Probing the limits of statistical neutron capture for the r process: Experimental constraints on 141Cs nuclear level densities

Bibliographic Details
Title: Probing the limits of statistical neutron capture for the r process: Experimental constraints on 141Cs nuclear level densities
Authors: B. Greaves, D. Mücher, A. Spyrou, S. Goriely, D. Rochman, H.C. Berg, D.L. Bleuel, J.A. Clark, C. Dembski, P.A. Deyoung, E. Good, C.M. Harris, A.J. Koning, A.C. Larsen, S.N. Liddick, S.M. Lyons, M. Markova, M.J. Mogannam, G. Owens-Fryar, A. Palmisano-Kyle, A.L. Richard, E.K. Ronning, D. Santiago-Gonzalez, G. Savard, M.K. Smith, A. Sweet, A. Tsantiri
Source: Physics Letters B, Vol 871, Iss , Pp 139992- (2025)
Publisher Information: Elsevier, 2025.
Publication Year: 2025
Collection: LCC:Physics
Subject Terms: Nuclear level density, Statistical capture, β-Oslo method, R process, Physics, QC1-999
Description: The r-process abundance peaks, particularly near mass number A ∼ 130, reflect underlying nuclear structure effects such as closed neutron shells, yet modeling the nucleosynthesis in this region remains hindered by uncertain neutron-capture rates. These rates are especially sensitive to nuclear level densities (NLDs) and γ-ray strength functions of neutron-rich nuclei, where experimental data are scarce. We present the first experimental constraint on the NLD of 141Cs using the β-Oslo method, extending sensitivity to the neutron-rich regime near the N=82 closed shell. Our data allow for critical calibration of microscopic NLD models and reveal that 141Cs lies near the limit of statistical model applicability. Using this experimental input, we evaluate radiative neutron-capture rates across neighboring isotones using both Hauser–Feshbach (HF) and High Fidelity Resonance (HFR) models. Our results show order-of-magnitude rate increases for nuclei along the N=86 line, signaling a transition to resonance-dominated capture in this region. These findings underscore the importance of constraining NLDs to improve r-process reaction network predictions, particularly in environments where the validity of statistical models breaks down.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 0370-2693
Relation: http://www.sciencedirect.com/science/article/pii/S0370269325007506; https://doaj.org/toc/0370-2693
DOI: 10.1016/j.physletb.2025.139992
Access URL: https://doaj.org/article/5efeb8f555b54aed9ee799343388a467
Accession Number: edsdoj.5efeb8f555b54aed9ee799343388a467
Database: Directory of Open Access Journals
Description
ISSN:03702693
DOI:10.1016/j.physletb.2025.139992