Abstract：In the present work, we extend the Coulomb and Proximity Potential Model (CPPM) to study two-proton (2p) radioactivity from excited states while the proximity potential is chosen as AW95 proposed by Aage Withner in 1995. Demonstration reveals that the theoretical results acquired by CPPM exhibit a high level of consistency with prior theoretical models, such as the unified fission model (UFM), generalized liquid drop model (GLDM) and effective liquid drop model (ELDM). Furthermore, within the CPPM, we predicted the half-lives of potential 2p radioactive nuclei for which experimental data are currently unavailable. The predicted results were then assessed, compared with UFM, ELDM, and GLDM models, and examined in detail.
Keywords：2p radioactivity;CPPM;Half-lives;Excited state
Abstract：The sensitivity of an experiment to detect the Majorana neutrino mass via neutrinoless double beta decay (0νββ) strongly depends on the rate of background events that can mimic this decay. One major source of this background is the radioactive emissions from the laboratory environment. In our study, we focused on assessing the background contributions from environmental gamma rays, neutrons, and underground muons to the Jinping bolometric demonstration experiment. This experiment uses an array of lithium molybdate crystal bolometers to probe the potential 0νββ decay of the 100Mo isotope at the China Jinping Underground Laboratory. We also evaluated the shielding effectiveness of the experimental setup through an attenuation study. Our simulations indicate that the combined background from environmental gamma rays, neutrons, and muons in the relevant 100Mo 0νββ Q-value region can be reduced to approximately 0.003 cts/kg/keV/yr.
Abstract：As a unique probe, the precision measurement of pp solar neutrinos is important for studying the sun’s energy mechanism as it enables monitoring the thermodynamic equilibrium and studying neutrino oscillations in the vacuum-dominated region. For a large-scale liquid scintillator detector, a bottleneck for pp solar neutrino detection is the pile-up events of intrinsic 14C decay. This paper presents a few approaches to discriminating between pp solar neutrinos and 14C pile-up events by considering the differences in their time and spatial distributions. In this study, a Geant4-based Monte Carlo simulation is conducted. Multivariate analysis and deep learning technology are adopted to investigate the capability of 14C pile-up reduction. The BDTG (boosted decision trees with gradient boosting) model and VGG network demonstrate good performance in discriminating pp solar neutrinos and 14C double-pile-up events. Under the 14C concentration assumption of 5×10-18 g/g, the signal significance can achieve 10.3 and 15.6 using the statistics of only one day. In this case, the signal efficiency for discrimination using the BDTG model while rejecting 99.18% 14C double pile-up events is 51.1%, and that for the case where the VGG network is used while rejecting 99.81% of the 14C double pile-up events is 42.7%.
Keywords：Liquid scintillator detector;pp solar neutrinos;14C pile-up;Multivariate analysis;Deep learning
Abstract：The gradient element of the aperture gradient map is utilized directly to generate the aperture shape without modulation. This process can be likened to choosing the direction of negative gradient descent for the generic aperture shape optimization. The negative-gradient descent direction is more suitable under local conditions and has a slow convergence rate. To overcome these limitations, this study introduced conjugate gradients into aperture shape optimization based on gradient modulation. First, the aperture gradient map of the current beam was obtained for the proposed aperture shape optimization method, and the gradients of the aperture gradient map were modulated using conjugate gradients to form a modulated gradient map. The aperture shape was generated based on the modulated gradient map. The proposed optimization method does not change the optimal solution of the original optimization problem but changes the iterative search direction when generating the aperture shape. The performance of the proposed method was verified using cases of head and neck cancer, and prostate cancer. The optimization results indicate that the proposed optimization method better protects the organs at risk and rapidly reduces the objective function value by ensuring a similar dose distribution to the planning target volume. Compared to the contrasting methods, the normal tissue complication probability obtained by the proposed optimization method decreased by up to 4.61%, and the optimization time of the proposed method decreased by 5.26% on average for ten cancer cases. The effectiveness and acceleration of the proposed method were verified through comparative experiments. According to the comparative experiments, the results indicate that the proposed optimization method is more suitable for clinical applications. It is feasible for the aperture shape optimization involving the proposed method.
Abstract：In this study, a microscopic method for calculating the nuclear level density (NLD) based on the covariant density functional theory (CDFT) is developed. The particle-hole state density is calculated by a combinatorial method using single-particle level schemes obtained from the CDFT, and the level densities are then obtained by considering collective effects such as vibration and rotation. Our results are compared with those of other NLD models, including phenomenological, microstatistical and non-relativistic Hartree–Fock–Bogoliubov combinatorial models. This comparison suggests that the general trends among these models are essentially the same, except for some deviations among the different NLD models. In addition, the NLDs obtained using the CDFT combinatorial method with normalization are compared with experimental data, including the observed cumulative number of levels at low excitation energies and the measured NLDs. The CDFT combinatorial method yields results that are in reasonable agreement with the existing experimental data.
Keywords：Nuclear level density;Covariant density functional theory;Combinatorial method
Abstract：A fully digital data acquisition system based on a field-programmable gate array (FPGA) was developed for a CsI(Tl) array at the External Target Facility (ETF)in the Heavy Ion Research Facility in Lanzhou(HIRFL). To process the CsI(Tl) signals generated by γ-rays and light-charged ions, a scheme for digital pulse processing algorithms is proposed. Every step in the algorithms was benchmarked using standard γ and α sources. The scheme, which included a moving average filter, baseline restoration, leading-edge discrimination, moving window deconvolution and digital charge comparison was subsequently implemented on the FPGA. A good energy resolution of 5.7% for 1.33 MeV γ rays and excellent α-γ identification using the digital charge comparison method were achieved, which satisfies CsI(Tl) array performance requirements.
Keywords：CsI(Tl) array;On-line digital algorithms;Moving average filter;Moving window deconvolution;On-line particle identification algorithms
Abstract：A particle detector array designed for light-charged particles, known as the CsI-bowl, was built for exit channel selection for in-beam γ-ray spectroscopy experiments. This device is composed of 64 CsI(Tl) detectors, organized in a structure reminiscent of a tea-bowl. High quantum efficiency photodiodes, characterized by their minimal mass, were employed to collect scintillation light. Its design, construction, particle identification resolution, and its effectiveness in relation to exit channel selection is described in this paper. In source tests, the optimal figure of merit for the identification of α-particles and γ-rays using the charge comparison method was found to be 3.3 and 12.1 for CsI detectors coupled to photodiodes and avalanche photodiodes, respectively. The CsI-bowl demonstrated effectiveness in identifying particles, specifically the emission of protons and α-particles in the 58Ni(19F, xpyn) fusion–evaporation reaction, thereby enabling the selection of the desired exit channels.
Abstract：A new scintillating fiber detector inside magnetic shielding tube was designed and assembled for use in the next round of fusion experiments in the experimental advanced superconducting tokamak to provide D–T neutron yield with time resolution. In this study, Geant4 simulations were used to obtain the pulse-height spectra for ideal signals produced when detecting neutrons and gamma rays of multiple energies. One of the main sources of interference was found to be low-energy neutrons below 10-5 MeV, which can generate numerous secondary particles in the detector components, such as the magnetic shielding tube, leading to high-amplitude output signals. To address this issue, a compact thermal neutron shield containing a 1 mm Cd layer outside the magnetic shielding tube and a 5 mm inner Pb layer was specifically designed. Adverse effects on the measurement of fast neutrons and the shielding effect on gamma rays were considered. This can suppress the height of the signals caused by thermal neutrons to a level below the height corresponding to neutrons above 4 MeV because the yield of the latter is used for detector calibration. In addition, the detector has relatively flat sensitivity curves in the fast neutron region, with the intrinsic detection efficiencies (IDEs) of approximately 40%. For gamma rays with energies that are not too high (< 8 MeV), the IDEs of the detector are only approximately 20%, whereas for gamma rays below 1 MeV, the response curve cuts off earlier in the low-energy region, which is beneficial for avoiding counting saturation and signal accumulation.
Abstract：Loss of Coolant Accident (LOCA), Loss of Fluid Accident (LOFA), and Loss of Vacuum Accident (LOVA) are the most severe accidents that can occur in Nuclear Power Reactors (NPRs). These accidents occur when the reactor loses its cooling media, leading to uncontrolled chain reactions akin to a nuclear bomb. This article is focused on exploring methods to prevent such accidents and ensure that the reactor cooling system remains fully controlled. The Reactor Coolant Pump (RCP) has a pivotal role in facilitating heat exchange between the primary cycle, which is connected to the reactor core, and the secondary cycle associated with the steam generator. Furthermore, the RCP is integral to preventing catastrophic events such as LOCA, LOFA, and LOVA accidents. In this study, we discuss the most critical aspects related to the RCP, specifically focusing on RCP control and RCP fault diagnosis. The AI-based adaptive fuzzy method is used to regulate the RCP’s speed and torque, whereas the Neural Fault Diagnosis System (NFDS) is implemented for alarm signaling and fault diagnosis in nuclear reactors. To address the limitations of linguistic and statistical intelligence approaches, an integration of the statistical approach with fuzzy logic has been proposed. This integrated system leverages the strengths of both methods. Adaptive fuzzy control was applied to the VVER 1200 NPR-RCP induction motor, and the NFDS was implemented on the Kori-2 NPR-RCP.
Abstract：With the growing threat of airborne epidemics, there has been an increasing emphasis on personal protection. Masks serve as our primary external defense against bacteria and viruses that might enter the respiratory tract. Hence, it's crucial to develop a polypropylene (PP) nonwoven fabric with quick antibacterial capabilities as a key component for masks. This study introduces silver nanoclusters (AgNCs) into non-woven PP using radiation technology to infuse antibacterial properties. Initially, a solid ligand (PP-g-PAA) was procured via radiation grafting of the ligand polyacrylic acid (PAA), which was incorporated into the nonwoven PP with the aid of a crosslinking agent at a lower absorbed dosage. Subsequently, AgNCs were synthesized in situ on PP-g-PAA via an interaction between PAA and AgNCs, leading directly to the formation of AgNCs@PP-g-PAA composites. Owing to the hydrophilicity of PAA, AgNCs@PP-g-PAA maintains good moisture permeability even when the voids are heavily saturated with PAA gel, preventing droplet aggregation by diffusing droplets on the surface of the material. This feature enhances the comfort of the masks. Most importantly, due to the incorporation of AgNCs, AgNCs@PP-g-PAA demonstrates outstanding antibacterial effects against E. coli and S. aureus, nearly achieving an instant "touch and kill" outcome. In conclusion, we synthesized a modified nonwoven fabric with significant antibacterial activity using a simple synthetic route, offering a promising material that provides improved personal protection.
Abstract：Radio frequency windows are developed and evaluated for a 650 MHz continuous-wave multibeam klystron. Thin-pillbox windows with alumina and beryllia disks are designed with an average RF power of CW 400 kW. Results of a cold test and tuning procedures are described. The final measured S11 curves under the required bandwidth are less than -32.0 and -26.9 dB for alumina and beryllia windows, respectively. The windows are tested up to CW 143 kW for traveling waves and CW 110 kW for standing waves using a solid-state amplifier as an RF power source. Multipactor simulations for windows and benchmark studies for the thermal analysis of ceramic disks are introduced.
Abstract：Intensity-modulated particle therapy (IMPT) with carbon ions is comparatively susceptible to various uncertainties caused by breathing motion, including range, setup, and target positioning uncertainties. To determine relative biological effectiveness-weighted dose (RWD) distributions that are resilient to these uncertainties, the reference phase-based four-dimensional (4D) robust optimization (RP-4DRO) and each phase-based 4D robust optimization (EP-4DRO) method in carbon-ion IMPT treatment planning were evaluated and compared. Based on RWD distributions, 4DRO methods were compared with 4D conventional optimization using planning target volume (PTV) margins (PTV-based optimization) to assess the effectiveness of the robust optimization methods. Carbon-ion IMPT treatment planning was conducted in a cohort of five lung cancer patients. The results indicated that the EP-4DRO method provided better robustness (P=0.080) and improved plan quality (P=0.225) for the clinical target volume (CTV) in the individual respiratory phase when compared with the PTV-based optimization. Compared with the PTV-based optimization, the RP-4DRO method ensured the robustness (P=0.022) of the dose distributions in the reference breathing phase, albeit with a slight sacrifice of the target coverage (P=0.450). Both 4DRO methods successfully maintained the doses delivered to the organs at risk (OARs) below tolerable levels, which were lower than the doses in the PTV-based optimization (P<0.05). Furthermore, the RP-4DRO method exhibited significantly superior performance when compared with the EP-4DRO method in enhancing overall OAR sparing in either the individual respiratory phase or reference respiratory phase (P<0.05). In general, both 4DRO methods outperformed the PTV-based optimization in terms of OAR sparing and robustness.
Abstract：To understand the dynamical system scaling (DSS) analysis theory, the applicability of DSS β- and ω-strain transformation methods for the scaling analysis of complex loops was explored. A simplified model consisting of two loops was established based on the primary and secondary sides of a nuclear reactor, and β- and ω-strain transformation methods were used to analyze the single-phase natural circulation in the primary circuit. For comparison with the traditional method, simplified DSS β- and ω-strain methods were developed based on the standard scaling criterion. The strain parameters in these four methods were modified to form multiple groups of scaled-down cases. The transient process of the natural circulation was simulated using the Relap5 code, and the variation in the dynamic flow characteristics with the strain numbers was obtained using different scaling methods. The results show that both the simplified and standard DSS methods can simulate the dynamic characteristics of natural circulation in the primary circuit. The scaled-down cases in the simplified method exhibit the same geometric scaling and correspond to small core power ratios. By contrast, different scaled-down cases in the standard DSS method correspond to different geometric scaling criteria and require more power. The dynamic process of natural circulation can be simulated more accurately using the standard DSS method.
Keywords：Dynamical System Scaling analysis;β-strain transformation;ω-strain transformation;Natural circulation
Abstract：Alloys of uranium and molybdenum are considered as the future of nuclear fuel and defense materials. However, surface corrosion is a fundamental problem in practical applications and storage. In this study, the static and dynamic evolution of carbon monoxide (CO) adsorption and dissociation on γ-U (1 0 0) surface with different Mo doping levels was investigated based on density functional theory and ab initio molecular dynamics. During the static calculation phase, parameters, such as adsorption energy, configuration, and Bader charge, were evaluated at all adsorption sites. Furthermore, the time-dependent behavior of CO molecule adsorption were investigated at the most favorable sites. The minimum energy paths for CO molecular dissociation and atom migration were investigated using the transition state search method. The results demonstrated that the CO on the uranium surface mainly manifests as chemical adsorption before dissociation of the CO molecule. The CO molecule exhibited a tendency to rotate and tilt upright adsorption. However, it is difficult for CO adsorption on the surface in one of the configurations with CO molecule in vertical direction but oxygen (O) is closer to the surface. Bader charge illustrates that the charge transfers from slab atoms to the 2π* antibonding orbital of CO molecule and particularly occurs in carbon (C) atoms. The time is less than 100 fs for the adsorptions that forms embryos with tilt upright in dynamics evolution. The density of states elucidates that the overlapping hybridization of C and O 2p orbitals is mainly formed via the d orbitals of uranium and molybdenum (Mo) atoms in the dissociation and re-adsorption of CO molecule. In conclusion, Mo-doping of the surface can decelerate the adsorption and dissociation of CO molecules. A Mo-doped surface, created through ion injection, enhanced the resistance to uranium-induced surface corrosion.
Keywords：Adsorption and dissociation;Uranium;CO molecule;Density functional theory;ab-initio molecular dynamics
Abstract：Gamma ray shielding is essential to ensure the safety of personnel and equipment in facilities and environments where radiation exists. The Monte Carlo technique is vital for analyzing the gamma-ray shielding capabilities of materials. In this study, a simple Monte Carlo code, EJUSTCO, is developed to cd simulate gamma radiation transport in shielding materials for academic purposes. The code considers the photoelectric effect, Compton (incoherent) scattering, pair production, and photon annihilation as the dominant interaction mechanisms in the gamma radiation shielding problem. Variance reduction techniques, such as the Russian roulette, survival weighting, and exponential transformation, are incorporated into the code to improve computational efficiency. Predicting the exponential transformation parameter typically requires trial and error as well as expertise. Herein, a deep learning neural network is proposed as a viable method for predicting this parameter for the first time. The model achieves an MSE of 0.00076752 and an R-value of 0.99998. The exposure buildup factors and radiation dose rates due to the passage of gamma radiation with different source energies and varying thicknesses of lead, water, iron, concrete, and aluminum in single-, double-, and triple-layer material systems are validated by comparing the results with those of MCNP, ESG, ANS-6.4.3, MCBLD, MONTEREY MARK (M), PENELOPE, and experiments. Average errors of 5.6%, 2.75%, and 10% are achieved for the exposure buildup factor in single-, double-, and triple-layer materials, respectively. A significant parameter that is not considered in similar studies is the gamma ray albedo. In the EJUSTCO code, the total number and energy albedos have been computed. The results are compared with those of MCNP, FOTELP, and PENELOPE. In general, the EJUSTCO-developed code can be employed to assess the performance of radiation shielding materials because the validation results are consistent with theoretical, experimental, and literary results.