Eur. Phys. J. A (2015) 51: 167
https://doi.org/10.1140/epja/i2015-15167-y

Review

From emissions to (n,xn) cross sections of interest: The role of GAINS and GRAPhEME in nuclear reaction modeling

¹ Université de Strasbourg, IPHC, 23 rue du Loess, 67037, Strasbourg, France
² CNRS, UMR7178, 67037, Strasbourg, France
³ Horia Hulubei National Institute of Physics and Nuclear Engineering, Str. Reactorului 30, 077125, Bucharest-Magurele, Romania
⁴ Studiecentrum voor Kernenergie, Centre d’Etude de l’Energie Nucléaire, B-2400, Mol, Belgium
⁵ European Commission, Joint Research Centre, Institute for Reference Materials and Measurements, Retieseweg 111, B-2440, Geel, Belgium
⁶ University of Bucharest, Faculty of Physics, Atomistilor 405, 077125, Bucharest-Magurele, Romania

^* e-mail: maelle.kerveno@iphc.cnrs.fr

Received: 20 February 2015
Accepted: 1 July 2015
Published online: 23 December 2015

Abstract

During the last 10 years, in the general context of nuclear energy applications and future reactors development, our collaboration has performed measurements of (n,x n cross sections to study (n,xn) reactions. Large sets of new and accurate experimental data have been produced on a variety of nuclei from ⁷Li to ²³⁸U. Comparisons with nuclear reaction code calculations have shown that the predictions of these exclusive cross sections are a real challenge for the theoretical codes. Indeed many processes are involved as evaporation, fission if fissionable nucleus, direct and pre-equilibrium reactions, etc. All these processes should be simultaneously well described by the models that using nuclear structure description for optical potential, level densities, decay scheme, etc. In this article, we review what we have learned since the last P(ND)² workshop held in 2005 (A.J.M. Plompen, Proceedings of the Perspectives on Nuclear data for the Next Decade Workshop, Bruyères-le-Châtel, France, 26-28 September 2005, NEA Report N° 6121, p. 151) and highlight how we can further progress in this field in order to provide new, complete, accurate and relevant experimental data.