Session K13: Applications of Nuclear Physics

Live

Nuclear fission yields are important for determining the abundances and cosmic origin of $r$-process elements. The neutron-rich actinides and transactinides that are involved are inaccessible experimentally, and so theoretical computations are required to determine their properties. In this study, energy density functional theory is used to compute nuclear potential energy surfaces (PES) which are essential theoretical ingredients to determine fission yields. Multi-dimensional PES computations, covering the full fission trajectory from the ground state to scission, are too expensive to perform across the large region of the nuclear chart that is relevant for the $r$-process. \par To reduce the computation effort, we (i) employ the recently proposed efficient method for estimation of fission fragment yields [1] and (ii) we train a neural network (NN) using PES determined for selected nuclei, and then use machine learning to make predictions on the full region of interest in the nuclear chart. In this talk, we present the performance of this approach to global fission calculations. \par\noindent [1] {\it Efficient method for estimation of fission fragment yields of r-process nuclei}, J. Sadhukhan, S. A. Giuliani, Z. Matheson, and W. Nazarewicz, Phys. Rev. C 101, 065803 (2020   

Live

Theranostics is an emerging field of nuclear medicine that uses radioisotopes to~simultaneously image and treat disease. One possible theranostic isotope, $^{\mathrm{149}}$Tb, performs therapeutic and diagnostic functions with branches of alpha and positron decay modes. As a very proton-rich nucleus, $^{\mathrm{149}}$Tb (t$_{\mathrm{1/2\thinspace }}=$ 4.12 h) is restricted to accelerator production, harvesting and clinical work in close proximity. It has only been produced for clinical tests by a light-ion spallation reaction at a high-energy nuclear physics facility to date.~ We propose an alternate production method using a heavy-ion reaction close to the Coulomb barrier. In this study $^{\mathrm{89}}$Y($^{\mathrm{63}}$Cu,x)$^{\mathrm{149}}$X was studied as an indirect production pathway for all n$=$149 isobars. The preliminary physical yields for $^{\mathrm{149}}$Tb and other~reaction~products measured by offline gamma spectroscopy are compared to the PACE4 fusion-evaporation predictions. A near symmetric fission yield is also observed.~ This method has demonstrated significant radiochemical purity compared to spallation production methods, which makes for easier radiochemical separation.   

Live

While nuclear data play an important role in nuclear physics applications, it has become important to have a better understanding and try to minimize their uncertainties. In particular, there is a need for precision neutron-induced fission cross section measurements on fissile nuclei. Neutron-induced fission cross sections are typically measured as ratios, with a well-known standard in the denominator. While the $^{235}$U(n,f) standard is well measured, some light particle reactions are also well-known and their use as reference can provide information to remove shared systematic uncertainties that are present in an actinide-only ratio. The NIFFTE collaboration's fission time projection chamber (fissionTPC) is a 2$\times$2$\pi$ charged particle tracker designed for measuring neutron-induced fission. Detailed 3D track reconstruction of the reaction products enables evaluation of systematic effects and corresponding uncertainties which are less directly accessible by other measurement techniques. This work focuses on the recent measurement of the $^{235}$U(n,f) using as a reference the standard $^{6}$Li(n,t) reaction. Preliminary data of the $^{235}$U(n,f)/$^{6}$Li(n,t) measurement deployed at the Los Alamos Neutron Science Center will be presented.   

Live

In a novel experiment, a tritium beam was generated via the target normal sheath acceleration (TNSA) mechanism using tritiated titanium targets. Commercial 25-$\mu $m-thick Ti foil was cut into 500 \texttimes 500-$\mu $m$^{\mathrm{2}}$ squares and exposed for 2 h to \textasciitilde 1 atm. of 99.97{\%} pure tritium gas at 200\textdegree C. These targets were irradiated with an on-target intensity of 2 \texttimes 10$^{\mathrm{18}}$ W/cm$^{\mathrm{2\thinspace }}$with the high-energy (1250-kJ), short-pulse (10-ps) OMEGA EP laser. Using a Thomson parabola velocity analyzer, the energy spectrum of the beam was found to exponentially decrease with a high-energy cutoff at \textasciitilde 10 MeV. The total beam yield was determined to be \textasciitilde 10$^{\mathrm{12}}$ tritons per pulse, comparable to other TNSA experiments with protons. In a second experiment, the tritium beam was directed onto a secondary deuterated-polyethylene target, which produced 10$^{\mathrm{8}}$ neutrons from DT fusion nuclear reactions. Future applications of the tritium beam will be discussed. This work was supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0003856.   

Live

The decay scheme for Gd-153 has been scrutinized by researchers for decades, with little consensus on the electron capture transition probabilities feeding the several excited states and, arguably, the ground state of Eu-153. Absolute activity determinations based on liquid scintillation counting are often challenging for electron capture nuclides, with uncertainties on decay data propagating to significant uncertainties on counting efficiencies. Activity standards for electron capture nuclides are thus mostly based on coincidence counting techniques. We analyze experimental data acquired with the triple-to-double coincidence ratio method using activities determined by live-timed anticoincidence counting and demonstrate that the derived efficiency curves disfavor electron capture to the ground state. This result is in accord with a re-balancing of the decay scheme based on new absolute gamma-ray emission intensities.   

Live

Machine learning methods are used to analyze systematic trends in nuclear reaction cross section evaluations over the nuclear landscape. We employ a system of multiple generative adversarial neural networks to learn how a cross section changes when proton- and/or neutron-number change. We first apply this to a toy problem using a lattice of Gaussian functions; then the system, having learned from the whole lattice, can identify functions with artificial defects. Given this proof-of-concept, we apply a similar method to one channel of the TENDL data set, where a handful of defects do exist, and the system is used to identify areas of the chart that may need attention. This work is the foundation for a larger system that can incorporate correlations between reaction channels and enhance our understanding of trends in reaction data. Supported in part by LLNL under DOE Contract DE-AC52-07NA27344 and DOE Grant DE-FG02-03ER4127.