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Polylactic acid (PLA) plastic waste has significant potential for methane production in anaerobic digestion, but its slow degradation rate hinders efficient fermentation. Pre-treatment of PLA plastic waste can enhance anaerobic fermentation efficiency, promoting resource utilization. PLA plastic cup sample was pre-treated by irradiation with 60Co-γ ray to study the changes of PLA molecular structure and soluble substance content under the irradiation with absorbed doses of 0, 20, 40 and 60 kGy. And the effect of ionizing irradiation on the anaerobic fermentation performance of PLA samples was investigated by the proteolytic enzyme enzymatic digestion experiments and the changes of anaerobic fermentation gas production. The results showed that the lactic acid content in the supernatant of PLA samples irradiated by 60Co-γ ray increased slightly with the increase of absorbed dose in the range of 0~60 kGy. The molecular structure of the samples did not change significantly, but their crystallinity and molecular weight decreased significantly. The lactate concentration and mass loss of the irradiated samples increased significantly during the enzymatic digestion process compared to the unirradiated samples. Specifically, The PLA sample with an absorbed dose of 60 kGy reached its maximum lactate concentration on the 4th day, which was 17.4% higher than that of non irradiated samples. The mass loss increased over time, which was 68.7% higher than that of non irradiated samples on the 7th day. The irradiated samples took significantly less time to reach gas production equilibrium in anaerobic fermentation, and the total gas production increased by 3.0%. The results indicate that γ-ray irradiation has potential application as a pretreatment technology for PLA plastics, and this study can provide a theoretical reference for the resourceful disposal of PLA plastics.

Borosilicate glass is currently the best comprehensive solidified material for deep disposal of high-level radioactive waste. The stability of borosilicate glass under irradiation is an important factor affecting the leakage of radioactive isotopes into the biosphere. In this study, three-component borosilicate glass (NBS) was irradiated by γ-rays at doses of 8 kGy and 800 kGy, respectively. The leaching behaviors of the irradiated samples at different absorbed doses were studied. The surface morphologies of the samples were analyzed using optical microscopy and scanning electron microscopy (SEM). The distributions of elements were analyzed using energy dispersive X-ray spectroscopy (EDS), and the elements in solution were characterized using inductively coupled plasma-optical emission spectroscopy (ICP-OES). The results indicate that the irradiation effects on the leaching behavior of borosilicate glass occurs at certain thresholds. When the corrosion time is prolonged, the corrosion effect gradually covers the irradiation effect of the glass. Compared with 8 kGy irradiation, NBS glass samples exhibit more significant changes in elemental behavior under 800 kGy irradiation. After high-dose irradiation, the effect of corrosion on surface morphology is more significant than at low doses, and the element leaching rate of NBS glass is higher after 7 days of corrosion.

Path planning for the complete coverage of nuclear radiation fields is necessary to ensure the radiation safety of regional operators in radiation environments. Based on a bio-inspired neural network algorithm, a complete coverage path-planning algorithm for the optimal control of the radiation dose is proposed. First, part of the terrain of the Fukushima nuclear power plant and the Monte Carlo particle transport program were used to construct the obstacle distribution and radiation dose field in a simulated nuclear radiation field. Subsequently, the Python programming language was used to conduct algorithm simulation experiments. Each grid of the simulated nuclear radiation field was defined as a neuron, and a bio-inspired neural network was established. The grid dose rate and neuronal activity were combined to achieve optimal control of radiation dose in path planning, and single, four, and eight mobile units were used for simulation experiments. The results showed that the planning path of a single mobile unit can achieve 100% coverage and a 4% coverage repetition rate and can first cover the low-dose area and delay the coverage of the high-dose area to achieve optimal control of the process and cumulative doses. The algorithm is improved via a multiunit collaborative search to increase the time efficiency of complete coverage and decrease the cumulative dose of monomers. The coverage repetition rates of four-unit and eight-unit simulations were 5.72% and 6.29%, respectively. The complete coverage times of the one-unit, four-unit, and eight-unit simulations were 30, 9, and 4 min, respectively, and the time efficiency was doubled. The maximum cumulative doses of the monomers for the one-unit, four-unit, and eight-unit simulations were 4.11×10-3, 1.28×10-3, and 0.85×10-3 mSv, respectively, which also decreased significantly. The proposed algorithm can achieve complete coverage path planning of optimal control of the process dose and cumulative dose. Moreover, the algorithm can coordinate multiunit path planning and significantly decrease the cumulative dose of monomers, which is critical for radiation protection during regional operations in a radiation environment.

BackgroundIt is an inevitable trend in nuclear logging to use controllable source instead of isotopic neutron source for neutron porosity logging.PurposeThis study aims to improve the feasibility and measurement accuracy of controllable D-D source neutron porosity logging by analyzing, the influence of mud on D-D source neutron porosity logging.MethodsFirstly, the response of mudstone in neutron porosity logging of three sources (241Am-Be radioactive source, D-T source and D-D source) was compared and analyzed by Monte Carlo simulation method. Then, by changing the near and far source distance in D-D source neutron porosity logging, the source distance combination of D-D source was optimized to weaken the influence of shale by changing the source distance.ResultsAnalysis results show that the mudstone response characteristics of D-D source and 241Am-Be radioactive source are relatively close. When the source distance design of D-D source is closer to 241Am-Be, i.e., the source distance combination of 25~45 cm is adopted, the mudstone influence in D-D source neutron porosity logging shows the highest degree of proximity to that of 241Am-Be radioactive source.ConclusionsAlthough the change of source spacing combination can not make the mudstone response of D-D source and 241Am-Be radioactive source completely consistent or completely eliminate the influence of argillaceous matter, this high degree of convergence provides an idea for mudstone correction in D-D source neutron porosity logging and has certain application significance for the compatible substitution of radioactive sources in logging instruments in the future.

AbstractMolybdenum is an essential metal in modern industry; accurate determination of the Mo content of its ores significantly enhances production efficiency during mining and processing. This study employs a hybrid variable selection method for effective data selection from the complex spectra of Mo ores obtained by laser-induced breakdown spectroscopy (LIBS). Specifically, it incorporates a second-derivative peak-finding method to identify significant peaks in wavelet-smoothed and normalized spectra, eliminates irrelevant variables using Pearson correlation coefficients relative to target contents, and utilizes a genetic algorithm to optimize the selected variable combinations. This method integrates partial least squares regression models to analyze the LIBS spectra of molybdenite, concentrate, and tailings. The findings demonstrate that the hybrid variable selection method effectively filters low-contribution data and enhances prediction accuracy. For molybdenite, concentrate, and tailings, the root mean square errors of prediction (RMSEP) were reduced to 0.0082, 0.3964, and 0.0008 wt%, with coefficients of determination (RP2) of 0.972, 0.970, and 0.929, respectively. By comparison, upon using the full spectra as input, RMSEP values of 0.0167, 0.9376, and 0.0013 wt% for molybdenite, concentrate, and tailings, respectively, with RP2 values of 0.885, 0.833, and 0.812 were recorded. [ABSTRACT FROM AUTHOR]

The silicon-aluminum ratio of the molecular sieves is a crucial control index for the quality of synthetic molecular sieves. Here a fast, simple and reliable sample preparation method, referred to as pouring and curing method, is described for determining the silicon-aluminum ratio of high silicon molecular sieves by energy dispersive x-ray fluorescence (EDXRF). Resin is used as the carrier with the addition of a curing agent, so that the sample powder is embedded in the resin matrix. By measuring sixteen random positions of the same cured sample, the homogeneity of the sample was evaluated to ensure the stability of the results. A double logarithmic calibration curve of the analysis line ratio and the corresponding concentration ratio of silicon and aluminum was established according to the binary ratio method. The results by EDXRF and inductively coupled plasma-optical emission spectrometer (ICP-OES) were compared with a relative standard error from 2.934 to 6.777%. The good precision shows that the pouring and curing method is a suitable for measuring the silicon-aluminum ratio of molecular sieves. [ABSTRACT FROM AUTHOR]