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Researcher
- Vandana Rallabandi
- Subho Mukherjee
- Rama K Vasudevan
- Ryan Dehoff
- Gui-Jia Su
- Omer Onar
- Sergei V Kalinin
- Yongtao Liu
- Burak Ozpineci
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- Kyle Kelley
- Maxim A Ziatdinov
- Mostak Mohammad
- Olga S Ovchinnikova
- Shajjad Chowdhury
- Veda Prakash Galigekere
- Costas Tsouris
- Gurneesh Jatana
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- Todd Toops
- Vincent Paquit
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- Amir K Ziabari
- Amit Shyam
- An-Ping Li
- Andres Marquez Rossy
- Andrew Lupini
- Anton Ievlev
- Arpan Biswas
- Benjamin Manard
- Ben Lamm
- Beth L Armstrong
- Blane Fillingim
- Bogdan Dryzhakov
- Brian Fricke
- Brian Post
- Charles F Weber
- Christopher Ledford
- Christopher Rouleau
- Clay Leach
- David Nuttall
- Debangshu Mukherjee
- Dhruba Deka
- Diana E Hun
- Erdem Asa
- Gerd Duscher
- Gina Accawi
- Gs Jung
- Gyoung Gug Jang
- Haiying Chen
- Himel Barua
- Hongbin Sun
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- Ivan Vlassiouk
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- Jamieson Brechtl
- Jewook Park
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- Jong K Keum
- Jon Wilkins
- Kai Li
- Kyle Gluesenkamp
- Liam Collins
- Lingxiao Xue
- Mahshid Ahmadi-Kalinina
- Mark M Root
- Marti Checa Nualart
- Matt Vick
- Md Inzamam Ul Haque
- Meghan Lamm
- Melanie Moses-DeBusk Debusk
- Mina Yoon
- Neus Domingo Marimon
- Nickolay Lavrik
- Ondrej Dyck
- Patxi Fernandez-Zelaia
- Pedro Ribeiro
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- Vipin Kumar
- Vishaldeep Sharma
- Vivek Sujan
- Vlastimil Kunc
- William Peter
- William P Partridge Jr
- Xiang Lyu
- Xiaobing Liu
- Yan-Ru Lin
- Ying Yang
- Yukinori Yamamoto
- Zhiming Gao

Simurgh revolutionizes industrial CT imaging with AI, enhancing speed and accuracy in nondestructive testing for complex parts, reducing costs.

This invention introduces a system for microscopy called pan-sharpening, enabling the generation of images with both full-spatial and full-spectral resolution without needing to capture the entire dataset, significantly reducing data acquisition time.

An innovative low-cost system for in-situ monitoring of strain and temperature during directed energy deposition.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.

This technology introduces an advanced machine learning approach for enhancing chemical imaging by correlating data from two mass spectrometry imaging (MSI) techniques.

ORNL has developed a revolutionary system for wirelessly transferring power to electric vehicles and energy storage systems, enabling efficient, contactless charging.

A high-strength, heat-resistant Al-Ce-Ni alloy optimized for additive manufacturing in industrial applications.
Aromas play a significant role in the quality and safety of food, beverages, and even manufactured products. The ability to detect and interpret these aromas accurately can enhance product safety and consumer satisfaction.

Wireless power transfer technology has been increasingly adopted for charging batteries in various applications, notably in electric vehicles (EVs).