Filter Results
Related Organization
- Biological and Environmental Systems Science Directorate
(26)
- 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)
Researcher
- Alexander I Wiechert
- Andrew F May
- Annetta Burger
- Ben Garrison
- Brad Johnson
- Carter Christopher
- Chance C Brown
- Charlie Cook
- Christopher Hershey
- Costas Tsouris
- Craig Blue
- Daniel Rasmussen
- Debangshu Mukherjee
- Debraj De
- Gautam Malviya Thakur
- Gerald Tuskan
- Gs Jung
- Gyoung Gug Jang
- Hsin Wang
- Ilenne Del Valle Kessra
- Isaiah Dishner
- James Gaboardi
- James Klett
- Jeff Foster
- Jesse McGaha
- John F Cahill
- John Lindahl
- Josh Michener
- Kevin Sparks
- Liangyu Qian
- Liz McBride
- Md Inzamam Ul Haque
- Mike Zach
- Nedim Cinbiz
- Olga S Ovchinnikova
- Paul Abraham
- Radu Custelcean
- Todd Thomas
- Tony Beard
- Vilmos Kertesz
- Xiaohan Yang
- Xiuling Nie
- Yang Liu

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

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.

Among the methods for point source carbon capture, the absorption of CO2 using aqueous amines (namely MEA) from the post-combustion gas stream is currently considered the most promising.

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.

The technologies provide a system and method of needling of veiled AS4 fabric tape.

ORNL will develop an advanced high-performing RTG using a novel radioisotope heat source.

The invention provides on-line analysis of droplets for mass spectrometry.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.