Filter Results
Related Organization
- Computing and Computational Sciences Directorate (38)
- Energy Science and Technology Directorate (223)
- Fusion and Fission Energy and Science Directorate (24)
- Information Technology Services Directorate (3)
- Isotope Science and Enrichment Directorate (7)
- National Security Sciences Directorate (20)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate (135)
- User Facilities
(27)
- (-) Biological and Environmental Systems Science Directorate (26)
Researcher
- Adam M Guss
- Ali Passian
- Josh Michener
- Joseph Chapman
- Kyle Kelley
- Liangyu Qian
- Nicholas Peters
- Rama K Vasudevan
- Andrzej Nycz
- Biruk A Feyissa
- Carrie Eckert
- Daniel Jacobson
- Hsuan-Hao Lu
- Isaiah Dishner
- Jeff Foster
- John F Cahill
- Joseph Lukens
- Kuntal De
- Muneer Alshowkan
- Serena Chen
- Sergei V Kalinin
- Udaya C Kalluri
- Vilmos Kertesz
- Xiaohan Yang
- Alex Roschli
- Alex Walters
- Anees Alnajjar
- Anton Ievlev
- Austin Carroll
- Bogdan Dryzhakov
- Brian Sanders
- Brian Williams
- Chris Masuo
- Claire Marvinney
- Clay Leach
- Debjani Pal
- Erin Webb
- Evin Carter
- Gerald Tuskan
- Harper Jordan
- Ilenne Del Valle Kessra
- Jay D Huenemann
- Jeremy Malmstead
- Jerry Parks
- Joanna Tannous
- Joel Asiamah
- Joel Dawson
- Kevin M Roccapriore
- Kitty K Mccracken
- Kyle Davis
- Liam Collins
- Mariam Kiran
- Marti Checa Nualart
- Maxim A Ziatdinov
- Mengdawn Cheng
- Nance Ericson
- Nandhini Ashok
- Neus Domingo Marimon
- Olga S Ovchinnikova
- Oluwafemi Oyedeji
- Paul Abraham
- Paula Cable-Dunlap
- Soydan Ozcan
- Srikanth Yoginath
- Stephen Jesse
- Steven Randolph
- Tyler Smith
- Varisara Tansakul
- Vincent Paquit
- Xianhui Zhao
- Yang Liu
- Yasemin Kaygusuz
- Yongtao Liu

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.

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

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.

Technologies directed to polarization agnostic continuous variable quantum key distribution are described.
Contact:
To learn more about this technology, email partnerships@ornl.gov or call 865-574-1051.

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.

The development of quantum networking requires architectures capable of dynamically reconfigurable entanglement distribution to meet diverse user needs and ensure tolerance against transmission disruptions.

Polarization drift in quantum networks is a major issue. Fiber transforms a transmitted signal’s polarization differently depending on its environment.

This invention addresses a key challenge in quantum communication networks by developing a controlled-NOT (CNOT) gate that operates between two degrees of freedom (DoFs) within a single photon: polarization and frequency.