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The current state of research in the field of nuclear and thermonuclear power aimed at creating power generation plants makes it possible to predict the further development of modern power industry in the direction hybrid reactor power plants. Such hybrid systems include a tokamak with reactor technologies, worked out in detail in Russia, and systems with an additional source of neutrons. Power generation plants using tokamaks and accelerators with the required level of proton energy will be of exceptionally large size and power, which will postpone their construction on an industrial scale to the distant future. The ongoing research is aimed at the development of small generation and has the prospect of entering the field of energy use in a shorter period. The hybrid reactor facility under study consists of an axisymmetric assembly of fuel blocks of a high-temperature gas-cooled reactor and a linear plasma source of additional neutrons. The paper demonstrates the results of optimization plasma-physical, thermophysical and gas-dynamic studies, the purpose of which is to level the distortions of the power density field, which are formed in the volume of the multiplicating part of the facility due to the pulsed operation of the plasma source of D-T-neutrons. The studies on increasing the “brightness” of the source and modeling its operating modes were carried out using the DOL and PRIZMA programs. The thermophysical optimization and gas-dynamic calculations were performed using the verified SERPENT and FloEFD software codes. The calculations were made on a high-performance cluster of the Tomsk Polytechnic University.

The authors investigate the neutronic characteristics of the operating mode of a hybrid nuclear-thermonuclear reactor. The facility under study consists of a modified core of a high-temperature gas-cooled thorium reactor and an extended plasma neutron source penetrating the near-axial region of the core. The proposed facility has a generated power that is convenient for the regional level (60–100 MW), acceptable geometric dimensions and a low level of radioactive waste. The paper demonstrates optimization neutronic studies, the purpose of which is to level the resulting offsets of the radial energy release field, which are formed within the fuel part of the blanket during long-term operation and due to the pulsed operation of the plasma D-T neutron source. The calculations were performed using both previously developed models and the SERPENT 2.1.31 precision program code based on the Monte Carlo method. In the simulation, we used pointwise evaluated nuclear data converted from the ENDF-B/VII.1 library, as well as additional data for neutron scattering in graphite from ENDF-B/VII.0, based on the S (α, β) formalism.

Up today, two hyper research projects to achieve nuclear fusion energy exist; inertial confinement fusion (ICF) driven by laser, called national ignition facility (NIF) and magnetic confinement fusion the international thermonuclear experimental reactor (ITER) project. In reaching the required temperature and pressure, to ignite nuclear fusion reactor, is technologically complex and economically expensive. Thus, a breakthrough and a short cut, other alternative methods should be considered. Pulsed power ICF driver with repetitive pulse operation, mainly dense plasma focus (DPF) machines for high yield fusion neutrons could be taken as drivers for the fission blanket operation. The setup can be a cost-effective and efficient. In this article, we consider a set of two medium energy sizes DPF to produce simultaneously dense plasma columns, operating as thermonuclear plasma driver, to pierce the pellet target for external nuclear fusion reactions. These DPFs produce sufficient fast neutrons for the fission process in the neutral uranium or thorium and/or weak enriched uranium blanket. The drive systems and the concept for delivering thermonuclear plasma to pellets target in the magnetic free zone of central region will be presented. The feasibility of such fusion–fission hybrid reactor will be discussed.

In the present study, a three-layer artificial neural network (ANN) and nonlinear regression models were developed to predict the performance of biogas production from the anaerobic hybrid reactor (AHR). Firstly, the performance of an AHR which is filled with perlite (2.38–4.36 mm) at fill rates of 1/3, 1/4 and 1/5 for the treatment of synthetic wastewater was investigated at a loading rate of 5, 7.5, 10, 12.5 and 15 kg COD m−3 day with 12, 24, 36 and 48 h of hydraulic retention time (HRT) under mesophilic conditions (37 ± 1 °C). In this study, experimental data were used to estimate the biogas production rate with models produced using both ANNs and nonlinear regression methods. Moreover, ten related variables, such as reactor fill ratio, influent pH, effluent pH, influent alkalinity, effluent alkalinity, organic loading rate, effluent chemical oxygen demand, effluent total suspended solids, effluent suspended solids and effluent volatile suspended solids, were selected as inputs of the model. Finally, ANN and nonlinear regression models describing the biogas production rate were developed. The R2, IA, FA2, RMSE, MB for ANNs and nonlinear regression models were found to be 0.9852 and 0.9878, 0.9956 and 0.9945, 0.9973 and 0.9254, 217.4 and 332, 36 and 222, respectively. The statistical quality of ANNs and nonlinear regression models were found to be significant due to its high correlation between experimental and simulated biogas values. The ANN model generally showed greater potential in determining the relationship between input data and the biogas production rate according to statistical parameters (except R2 and R). The results showed that the proposed ANNs and nonlinear regression models performed well in predicting the biogas production rate of AHR on behalf of avoiding economic and environmental sustainability problems.Graphic abstract

The increasing presence of persistent pollutants in industrial wastewater underscores the shortcomings of conventional treatment methods, prompting the adoption of advanced oxidation processes (AOPs) for sustainable water remediation. This review examines the development of AOPs, focusing on their ability to produce hydroxyl radicals and reactive oxygen species (ROS) to mineralize complex pollutants. Homogeneous systems such as Fenton’s reagent show high degradation efficiency. However, challenges like pH sensitivity, catalyst recovery issues, sludge generation, and energy-intensive operations limit their scalability. Heterogeneous catalysts, such as TiO2-based photocatalysts and Fe3O4 composites, offer improved pH adaptability, visible-light activation, and recyclability. Emerging innovations like ultraviolet light emitting diode (UV-LED)-driven systems, plasma-assisted oxidation, and artificial intelligence (AI)-enhanced hybrid reactors demonstrate progress in energy efficiency and process optimization. Nevertheless, key challenges remain, including secondary byproduct formation, mass transfer constraints, and economic feasibility for large-scale applications. Integrating AOPs with membrane filtration or biological treatments enhances treatment synergy, while advances in materials science and computational modeling refine catalyst design and reaction mechanisms. Addressing barriers in energy use, catalyst durability, and practical adaptability requires multidisciplinary collaboration. This review highlights AOPs as pivotal solutions for water security amid growing environmental pollution, urging targeted research to bridge gaps between laboratory success and real-world implementation.

In this study, a simplified computational model of the blanket mock-up is created using the SERPENT Monte Carlo Code. The nuclear data is obtained from the enriched ENDF/B.VII.1 data library to conduct this study. The model is validated, as the error percentage for 63 Cu(n,2n) 62 Cu and 65 Cu(n,2n) 64 Cu reactions is less than 10% when compared to experimental results. The computational model is used to calculate the tritium production rate in different lithium zones with various neutron multipliers (U, Pb) and without any multipliers. The results show that the tritium production rate with a uranium multiplier is 86% higher than with a lead multiplier and 238% higher than with no multiplier. The neutron energy spectrum shows a peak in the 0.1 MeV to 10 MeV energy range for every case. This study also examines the effects of fusion neutrons on different isotopes, providing valuable data on how materials behave under high-speed neutron exposure.

Z-Pinch fusion centre, encased by a fission envelope, serves as an individual neutron source. It can expeditiously catalyze fission reactions in 238U and 232Th nuclear materials, which are hard to use in current commercial nuclear reactors. This is the essence of the Z-Pinch Driven Fusion-Fission Hybrid Reactor (Z-FFR). The fusion core acts as a stand-alone neutron source, efficiently driving fission reactions in nuclear energy materials that are difficult to use in existing commercial nuclear reactors, such as 238U and 232Th. Then it can deliver enormous amounts of energy in a stable and controlled manner. This new type of reactor uses the fact that the fission discharges energy (∼200 Megaelectronvolts) and the neutrons’ number released is much greater than that released when the fusion discharge energy (∼17 Megaelectronvolts). Moreover, the neutrons’ number is released to achieve energy amplification and neutron amplification, significantly makes it less difficult in implementing fusion technology applications, and increases the utilisation of nuclear energy resources by more than one order of magnitude. The Z-FFR has a complex design and covers a wide range of physical processes. The use of deep learning to design the device model allows for a more closely engineered model. Deep learning allows the model design to be decomposed, the Z-FFR design data flow to be analysed and optimised, and the tedious physical process to be turned into a deep learning network layering so that we can obtain an accurate physical model. The deuterium-tritium combustion depth parameters obtained by deep learning reach around 30%, demonstrating the ability to achieve fusion self-sustained combustion.

New data on biogas production and treatment of cattle wastewater were registered using an upflow anaerobic sludge blanket-anaerobic filter (UASB-AF) hybrid reactor under mesophilic temperature conditions (37 °C). The reactor was operated in semi-continuous mode with hydraulic retention times of 6, 5, 3 and 2 days and organic loading rates of 3.8, 4.6, 7.0 and 10.8 kg CODt m−3 d−1. Biogas volumes of 0.6–0.8 m3 m−3 d−1 (3.8–4.6 kg CODt m−3 d−1) and 1.2–1.4 m3 m−3 d−1 (7.0–10.8 kg CODt m−3 d−1), with methane concentrations between 69 and 75%, were attained. The removal of organic matter with values of 60–81% (CODt) and 51–75% (CODs) allowed methane yields of 0.155–0.183 m3 CH4 kg−1 CODt and 0.401–0.513 m3 CH4 kg−1 CODs to be obtained. Volatile solids were removed in 34 to 69%, with corresponding methane yields of 0.27 to 0.42 m3 CH4 kg−1 VSremoved. The good performance of the novel hybrid reactor was demonstrated by biogas outputs higher than reported previously in the literature, along with the quality of the gas obtained in the various experimental phases. The hybrid reactor investigated in this study presents comparative advantages, particularly in relation to conventional complete mixture units, considering economic factors such as energy consumption, reactor volume and installation area.

The combination of photocatalysis and membrane filtration in a single reactor has been proposed, since the photocatalytic treatment may degrade the pollutants retained by the membrane and reduce fouling. However, polymeric membranes can be susceptible to degradation by UV radiation and free radicals. In the present study, five commercial polymeric membranes were exposed to ultraviolet (UV) radiation before and after applying a sol–gel coating with TiO2 nanoparticles. Membrane stability was characterized by changes in hydrophilicity as well as analysis of soluble substances and nanoparticles detached into the aqueous medium, and by Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), and energy-dispersive X-ray spectrometry (EDS) for structural, morphological, and elemental distribution analysis, respectively. The TiO2 coating conferred photocatalytic properties to the membranes and protected them during 6 h of UV radiation exposures, reducing or eliminating chemical and morphological changes, and in some cases, improving their mechanical resistance. A selected commercial nanofiltration membrane was coated with TiO2 and used in a hybrid reactor with a low-pressure UV lamp, promoting photocatalysis coupled with cross-flow filtration in order to remove 17α-ethinylestradiol spiked into an aqueous matrix, achieving an efficiency close to 100% after 180 min of combined filtration and photocatalysis, and almost 80% after 90 min.

The use of agricultural waste to produce biofuel is challenging for waste management. This study investigated the biogas including methane production, and chemical oxygen demand (COD) removal efficiency by anaerobic digestion (AD) from mixed pineapple pulp and peel (MPP). Two-stage of anaerobic digestion system was configured as a continuously stirred tank reactor (CSTR) installed with an anaerobic hybrid reactor (AHR). Total solids (TS) of MPP loading at 4% (w/v) was used with four different hydraulic retention times (HRT) to investigate the subsequent effects, such as pH, alkalinity, biogas and methane production, and COD removal efficiency. The overall pH in CSTR was more acidic than the AHR system and exhibited less stability of the AD process by highly volatile acids. The highest biogas production (0.39 v/v-d) was obtained at HRT 7 with the biogas yield of 0.43 m3/kg COD removed and COD removal efficiency of 67.05% in the AHR system. The separated acidogenic and methanogenic stages in the two-stage system improved the digestion performance. The methane yields in the AHR system remained stable except for the lowest HRT condition (HRT5). Biogas production from pineapple wastes by two-stage anaerobic digestion systems was elucidated and could be applied for a larger digestion scale.