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Researcher
- Brian Post
- Adam M Guss
- Andrzej Nycz
- Peter Wang
- Chris Masuo
- Isabelle Snyder
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- Blane Fillingim
- Liangyu Qian
- Sudarsanam Babu
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- Viswadeep Lebakula
- Vlastimil Kunc
- William Carter
- William Peter
- Yang Liu
- Yarom Polsky
- Yasemin Kaygusuz
- Yukinori Yamamoto

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.

This manufacturing method uses multifunctional materials distributed volumetrically to generate a stiffness-based architecture, where continuous surfaces can be created from flat, rapidly produced geometries.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

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.

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

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