tansakul
- William Peter
- Yaocai Bai
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto
- Zhijia Du

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.

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

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.

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

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.

The ORNL invention addresses the challenge of poor mechanical properties of dry processed electrodes, improves their electrical properties, while improving their electrochemical performance.

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.

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