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Researcher
- Amit K Naskar
- Kyle Kelley
- Rama K Vasudevan
- Yong Chae Lim
- Zhili Feng
- Jaswinder Sharma
- Jian Chen
- Logan Kearney
- Michael Toomey
- Nihal Kanbargi
- Rangasayee Kannan
- Sergei V Kalinin
- Stephen Jesse
- Wei Zhang
- Adam Stevens
- An-Ping Li
- Andrew Lupini
- Anton Ievlev
- Arit Das
- Benjamin L Doughty
- Bogdan Dryzhakov
- Brian Post
- Bryan Lim
- Christopher Bowland
- Dali Wang
- Edgar Lara-Curzio
- Felix L Paulauskas
- Frederic Vautard
- Holly Humphrey
- Hoyeon Jeon
- Huixin (anna) Jiang
- Jamieson Brechtl
- Jewook Park
- Jiheon Jun
- Kai Li
- Kashif Nawaz
- Kevin M Roccapriore
- Liam Collins
- Marti Checa Nualart
- Maxim A Ziatdinov
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Ondrej Dyck
- Peeyush Nandwana
- Priyanshi Agrawal
- Robert E Norris Jr
- Roger G Miller
- Ryan Dehoff
- Saban Hus
- Santanu Roy
- Sarah Graham
- Steven Randolph
- Sudarsanam Babu
- Sumit Gupta
- Tomas Grejtak
- Uvinduni Premadasa
- Vera Bocharova
- William Peter
- Yiyu Wang
- Yongtao Liu
- Yukinori Yamamoto

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

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

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.

The invention introduces a novel, customizable method to create, manipulate, and erase polar topological structures in ferroelectric materials using atomic force microscopy.

High coercive fields prevalent in wurtzite ferroelectrics present a significant challenge, as they hinder efficient polarization switching, which is essential for microelectronic applications.

Distortion in scanning tunneling microscope (STM) images is an unavoidable problem. This technology is an algorithm to identify and correct distorted wavefronts in atomic resolution STM images.

ORNL contributes to developing the concept of passive CO2 DAC by designing and testing a hybrid sorption system. This design aims to leverage the advantages of CO2 solubility and selectivity offered by materials with selective sorption of adsorbents.