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Researcher
- Singanallur Venkatakrishnan
- Vincent Paquit
- Amir K Ziabari
- Andrzej Nycz
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- Michael Kirka
- Obaid Rahman
- Oscar Martinez
- Philip Boudreaux
- T Oesch
- Xiaohan Yang

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.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

Due to a genes unique nucleotide sequences acquired through horizontal gene transfer, the gene has a transcriptional repressor activity and innate enzymatic role.

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

The invention provides a gene and methods for maintaining meiotic chromosomal architecture