A lignosulfonate-derived iron–carbon composite catalyst was fabricated via hydrothermal pyrolysis and employed to activate peroxydisulfate (PDS) for tetracycline hydrochloride (TCH) degradation. The optimized LFC possessed a porous carbon matrix uniformly decorated with Fe0/Fe3O4/Fe2O3 crystals, providing abundant active sites for catalytic reactions. The LFC/PDS system achieved nearly 100% TCH removal within 30 min at neutral pH and exhibited high efficiency over a broad pH range, strong anti-interference ability, and good universality for various organic pollutants. Mechanistic investigation confirmed that TCH degradation was dominated by a singlet oxygen (1O2)-mediated non-radical pathway, with minor contribution from radical species. The synergistic effect of iron cycle and surface functional groups promoted the generation of reactive oxygen species and 1O2. This research provides a low-cost, eco-friendly and efficient strategy for antibiotic wastewater treatment.

Polychlorinated biphenyls (PCBs), as typical persistent organic pollutants, pose significant threats to ecosystems and human health due to their strong hydrophobicity, environmental persistence, and high toxicity. However, conventional adsorption-based removal methods are often limited by low adsorption capacity, poor selectivity, slow mass transfer, and inadequate reusability. In this study, a magnetic carbon porous cyclodextrin polymer (MCPCP) was rationally designed and synthesized via an emulsion templating method. By integrating the high specific surface area of porous carbon, the magnetic responsiveness of Fe3O4 nanoparticles, and the host-guest inclusion capability of β-cyclodextrin (β-CD), the resulting material exhibits enhanced adsorption performance and facile magnetic separation. The structure and adsorption properties of MCPCP toward eight PCB congeners were systematically investigated. Compared with the magnetic carbon porous polymer (MCPP), MCPCP showed significantly improved selectivity toward PCB118, PCB153, PCB138, and PCB180. The maximum adsorption capacity for PCB138 reached 954.63 mg/g according to the Langmuir model. Kinetic analysis indicated that the adsorption process followed a pseudo-second-order model, suggesting that chemisorption dominated the adsorption mechanism. These results demonstrate that MCPCP is a promising adsorbent for the efficient and selective removal of PCBs from environmental media.

For effective power system planning and scheduling, precision in photovoltaic power prediction is crucial as it allows for optimal resource allocation and operational efficiency. The research unveils a cutting-edge photovoltaic power prediction model established through the synergy of Variational Mode Decomposition (VMD) and a Multi-Strategy Enhanced Black-Winged Kite Algorithm (MBKA), which performs hierarchical optimization of the hyperparameters for a Convolutional Neural Network Long Short-Term Memory (CNN-LSTM) network model. Initially, VMD is utilized for signal dimensionality reduction. Subsequently, the MBKA, integrated into the model, employs an elite opposite learning strategy to refine the initial population quality. It enhances search efficiency by deploying spiral search and balances global and local searches via Levy flight. Moreover, to optimize the CNN-LSTM network model, the longitudinal and transversal crossover technique is incorporated into the model to boost accuracy and convergence speed. Finally, the MBKA is employed to optimize several key hyperparameters of the CNN-LSTM model, including the number of hidden units, training cycles, and learning rate. Specifically, compared to the VMD-BKA-CNN-LSTM model, the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) are reduced by 22.69% 25.39%, and 20.96%, respectively.

The loaded MoS2 co-catalytic Fenton systems have attracted wide attention in the field of pollution treatment recently, but the effect of the operation way of the system on the whole Fenton process was rarely reported. In this study, a partitioned reaction combined with intermittent addition of H2O2 was used to optimize the operation way of the co-catalytic Fenton reaction. Under appropriate conditions, the partitioned reaction degraded up to 80 % of sulfamethoxazole (SMX) after 24 reaction cycles. Compared with the hybrid reaction, the reaction rate constant and Fe2+/Fe3+ ratio in the partitioned reaction were increased by 10.3 and 210.0 times, respectively, and the iron sludge generation was reduced by 90 % and Mo leaching by 41 %. center dot OH radicals was the main ROS for SMX degradation in partitioned reaction. Besides, a partitioned external circulation reactor (PECR) was designed to confirm the long-term stability of this mode of operation. Notably, PECR maintained nearly 100 % SMX degradation for 20 days of continued operation, with high total iron concentration and low metal leaching. This study provides new ideas to improve the design of Fenton reactors in the future and provides technical guidance for large-scale treatment of wastewater by Fenton technology.

To solve the characteristics of photovoltaic (PV) power generation with uncertainty and instability, the article proposes a prediction model based on variational modal decomposition (VMD), improved sparrow search algorithm (ISSA), and long short-term time memory neural network ( LSTM) to enhance the accuracy of photovoltaic power prediction and optimize the power system scheduling scheme. The model first decomposes the power and inputs the decomposed subsequence into the prediction network, then optimizes the hyper-parameters of the LSTM model through ISSA, and finally outputs the prediction results. The experimental data verification shows that the algorithm proposed in the article has higher prediction accuracy and better performance in predicting Photovoltaic power.

Photovoltaic (PV) energy, a cornerstone of renewable power generation, is instrumental in driving the shift toward eco-friendly industrial practices. By harnessing solar power, it fosters a balanced and sustainable progression that benefits economic growth, social advancement, and environmental preservation alike. Accurate PV power generation forecasting can help power system operators plan ahead, reduce the use of backup power, lower operational costs, optimize power generation schedules, and enhance the grid integration capability and generation efficiency of new energy microgrids. In practical applications, methods from the field of deep learning are commonly used for PV forecasting. Among these, Long Short-Term Memory (LSTM) networks excel at short-term photovoltaic power prediction, offering distinct benefits when dealing with long-term dependencies in time series data while maintaining remarkable flexibility. Their architecture proves particularly adept at capturing complex, time-dependent relationships that simpler models often miss. However, LSTM's high computational complexity, sensitivity to hyperparameter selection, and high data quality requirements make it less suitable for long-term forecasting. To improve forecasting accuracy, a combination of Variational Mode Decomposition (VMD) and an improved Grey Wolf Optimization (IGWO) algorithm is used to optimize the LSTM forecasting network, along with a self-attention mechanism, to establish a short-term PV forecasting model based on VMD-IGWO-LSTM-ATTENTION. This model is compared experimentally with LSTM, VMD-LSTM, and VMD-IGWO-LSTM, and the model accuracy is assessed using multiple error indicators. The findings demonstrate the proposed composite model effectively enhances PV forecasting accuracy.

In this study, magnetic carbon nanopolymers (Fe3O4/C@PM) were synthesized by suspension polymerization using magnetic carbon nanoparticles as the matrix, 2-thiophene formaldehyde and acrylamide as the monomers, and ethylene glycol dimethacrylate (EGDMA) as the crosslinking agent. The obtained material was characterized using multiple techniques, including scanning electron microscopy (SEM), infrared spectroscopy (FTIR), X-ray diffraction (XRD), N2 adsorption–desorption, and thermogravimetric analysis (TGA). The adsorption effects of Zn2+, Cd2+, and Pb2+ in the mixed solution were evaluated using magnetic carbon nanoparticles (Fe3O4/C) and Fe3O4/C@PM as adsorbents. The adsorption isotherms, kinetic models, and cyclic regeneration of various metal ions, including Zn2+, Cd2+ and Pb2+, were studied. The results showed that the Fe3O4/C@PM maintained a slightly aggregated spherical morphology similar to Fe3O4/C and exhibited excellent adsorption capacity for all of Zn2+, Cd2+, and Pb2+, with maximum adsorption capacities of 343.3, 250.7, and 177.6 mg·g−1, respectively. The adsorption mechanisms were mainly based on the chemical interactions between metal ions and functional groups on the surface of polymers. The kinetic study revealed that the adsorption process followed a pseudo-second-order kinetic model. When Fe3O4/C@PM was reused five times, its adsorption rates for Zn2+, Cd2+, and Pb2+ remained above 81%, indicating its great potential for the treatment of wastewater containing Zn2+, Cd2+, and Pb2+.

Developing ultraviolet (UV), visible (Vis) and near-infrared (NIR) responsive photocatalysts for Cr(VI) reduction is valuable. Herein, a 0-dimensional/1-dimensional (0D/1D) S-scheme Ag2S/BiSI hetero-structured photocatalyst was successfully synthesized, which displays greatly enhanced Cr(VI) removal activity either under UV, Vis or NIR light irradiation. In-situ characterization technique and theoretical calculation confirm that an internal electric field (IEF), directing from Ag2S to BiSI, exists between the interface, which facilitates the spatial-oriented separation of photoirradiated carriers. Furthermore, the immobilization of Cr2O72- and the transformation from *Cr2O72- to *CrO3H2 on the surface of S-scheme Ag2S/BiSI heterostructure is much more favorable than that on the surface of single Ag2S or BiSI. This work gives a comprehensive insight on the design of full spectrum responsive S-scheme photocatalysts for heavy metal removal.

The activation of peracetic acid (PAA) to generate highly reactive species has emerged as a promising advanced oxidation process (AOP) for the degradation of refractory organic pollutants. This review systematically summarizes the recent advancements in PAA-based AOPs, encompassing various activation strategies, underlying reaction mechanisms, and applications across different environmental matrices. The activation methods are critically discussed, including direct energy activation, homogeneous catalysis, and heterogeneous catalysis. The generation process of diverse reactive species, like hydroxyl radicals (HO·), organic radicals (CH3C(O)O·, CH3C(O)OO·), and singlet oxygen (1O2), was introduced, and their oxidation selectivity and anti-interference ability were compared. Furthermore, the practical applications of PAA-based AOPs in treating wastewater, groundwater, and contaminated soil/sediments are reviewed. Finally, this review outlines critical challenges, including potential toxic byproduct formation, catalyst stability, and economic feasibility, and proposes future research directions to facilitate the transition of PAA-based AOPs from laboratory-scale research to full-scale implementation. This review provides insights for developing efficient, selective, and sustainable oxidation technologies, thereby contributing to the mitigation of emerging contaminant threats and the advancement of environmental remediation practices.

In the energy management of fuel cell vehicles (FCEV), the traditional fuzzy logic strategy has the problems of strong subjectivity and average vehicle economy. This paper proposes a composite fuzzy energy management strategy with the goal of improving the life of the auxiliary energy source power battery, using an improved pigeon swarm optimization algorithm (IPIO) to update the fuzzy membership function, while ensuring that the power battery works in a suitable range for a long time and reducing equivalent hydrogen consumption quantity. This paper conducts secondary development on the existing ADVISOR model to establish a simulation model of the FCEV hybrid system, and conducts simulation experiments under NEDC and CLTC-P operating conditions. The results show that IPIO's improved energy management strategy can charge more than twice as fast as the power following strategy when the initial SOC is low, and can reach the appropriate SOC range faster, which can extend the life of the power battery; when the initial SOC is high, the charging speed is more than twice that of the power following strategy. In this case, the equivalent hydrogen consumption of IPIO's improved composite fuzzy energy management strategy was reduced by 9.09% and 9.09% respectively in the two working conditions compared with the before improvement 11.8%, which significantly reduced the hydrogen consumption and improved the economy of hydrogen fuel cell vehicles.

Levofloxacin (LEV) residue is one of the key issues with livestock wastewater, posing a threat to aquatic ecosystems and human health. Herein, MoS2 sponge (MS) co-catalyst was synthesized using a simple impregnation method to construct a MS/Fenton system. Under suitable conditions, MS/Fenton could achieve 95.8 % LEV degradation in 30 min, with a reaction rate constant 9.75 times higher than that of Fenton. The results of the reactive oxygen species identification and material characterization indicated that the massive decomposition of H2O2 generated ROS (center dot OH and O-1(2)) and accelerated Fe2+ regeneration were the main factors for pollutant removal. MS/Fenton performed well in various aqueous matrices, reflecting excellent adaptability and anti interference performance. MS was structurally stable with minimal Mo leaching after the reaction. Furthermore, an external circulation packed-bed reactor was designed for application feasibility verification of the system. The system demonstrated excellent removal efficiency during 20 days of continued operation (without MS regeneration). In addition, MS/Fenton demonstrated a remarkable purification effect on real livestock wastewater. This study offered new insights for the large-scale preparation of recyclable co-catalysts, and the constructed long-acting and stable MS/Fenton system and reactor provide a reference for the green and efficient treatment of practical wastewater.

The misuse of antibiotics, such as tetracycline hydrochloride (TC), poses a severe threat to aquatic environments. Adsorption and degradation are effective methods for TC removal. This study developed nitrogen-doped magnetic carbon microspheres (N-Fe3O4@CMSs) using starch and Fe3O4 as precursors, with urea as the nitrogen source. Morphology characterization revealed uniform spheres with Fe3O4 particles attached. Nitrogen doping increased mesopores and carbon graphitization. Adsorption tests showed that N-Fe3O4@CMSs adsorbed up to 96.43 mg center dot g(-1) of TC, with a removal rate of 0.01445 min(-1). Adding K2S2O8 accelerated the rate to 0.1075 min(-1), achieving 98.35 % removal in 20 min. N-Fe3O4@CMSs exhibit exceptional TC removal efficiency, achieving over 73 % removal after 3 cycles. Mechanisms include adsorption and degradation, involving monolayer adsorption and reactive species generation. This novel material demonstrates adsorption, degradation, separation, and reusable capabilities. It has promising potential in removing antibiotics and other pollutants from aqueous environments.

Aiming at the problem of controlling the excess ratio of oxygen in the air supply subsystem of proton exchange membrane fuel cells.Firstly,a control-oriented fourth-order nonlinear dynamic model of the proton exchange membrane fuel cells system is established,and a fitting curve equation between the stack load current and the optimal oxygen excess ratio is constructed.Subsequently,a sliding mode controller using a new compound reaching law is designed,and the parameters in the sliding mode control are optimized and tuned using the sand cat swarm optimization algorithm.Finally,the improved sliding mode controller is simulated and verified,and compared with PID and other three sliding mode controllers.The simulation results show that when the load current of the stack changes,the improved sliding mode controller can adjust the driving voltage of the air compressor according to the cathode flow deviation parameter.At this time,the real-time oxygen excess ratio of the system will quickly approach the optimal oxygen excess ratio.The deviation between the two can be controlled within 0.1%,and the required average adjustment time and error performance indicators are better than those of the comparison group.

Carbon-doped MoS2-Fe (C-MoS2-Fe-x) was synthesized induced by the introduction of ethylene glycol using hydrothermal method. Benefitting from the synergistic effect of 1 T/2 H mixed phase and abundant defects, C-MoS2-Fe-x had an excellent ability to simultaneous remove enrofloxacin (ENR) and Cr(VI) via peroxymonosulfate (PMS) activation (C-MoS2-Fe-x/PMS). The most effective C-MoS2-Fe-2/PMS showed a removal rate constant of 0.200 min(-1) and 0.110 min(-1) for ENR and Cr(VI), which were 15.4 and 8.5 times as high as those of the MoS2-Fe/PMS, respectively. Combined with quenching experiments, electron paramagnetic resonance (EPR), and electrochemical experiments, singlet oxygen and electron-transfer can be illustrated for synergistic removal. C-MoS2-Fe-2 exhibits high mineralization capacity and is structurally stable in use with minimal metal leaching. It is noteworthy that C-MoS2-Fe-2/PMS displayed an outstanding purification effect on real pharmaceutical wastewater. This work provides new ideas for designing efficient and green non-homogeneous catalysts for Fenton-like systems to deal with composite pollution wastewater.

A novel rod-shaped MIL-88A(Fe)/BiOI heterojunction composite is fabricated by an in-suit chemical deposition method for visible-light-assisted peroxymonosulfate activation to eliminate AR18 (acid red 18). A series of x % MIL-88A(Fe)/BiOI are obtained according to the mass ratio of MIL-88A(Fe) to BiOI. Among them, 30 %MIL-88A (Fe)/BiOI could remove 97.79 % AR18 within 40 minutes. The reaction parameters on this process are investigated, such as PMS concentration, catalyst dosage, initial pH and dye concentration. The optimal conditions are determined to be [catalyst]= 1 g center dot L-1, [PMS]=1 mM, pH=7.02. The scavenging experiments and EPR analysis manifest that O-1(2) is the main active species for AR18 degradation. In accordance with the band structure, active species, XPS, PL, EIS and photocurrent response, the Z-scheme electron transfer path of the composite catalyst is proved under 500 W (lambda > 420 nm) Xenon lamp irradiation. In the end, the stability and universality of the composite catalyst in practical application are evaluated by three cyclic tests and inorganic anion experiments. This work provides valuable guidance for synthesizing efficient and stable MOF based heterojunction photocatalysts.

Manganese dioxide (MnO2) nanomaterials have shown excellent performance in catalytic degradation and other fields because of their low density and great specific surface area, as well as their tunable chemical characteristics. However, the methods used to synthesize MnO2 nanomaterials greatly affect their structures and properties. Therefore, the present work systematically illustrates common synthetic routes and their advantages and disadvantages, as well as examining research progress relating to electrochemical applications. In contrast to previous reviews, this review summarizes approaches for preparing MnO2 nanoparticles and describes their respective merits, demerits, and limitations. The aim is to help readers better select appropriate preparation methods for MnO2 nanomaterials and translate research results into practical applications. Finally, we also point out that despite the significant progress that has been made in the development of MnO2 nanomaterials for electrochemical applications, the related research remains in the early stages, and the focus of future research should be placed on the development of green synthesis methods, as well as the composition and modification of MnO2 nanoparticles with other materials.

Self-assembly broccoli-like cobalt nickel spinel via a one-pot hydrothermal method, and built NiCo2O4/PDS (NiCo2O4/PDS) system for highly effective ciprofloxacin (CIP) degradation within a wide pH range (3-10). Note that quick CIP removal (98.5 % removal in 15 min with 0.2 g/L NiCo2O4 and 1.00 g/L PDS dosage) was observed without pH adjustment (pH = 6.2) in the system with the highest reaction rate of 0.2677 min-1, which was 35.22, 2.47, and 3.36 times over that of MgCo2O4 (0.0076 min-1), Co3O4 (0.1085 min-1), CuCo2O4 (0.0797 min-1), respectively. DFT calculations found that the lowest PDS adsorption energy (-4.91 eV) of NiCo2O4 among MCo2O4 (M = Ni, Mg, Co, and Cu) was the major reason for the great catalytic performance. Quenching experiments implied that center dot OH and SO4-center dot were identified to be the dominant ROS for CIP degradation, while amperometric i-t experiments revealed that direct electron transfer between PDS and CIP also contributed to the CIP degradation via a non-radical pathway. The proposed degradation pathway of CIP was deduced according to the determined nine intermediates of CIP. This work provides a new perspective for designing highly efficient heterogeneous catalysts with broccoli-like structures and renders environmental remediation with cobalt nickel spinel possible.

To degrade the antiviral and antimalarial drug chloroquine phosphate (CQP), an oxygen doping MoS2 nano-flower (O-MoS2-230) co-catalyst was prepared by a hydrothermal method to construct an O-MoS2-230 co-catalytic Fenton system (O-MoS2-230/Fenton) without pH adjustment (initial pH 5.4). Remarkable CQP degradation efficiency (99.5 %) could be achieved in 10 min under suitable conditions ([co-catalyst] = 0.2 g L-1, [Fe2+]0 = 70 & mu;M, [H2O2]0 = 0.4 mM) with a reaction rate constant of 0.24 min-1, which was 4.8 times that of MoS2 co-catalytic Fenton system (MoS2/Fenton). Compared to MoS2/Fenton, the system had 1.5 times more Fe2+ (28.4 & mu;M) and showed a 24.0 % increase in H2O2 activation efficiency, reaching 50.0 %. The electron para-magnetic resonance (EPR) determinations and active species trapping experimental data revealed that & BULL;OH and 1O2 were responsible for CQP degradation. The combination of experiments and density functional theory (DFT) calculation demonstrates that O doping in MoS2 modifies the surface charge distribution, leading to an increase in its conductivity, thus accelerating the Fe3+/Fe2+ cycle and promoting reactive oxygen species (ROS) generation. Furthermore, O-MoS2-230/Fenton system exhibited excellent stability. This work reveals the degradation mechanism of accelerated Fe3+/Fe2+ cycle and abundant ROS in the O-MoS2-230/Fenton system and provides a promising technology for antibiotic pollutant degradation.

To utilize the chloridion in practical pharmaceutical wastewater and to minimize the negative impact of chloridion on the aerobic bacteria in the biochemical pool, a composite electrocatalyst consisting of CeO2 and CoFe2O4 loaded on electrospun carbon nanofibers (CeO2/CoFe2O4@C-NCNFs-800) was prepared and employed for NOR degradation in the heterogeneous electro-Fenton/Cl- (hetero-EF/Cl-) system. A superior NOR degra-dation efficiency was discovered in the hetero-EF/Cl- system than in the hetero-EF system, which benefited from the generation of more selective oxidants (ClO.) when hydroxyl radical (.OH) and Cl- were present simulta-neously. The 20 min operation allowed 99.54% NOR removal under the appropriate conditions (pH = 6.05, current = 40 mA, and [Cl-] = 0.1 M) with a reaction rate constant (kobs) of 0.3032 min-1. According to the quenching and the probe experiments, .OH, ClO., and singlet oxygen (1O2) were confirmed to be predominance during NOR degradation, whose steady-state concentrations were 2.00 x 10-11 M, 1.39 x 10-11 M, and 1.19 x 10- 11 M, respectively. In short, this study offered a probable method to utilize chloridion in practical pharmaceutical wastewater.

In this study, an effective flux-weakening control for permanent magnet synchronous motor (PMSM) is proposed, which combines model predictive control (MPC) with vector control. On the one hand, in order to achieve full-speed domain control, the optimal working point of the motor running is tracked and the reference current is calculated according to the feedback information in the speed control loop. On the other hand, MPC replaces the three PI controllers of the speed loop and the current loop in the traditional vector control, which not only does not need to set the PI parameters, but also improves the rapidness and accuracy of the speed control system. The results show that, compared with traditional vector control, the proposed control method has a great dynamic response and disturbance rejection performance in the full-speed domain.