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Researcher
- Amit K Naskar
- Sam Hollifield
- Singanallur Venkatakrishnan
- Amir K Ziabari
- Chad Steed
- Jaswinder Sharma
- Junghoon Chae
- Logan Kearney
- Michael Toomey
- Mingyan Li
- Nihal Kanbargi
- Philip Bingham
- Ryan Dehoff
- Travis Humble
- Vincent Paquit
- Aaron Werth
- Ali Passian
- Arit Das
- Benjamin L Doughty
- Brian Weber
- Christopher Bowland
- Diana E Hun
- Edgar Lara-Curzio
- Emilio Piesciorovsky
- Felix L Paulauskas
- Frederic Vautard
- Gary Hahn
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Holly Humphrey
- Isaac Sikkema
- Jason Jarnagin
- Joel Asiamah
- Joel Dawson
- Joseph Olatt
- Kevin Spakes
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mark M Root
- Mark Provo II
- Mary A Adkisson
- Michael Kirka
- Nance Ericson
- Obaid Rahman
- Oscar Martinez
- Philip Boudreaux
- Raymond Borges Hink
- Robert E Norris Jr
- Rob Root
- Samudra Dasgupta
- Santanu Roy
- Srikanth Yoginath
- Sumit Gupta
- T Oesch
- Uvinduni Premadasa
- Varisara Tansakul
- Vera Bocharova
- Yarom Polsky

ORNL researchers have developed a deep learning-based approach to rapidly perform high-quality reconstructions from sparse X-ray computed tomography measurements.

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.

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

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.

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.

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.