Developments in capture-γ libraries for nonproliferation applications

¹ Department of Nuclear Engineering, University of California, Berkeley, California 94720, USA
² Lawrence Livermore National Laboratory, Livermore, California 94550, USA
³ Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
⁴ Faculty of Mathematics and Physics, Charles University in Prague, CZ-180 00 Prague, Czech Republic
⁵ Centre for Energy Research, Hungarian Academy of Sciences, 1525 Budapest, Hungary
⁶ U. S. Army Research Laboratory, Adelphi, Maryland 20783, USA
⁷ Youngstown State University, Youngstown, Ohio 44555, USA
⁸ Technische Universit’ at M’ unchen, Forschungsneutronenquelle Heinz Maier-Leibnitz (FRM-II) Garching, Germany
⁹ Department of Engineering Physics, Air Force Institute of Technology, Wright-Patterson AFB, Ohio 45433, USA
¹⁰ Defense Threat Reduction Agency, Fort Belvoir, Virginia 22060, USA
¹¹ Department of Mechanical and Aerospace Engineering, Ohio State University, Columbus, Ohio 43210, USA
¹² National Institute of Standards and Technology, Gaithersburg, Maryland 20899, USA

^a e-mail: amhurst@berkeley.edu

Published online: 13 September 2017

Abstract

The neutron-capture reaction is fundamental for identifying and analyzing the γ-ray spectrum from an unknown assembly because it provides unambiguous information on the neutron-absorbing isotopes. Nondestructive-assay applications may exploit this phenomenon passively, for example, in the presence of spontaneous-fission neutrons, or actively where an external neutron source is used as a probe. There are known gaps in the Evaluated Nuclear Data File libraries corresponding to neutron-capture γ-ray data that otherwise limit transport-modeling applications. In this work, we describe how new thermal neutron-capture data are being used to improve information in the neutron-data libraries for isotopes relevant to nonproliferation applications. We address this problem by providing new experimentally-deduced partial and total neutron-capture reaction cross sections and then evaluate these data by comparison with statistical-model calculations.