ANS is committed to advancing, fostering, and promoting the development and application of nuclear sciences and technologies to benefit society.
Explore the many uses for nuclear science and its impact on energy, the environment, healthcare, food, and more.
Explore membership for yourself or for your organization.
Conference Spotlight
2026 ANS Annual Conference
May 31–June 3, 2026
Denver, CO|Sheraton Denver
Latest Magazine Issues
Feb 2026
Jul 2025
Latest Journal Issues
Nuclear Science and Engineering
February 2026
Nuclear Technology
January 2026
Fusion Science and Technology
Latest News
DOE, General Matter team up for new fuel mission at Hanford
The Department of Energy's Office of Environmental Management (EM) on Tuesday announced a partnership with California-based nuclear fuel company General Matter for the potential use of the long-idle Fuels and Materials Examination Facility (FMEF) at the Hanford Site in Washington state.
According to the announcement, the DOE and General Matter have signed a lease to explore the FMEF's potential to be used for advanced nuclear fuel cycle technologies and materials, in part to help satisfy the predicted future requirements of artificial intelligence.
M. Čopič, T. Kalin, G. Pregl, F. Žerdin
Nuclear Science and Engineering | Volume 19 | Number 1 | May 1964 | Pages 74-79
Technical Paper | doi.org/10.13182/NSE64-A19790
Articles are hosted by Taylor and Francis Online.
The thermal-neutron diffusion constant was measured in a plexiglas system with empty channels, using the pulsed-neutron-source technique. From separate sets of measurements on rectangular blocks, the diffusion constants parallel and perpendicular to channels were determined, whereas the measurements on cubes give the average diffusion constant. The results are compared with existing theoretical estimations. It is found that the average diffusion constant is well below the theoretical predictions of Behrens. On the other hand, the difference between the parallel and the perpendicular diffusion constant is almost as large as predicted theoretically.