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Researcher
- Amit K Naskar
- Srikanth Yoginath
- Chad Steed
- James J Nutaro
- Jaswinder Sharma
- Junghoon Chae
- Logan Kearney
- Michael Toomey
- Nihal Kanbargi
- Pratishtha Shukla
- Sudip Seal
- Travis Humble
- Ali Passian
- Annetta Burger
- Arit Das
- Benjamin L Doughty
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Christopher Bowland
- Dali Wang
- Debraj De
- Edgar Lara-Curzio
- Felix L Paulauskas
- Frederic Vautard
- Gautam Malviya Thakur
- Harper Jordan
- Holly Humphrey
- James Gaboardi
- Jesse McGaha
- Jian Chen
- Joel Asiamah
- Joel Dawson
- Kevin Sparks
- Liz McBride
- Nance Ericson
- Pablo Moriano Salazar
- Peeyush Nandwana
- Rangasayee Kannan
- Robert E Norris Jr
- Samudra Dasgupta
- Santanu Roy
- Sumit Gupta
- Todd Thomas
- Tomas Grejtak
- Uvinduni Premadasa
- Varisara Tansakul
- Vera Bocharova
- Wei Zhang
- Xiuling Nie
- Yiyu Wang
- Zhili Feng

Efficient thermal management in polymers is essential for developing lightweight, high-strength materials with multifunctional capabilities.

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

The disclosure is directed to optimized fiber geometries for use in carbon fiber reinforced polymers with increased compressive strength per unit cost. The disclosed fiber geometries reduce the material processing costs as well as increase the compressive strength.

A novel and cost-effective process for the activation of carbon fibers was established.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.

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

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

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.