arXiv subjects

Xiangai Deng

Publications and source records attributed to Xiangai Deng.

3 recordsLinked to original sources

arXiv2026

Enhanced electron injection for efficient proton acceleration and neutron production in femtosecond laser-driven nano-structured targets

Micro- or nano-structured targets are advantageous in enhancing and manipulating laser-proton acceleration, due to the increased absorption of laser energy and onset of direct laser acceleration for high-energy electrons. Here, we experimentally demonstrate that nano-wire-array printed on a flat substrate is an efficient nano-injector of relativistic electrons that leads to a significant boost of laser-driven proton acceleration and neutron production beyond normal geometry. By employing an ultra-intense (2*1021 W/cm2) femtosecond laser pulse to irradiate nano-wire-array targets, protons with cut-off energies of 62.8 MeV are generated, and notably, the energy conversion efficiency from laser to protons reaches up to 9% - 3.5 times higher than that of flat foils. After bombarding a beryllium converter, 1.1*1010 neutrons are produced. Full 3D particle-in-cell simulations have reproduced experimental results and reveal interference mechanisms between the nano-wires and substrate, leading to continuous pumping of electrons from the substrate and standing-wave enhanced re-injection from the wire tip. This efficient injection finally results in the large sheath field and thus high yield of energetic protons and neutrons. Dependence on the wire length and scaling with laser amplitude are further discussed. These results suggest that 3D-printed structures are promising in developing compact laser-driven high-flux proton and neutron sources for numerous applications.

physics.plasm-ph↗

arXiv2025

Production of Iodine Isotopes via Ultra-intense Laser Driven Photonuclear Reactions

The investigation and production of proton-rich iodine isotopes predominantly rely on conventional accelerator-based methods, typically requiring prolonged irradiation periods to measure or achieve quantifiable yields for isotopic isolation. Bremsstrahlung radiation sources generated by high-power laser-plasma-accelerated electron beams with ultrahigh charge (tens of nanocoulombs) bombarding high-Z targets demonstrate extraordinary photon flux characteristics. An electron beam with a total charge of approximately 47.7 nC (E$_e$ $\gt$ 10.4 MeV) was generated in our experiment by focusing a ultra-intense laser pulse onto a deuterium gas jet. Laser-driven bremsstrahlung was employed to induce $^{127}I$$(γ,xn)$ ($x$ = 1,3,4,6-8), and the product yields and the corresponding flux-weighted average cross sections are reported. Our results demonstrate production of medical isotopes, with average yields of $^{124}$I and $^{123}$I at approximately $9.83\pm0.45\times10^{5}$/shot and $2.81\pm0.11\times10^{5}$/shot, respectively. This method, utilizing high-power lasers to generate bremsstrahlung radiation, shows significant potential for medical applications and opens new avenues for studying photonuclear processes in astrophysical contexts.

nucl-ex↗

arXiv2023

Machine learning method for $^{12}$C event classification and reconstruction in the active target time-projection chamber

Active target time projection chambers are important tools in low energy radioactive ion beams or gamma rays related researches. In this work, we present the application of machine learning methods to the analysis of data obtained from an active target time projection chamber. Specifically, we investigate the effectiveness of Visual Geometry Group (VGG) and the Residual neural Network (ResNet) models for event classification and reconstruction in decays from the excited $2^+_2$ state in $^{12}$C Hoyle rotation band. The results show that machine learning methods are effective in identifying $^{12}$C events from the background noise, with ResNet-34 achieving an impressive precision of 0.99 on simulation data, and the best performing event reconstruction model ResNet-18 providing an energy resolution of $σ_E<77$ keV and an angular reconstruction deviation of $σ_θ<0.1$ rad. The promising results suggest that the ResNet model trained on Monte Carlo samples could be used for future classifying and predicting experimental data in active target time projection chambers related experiments.

physics.ins-det↗