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Reimagining nuclear materials for the future of medicine
Nuclear medicine has come a long way since Henri Becquerel first observed the penetrating energy of radioactive materials in 1896. Today, technetium-99m alone is used in more than 40 million diagnostic procedures every year—from cardiovascular imaging and bone scans to cancer detection—making it the undisputed workhorse of nuclear medicine. That single statistic tells you something important: An enormous portion of modern diagnostic medicine rests on a surprisingly narrow foundation, one built around a small number of aging research reactors that were never originally designed for continuous isotope production.
M. Kostuk, T. D. Uram, T. Evans, D. M. Orlov, M. E. Papka, D. Schissel
Fusion Science and Technology | Volume 74 | Number 1 | July-August 2018 | Pages 135-143
Technical Paper | doi.org/10.1080/15361055.2017.1390388
Articles are hosted by Taylor and Francis Online.
For the first time, an automatically triggered, between-pulse fusion science analysis code was run on-demand at a remotely located supercomputer at Argonne Leadership Computing Facility (ALCF, Lemont, Illinois) in support of in-process experiments being performed at DIII-D (San Diego, California). This represents a new paradigm for combining geographically distant experimental and high-performance computing facilities to provide enhanced data analysis that is quickly available to researchers. Enhanced analysis improves the understanding of the current pulse, translating into a more efficient use of experimental resources and quality of the resultant science. The analysis code used here, called SURFMN, calculates the magnetic structure of the plasma using Fourier transform. Increasing the number of Fourier components provides a more accurate determination of the stochastic boundary layer near the plasma edge by better resolving magnetic islands, but requires 26 min to complete using local DIII-D resources, putting it well outside the useful time range for between-pulse analysis. These islands relate to confinement and edge-localized mode suppression, and may be controlled by adjusting coil currents for the next pulse. ALCF has ensured on-demand execution of SURFMN by providing a reserved queue, a specialized service that launches the code after receiving an automatic trigger, and network access from the worker nodes for data transfer. Runs are executed on 252 cores of ALCF’s Cooley cluster and the data are available locally at DIII-D within 3 min of triggering. The original SURFMN design limits additional improvements with more cores; however, our work shows a path forward where codes that benefit from thousands of processors can run between pulses.