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Materials Science & Technology
The objectives of MSTD are: promote the advancement of materials science in Nuclear Science Technology; support the multidisciplines which constitute it; encourage research by providing a forum for the presentation, exchange, and documentation of relevant information; promote the interaction and communication among its members; and recognize and reward its members for significant contributions to the field of materials science in nuclear technology.
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ANS Student Conference 2025
April 3–5, 2025
Albuquerque, NM|The University of New Mexico
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The Standards Committee is responsible for the development and maintenance of voluntary consensus standards that address the design, analysis, and operation of components, systems, and facilities related to the application of nuclear science and technology. Find out What’s New, check out the Standards Store, or Get Involved today!
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Latest News
First astatine-labeled compound shipped in the U.S.
The Department of Energy’s National Isotope Development Center (NIDC) on March 31 announced the successful long-distance shipment in the United States of a biologically active compound labeled with the medical radioisotope astatine-211 (At-211). Because previous shipments have included only the “bare” isotope, the NIDC has described the development as “unleashing medical innovation.”
Thomas E. Booth, James E. Gubernatis
Nuclear Science and Engineering | Volume 165 | Number 3 | July 2010 | Pages 283-291
Technical Paper | doi.org/10.13182/NSE09-62
Articles are hosted by Taylor and Francis Online.
Recently, we proposed a modified power iteration method that simultaneously determines the dominant and subdominant eigenvalues and eigenfunctions of a matrix or a continuous operator. One advantage of this method is the convergence rate to the dominant eigenfunction being [vertical bar]k3[vertical bar]/k1 instead of [vertical bar]k2[vertical bar]/k1, a potentially significant acceleration. One challenge for a Monte Carlo implementation of this method is that the second eigenfunction is represented by particles of both positive and negative weights that somehow must sum (cancel) to estimate the second eigenfunction faithfully. Our previous Monte Carlo work has demonstrated the improved convergence rate by using a point flux estimator method and a binning method to effect this cancellation. This paper presents an exact method that cancels over a region instead of at points or in small bins and has the potential of being significantly more efficient than the other two.