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Researcher
- Adam M Guss
- Amit K Naskar
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- Andrzej Nycz
- Biruk A Feyissa
- Carrie Eckert
- Jaswinder Sharma
- Josh Michener
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- Arit Das
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- Kyle Davis
- Liangyu Qian
- Marie Romedenne
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- Priyanshi Agrawal
- Robert E Norris Jr
- Santanu Roy
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- Sumit Gupta
- Uvinduni Premadasa
- Vera Bocharova
- Vincent Paquit
- Yang Liu
- Yasemin Kaygusuz
- Yong Chae Lim
- Zhili Feng

Efficient thermal management in polymers is essential for developing lightweight, high-strength materials with multifunctional capabilities.

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.

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.

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.

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.

A novel method that prevents detachment of an optical fiber from a metal/alloy tube and allows strain measurement up to higher temperatures, about 800 C has been developed. Standard commercial adhesives typically only survive up to about 400 C.

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.

Test facilities to evaluate materials compatibility in hydrogen are abundant for high pressure and low temperature (<100C).

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

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.