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Researcher
- Ryan Dehoff
- Singanallur Venkatakrishnan
- Yong Chae Lim
- Amir K Ziabari
- Philip Bingham
- Rangasayee Kannan
- Vincent Paquit
- Adam Stevens
- Brian Post
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- Gurneesh Jatana
- Ilenne Del Valle Kessra
- Jerry Parks
- Jiheon Jun
- Mark M Root
- Michael Kirka
- Obaid Rahman
- Paul Abraham
- Peeyush Nandwana
- Philip Boudreaux
- Priyanshi Agrawal
- Roger G Miller
- Sarah Graham
- Sudarsanam Babu
- Tomas Grejtak
- Vilmos Kertesz
- William Peter
- Xiaohan Yang
- Yang Liu
- Yiyu Wang
- Yukinori Yamamoto
- Zhili Feng

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

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

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.

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.

Direct-acting antivirals are needed to combat coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).

There is a critical need for new antiviral drugs for treating infections of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2).