Estudo das reações >sup<nat>/sup<Pb(p,xn)>sup<201-207>/sup<Bi e discussão de possíveis contribuições astrofísicas para o processo r

Abstract

We analyzed the possible neutron sources for r-process production in stars of first, second and third generation. We propose a new mechanism of dynamic production for r-elements based on (p, xn) and (n, ) reactions on heavy nuclides. We called this r 2 p mechanism. We investigated proton and neutron energies that make that mechanism possible. Our model was able to reproduce r-elements like thorium and uranium with neutron flux of 10 20 neutrons ⋅ s −1 cm −3 . Critical conditions for neutrons flux of > 10 30 neutrons ⋅ s −1 cm −3 or slow r-process neutron flux (∼ 10 10 neutrons ⋅ s −1 cm −3 ) can be reproduced by our model, depending on the initial conditions. We discussed possible astrophysical sites for that mechanism and possible consequences for 232 Th, 235,238 U, and 244 Pu nucleochronometers.The study of nat Pb(p, xn) 201−207 Bi reactions have been made using 18−30 MeV proton beam energies from IPEN/CNEN's cyclotrons. We measured the cross-sections for these reactions and compared with theoretical simulations made with TALYS code. The nuclear reaction threshold of 204 Pb(p, 3n) 202 Bi, and 204 Pb(p, 4n) 201 Bi are determined. We discuss possible consequences of that results for the r-process. Also, we discuss possible discrepancies among our results and theoretical simulations for the neutron bind energy and Coulomb barrier of bismuth.The spectroscopy study with HPGe detectors has been made in association with the half-live measurement in order to fully identify the isotopes' formation. We noted some discrepancies in the energy levels of the IT isotope 204 Pb that comes from 204,206 Pb(p, xn) 204 Bi reactions. This may be related to a new possible state for this reaction at low energies above the Coulomb barrier. Finally, we have for the first time measured the cross reactions for these reactions at that proton energies.A new non-linear energy calibration method is developed, based in Principal Components Analysis (PCA). Our method is called Weighted Principal Polynomial Analysis (WPPA). We discuss possible uses of that method in nuclear physics and astronomy measurements. Machine learning for physics analysis could also use that algorithm.