Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate (23)
- Computing and Computational Sciences Directorate (35)
- Energy Science and Technology Directorate (217)
- Fusion and Fission Energy and Science Directorate (21)
- Information Technology Services Directorate (2)
- Isotope Science and Enrichment Directorate (6)
- National Security Sciences Directorate (17)
- Neutron Sciences Directorate (11)
- Physical Sciences Directorate
(128)
- User Facilities (27)
Researcher
- Chris Tyler
- Adam M Guss
- Justin West
- Peeyush Nandwana
- Ritin Mathews
- Brian Post
- Amit Shyam
- Andrzej Nycz
- Biruk A Feyissa
- Blane Fillingim
- Carrie Eckert
- David Olvera Trejo
- J.R. R Matheson
- Jaydeep Karandikar
- Josh Michener
- Kuntal De
- Lauren Heinrich
- Rangasayee Kannan
- Scott Smith
- Sudarsanam Babu
- Thomas Feldhausen
- Udaya C Kalluri
- Vilmos Kertesz
- Xiaohan Yang
- Yousub Lee
- Akash Jag Prasad
- Alex Plotkowski
- Alex Walters
- Andres Marquez Rossy
- Austin Carroll
- Brian Gibson
- Brian Sanders
- Bruce A Pint
- Bryan Lim
- Calen Kimmell
- Chris Masuo
- Christopher Fancher
- Clay Leach
- Daniel Jacobson
- Debjani Pal
- Emma Betters
- Gerald Tuskan
- Gordon Robertson
- Greg Corson
- Ilenne Del Valle Kessra
- Isaiah Dishner
- Jay D Huenemann
- Jay Reynolds
- Jeff Brookins
- Jeff Foster
- Jerry Parks
- Jesse Heineman
- Joanna Tannous
- John F Cahill
- John Potter
- Josh B Harbin
- Kyle Davis
- Liangyu Qian
- Nandhini Ashok
- Paul Abraham
- Peter Wang
- Ryan Dehoff
- Serena Chen
- Steven J Zinkle
- Tim Graening Seibert
- Tomas Grejtak
- Tony L Schmitz
- Vincent Paquit
- Vladimir Orlyanchik
- Weicheng Zhong
- Wei Tang
- Xiang Chen
- Yang Liu
- Yanli Wang
- Yasemin Kaygusuz
- Ying Yang
- Yiyu Wang
- Yutai Kato

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.

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.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

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.

Distortion generated during additive manufacturing of metallic components affect the build as well as the baseplate geometries. These distortions are significant enough to disqualify components for functional purposes.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

For additive manufacturing of large-scale parts, significant distortion can result from residual stresses during deposition and cooling. This can result in part scraps if the final part geometry is not contained in the additively manufactured preform.

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