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
- Yong Chae Lim
- Rangasayee Kannan
- Zhili Feng
- Adam Stevens
- Annetta Burger
- Brian Post
- Bryan Lim
- Carter Christopher
- Chance C Brown
- Debangshu Mukherjee
- Debraj De
- Gautam Malviya Thakur
- James Gaboardi
- Jesse McGaha
- Jian Chen
- Jiheon Jun
- Josh Michener
- Kevin Sparks
- Liangyu Qian
- Liz McBride
- Md Inzamam Ul Haque
- Olga S Ovchinnikova
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Serena Chen
- Sudarsanam Babu
- Todd Thomas
- Tomas Grejtak
- Wei Zhang
- William Peter
- Xiuling Nie
- Yiyu Wang
- Yukinori Yamamoto

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

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.

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

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.

The technologies provide a coating method to produce corrosion resistant and electrically conductive coating layer on metallic bipolar plates for hydrogen fuel cell and hydrogen electrolyzer applications.

Welding high temperature and/or high strength materials for aerospace or automobile manufacturing is challenging.

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