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Researcher
- Adam M Guss
- Josh Michener
- Liangyu Qian
- Venkatakrishnan Singanallur Vaidyanathan
- Vincent Paquit
- Amir K Ziabari
- Andrzej Nycz
- Biruk A Feyissa
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- Kuntal De
- Philip Bingham
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- Ryan Dehoff
- Serena Chen
- Stephen M Killough
- Udaya C Kalluri
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- Xiaohan Yang
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- Alex Walters
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- Chris Masuo
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- Gurneesh Jatana
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- Jerry Parks
- Joanna Tannous
- Junghyun Bae
- Kyle Davis
- Mark M Root
- Michael Kirka
- Nandhini Ashok
- Nolan Hayes
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- Paul Abraham
- Peter Wang
- Ryan Kerekes
- Sally Ghanem
- Yang Liu
- Yasemin Kaygusuz

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

Mechanism-Based Trait Inference in Plants Using Multiplex Networks, AI Agents, and Translation Tools
This system enables the modular design and optimization of complex plant traits by organizing genes and regulatory mechanisms into interpretable clades.

Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

Enzymes for synthesis of sequenced oligoamide triads and tetrads that can be polymerized into sequenced copolyamides.
Contact
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

We tested 48 diverse homologs of SfaB and identified several enzyme variants that were more active than SfaB at synthesizing the nylon-6,6 monomer.

By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.

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

The lattice collimator places a grid of shielding material in front of a radiation detector to reduce the effect of background from surrounding materials and to enhance the RPM sensitivity to point sources rather than distributed sources that are commonly associated with Natur

We present a comprehensive muti-technique approach for systematic investigation of enzymes generated by wastewater Comamonas species with hitherto unknown functionality to wards the depolymerization of plastics into bioaccessible products for bacterial metabolism.

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