Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher.
Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?
Some links on this page may take you to non-federal websites. Their policies may differ from this site.
-
Free, publicly-accessible full text available November 1, 2025
-
Machine learning enabled measurements of astrophysical ( ) reactions with the SECAR recoil separatorThe synthesis of heavy elements in supernovae is affected by low-energy and reactions on unstable nuclei, yet experimental data on such reaction rates are scarce. The SECAR (SEparator for CApture Reactions) recoil separator at FRIB (Facility for Rare Isotope Beams) was originally designed to measure astrophysical reactions that change the mass of a nucleus significantly. We used a novel approach that integrates machine learning with ion-optical simulations to find an ion-optical solution for the separator that enables the measurement of reactions, despite the reaction leaving the mass of the nucleus nearly unchanged. A new measurement of the reaction in inverse kinematics with a MeV/nucleon beam (corresponding to MeV proton energy in normal kinematics) yielded a cross-section of mb and served as a proof of principle experiment for the new technique demonstrating its effectiveness in achieving the required performance criteria. This novel approach paves the way for studying astrophysically important reactions on unstable nuclei produced at FRIB. Published by the American Physical Society2025more » « lessFree, publicly-accessible full text available January 1, 2026