Reasonable Mechanism Research Articles

A feasible preparation of leaf like 3D dendrite MnxCd1-xS with photocatalytic hydrogen evolution

It is well known that both the size and morphology of semiconductor photocatalysts impact their performance. No template synthesis is the future trend. In this study, a series of MnxCd1-xS photocatalysts with a leaf-shaped three-dimensional (3D) dendrite structure was prepared by hydrothermal method without the addition of template agent and surfactant. The hydrogen production rate of leaf-like dendrite MnxCd1-xS was tested under visible light irradiation with Pt as co-catalyst. The highest hydrogen production rate was 1360 μmol g−1 h−1 and the highest apparent quantum yield (AQY) at 450 nm was 3.64%. In addition, the leaf-shaped MnxCd1-xS has good cycling stability and can be used repeatedly. Finally, a reasonable reaction mechanism was proposed based on the experimental consequences. This work provides a feasible strategy for the construction of MnxCd1-xS solid solutions with new morphologies.

Enhanced dissolution of galactomannan and highly efficient selenium functionalization using ionic liquids with dual roles as solvents and catalysts

Galactomannan stands as a promising heteropolysaccharide, yet its randomly distributed non-linear structures and high molecular mass remain a huge challenge in solubilization and wide range of chemical modifications. This work develops a task specific approach for efficient dissolve of galactomannan in ionic liquids (ILs) by destructing and reconstructing intermolecular/intramolecular hydrogen bonds of galactomannan. Combining density functional theory calculations and experimental results, a reasonable mechanism of polysaccharide dissolution is proposed that the hydrogen bond networks of polysaccharide are broken, thus the hydroxyl groups are fully exposed and activated to facilitate functionalization. In view of the enhanced solubilization, an excellent effect in selenylation of galactomannan is notably improved by employing ILs with dual roles as solvents and catalysts. Typically, the introduction of -SO3H in ILs (SFILs) effectively enhances the protonation ability of selenium donor and thus further improves the functionalization efficiency. Furthermore, a surprising finding is observed that selenium content and average molecular mass of functionalized polysaccharide can be manipulated by the anions-cations synergistic effect which is highly dependent on SFILs acidity strength. This work proposed an integrated and promising strategy for improving the solubilization and functionalization manipulating by ILs, showing a great referential value for the widespread application in polysaccharide-rich resources.

POMF: A Privacy-preserved On-chain Matching Framework

With the growth of the Internet, an increasing number of online matching platforms have emerged. However, current online matching platforms need to address three open challenges to improve user experience: (1) transparency and inherent issues with centralized platforms; (2) privacy concerns of users’ sensitive information; and (3) high service fees for matching services. In this paper, we propose a Privacy-preserved On-chain Matching Framework (POMF) that is suitable for a broad range of matching scenarios to overcome the challenges above simultaneously. In order to address the first challenge, POMF is constructed via the decentralized blockchain, based on which smart contracts are utilized to execute matching services automatically and publicly. To address the second challenge, we combine Order-Preserved Encryption (OPE) with Software Guard Extensions (SGX) to design a privacy-preserved on-chain matching mechanism that can enable information matching among different users in the encrypted domain, while revealing only order information and maintaining confidentiality. To address the third challenge, we optimize the OPE algorithm to reduce its computing and communication overhead, which further reduces the matching service fee. Besides, we ensure the fairness of POMF by designing a reasonable price mechanism that prices the contact information based on the matching degree between the involved matched users. Finally, we prove the availability of POMF via an comprehensive analysis and demonstrate the practicality of POMF by implementing a prototype and deploying it on a Fabric test network with extensive simulations.

Structural Optimization Design of Electromagnetic Repulsion Mechanism Based on BP Neural Network and NSGA‐II

The long‐stroke electromagnetic repulsion mechanism is subjected to large stresses during the driving phase, and the repulsion disc is prone to fracture due to excessive vibration amplitude up and down. Therefore, it is necessary to reduce the peak stress and vibration amplitude of the repulsion disc, improve the mechanical life, and improve the driving performance without decreasing the motion displacement, but it is not possible to do so at present. To address this problem, this paper takes the ‘coil‐repulsion disc type’ electromagnetic repulsion mechanism as the research object, and builds a simulation model of electromagnetic repulsion mechanism with structural strength and driving performance by using finite element simulation software, and analyzes the effects of four structural parameters, namely, the height of the repulsion disc, the inner diameter of the repulsion disc, the radius of the circular table and the radius of the chamfer, on the displacement and stress distribution of the model. After that, 39 sets of samples were output by BBD experimental design method, which were introduced into the BP neural network prediction model and combined with NSGA‐II algorithm to optimize the structure of the electromagnetic repulsion mechanism. The simulation results show that with the repulsion disc height of 14 mm, the repulsion disc inner diameter of 14 mm, the radius of the circular table is 29.78 mm and the chamfer radius of 7.06 mm, the peak stress of the repulsion disc of the electromagnetic repulsion mechanism is reduced by 57.83%, the amplitude of the repulsion disc is reduced by 3.24 mm, the peak electromagnetic repulsion force is increased by 7.52 kN and speed at the end of 3 ms increased by 9.8%. Under the condition of satisfying the constraints and increasing the overall displacement, the structural strength is increased and the driving performance of the mechanism is ensured to be improved, providing reasonable mechanism parameters for the opening and closing requirements of the fast mechanical switch. © 2023 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Constituent Attention for Vision Transformers

Multi-head self-attention (MSA) endows vision Transformers (ViTs) with the ability of modeling long-range interactions between tokens. However, recent works have uncovered that current arbitrary attention makes tokens distracted by extraneous dependencies, complicating the understanding of ViTs and hindering the overall optimization of ViTs. In this paper, we propose Constituent Attention (CA), a straightforward yet effective constraint on MSA to resolve aforementioned issues in different variants of ViTs with negligible overhead. Specifically, CA is designed to encourage the mutual attention between spatially connectable tokens via gathering such token pairs to the same group (termed constituent). Furthermore, with the layers going deeper in ViTs, small adjacent constituents are gradually merged into larger ones, exploring hierarchical structures in the visual objectives. Extensive experiments on four popular benchmarks demonstrate that CA assists the optimization of ViTs and contributes to significant performance gains especially at data-scarce scenarios. Moreover, the layer-wise reasoning mechanism aids ViTs in more consistent and progressive attention across different layers, rendering the inner workings easier to interpret. Our code is publicly available at https://github.com/zju-vipa/ConstituentAttention.

A study on the photophysical properties of strong green-fluorescent N-doped carbon dots and application for pH sensing

Color tuneable effective pH sensor in both acidic and alkaline medium is important for environment and bioanalytical purpose. In this report, natural biomass derived N-doped fluorescent carbon dots are utilized as pH sensor. The fast microwave irradiation method was employed for synthesis using natural sweet lime juice extract. Ethylenediamine (EDA) was used for nitrogen doping with different amounts. The prepared N-doped carbon dots are comprehensively studied by various characterization methods to analyse the effect of dopant concentrations on photophysical and luminescence properties. Improved thermal stability from 900 °C to 1000 °C with EDA content is observed. The fluorescence spectra of prepared N-doped carbon dots exhibited stable green emission with high quantum yield 83 % under ultraviolet and 440 nm irradiation wavelengths for an optimal concentration of EDA. The color of emission confirmed by CIE plot and about 3.47 ns decay time is found by PL decay curve. The anti-photo bleaching ability and good photostability for 10 days are found. The prepared N-doped carbon dots exhibit high ionic stability and bio compatibility. Further, pH dependent color tuneable (green to yellow) emission spectra of prepared N-doped carbon dots displayed high fluorescence in acidic medium at pH -5. Although, emission was quenched and red shifted in alkaline medium. The effective pH-sensitivity, and good reversibility of fluorescent N-doped carbon dots samples were tested with real water samples having different pH values. The reasonable mechanism is discussed. It depicts the prepared N-doped carbon dots have potential to serve as pH sensor for physiochemical and bioanalytical measurements.

Green composite aerogel based on citrus peel/chitosan/bentonite for sustainable removal Cu(II) from water matrices

Here, we propose a green and sustainable 3D porous aerogel based on citrus peel (CP), chitosan (CS), and bentonite (BT). This aerogel is prepared through a simple sol–gel and freeze-drying process and is designed for efficient capture of Cu(II) ions from water matrices. CCBA-2, with its abundance of active binding sites, exhibits an impressive Cu(II) adsorption yield of 861.58 mg/g. The adsorption isotherm and kinetics follow the Freundlich and pseudo-second-order models, respectively. In the presence of coexisting mixed-metal ions, CCBA-2 demonstrates a significantly higher selectivity coefficient (KdCu = 1138.5) for removing Cu(II) ions compared to other toxic metal ions. Furthermore, the adsorption of Cu(II) ions by CCBA-2 is not significantly affected by coexisting cations/anions, ionic strength, organic matter, or different water matrices. Dynamic fixed-bed column experiments show that the adsorption capacity of Cu(II) ions reaches 377.4 mg/g, and the Yoon-Nelson model accurately describes the adsorption process and breakthrough curve. Through experiments, FTIR, and XPS analyses, we propose a reasonable binding mechanism between CCBA-2 and metal cations, involving electrostatic attraction and chemical chelation between Cu(II) and the functional groups of the aerogel. CCBA-2 saturated with Cu(II) ions can be successfully regenerated by elution with 1 M HNO3, with only a slight decrease in adsorption efficiency (5.3%) after 5 adsorption–desorption cycles. Therefore, CCBA-2 offers a cost-effective and environmentally friendly material that can be considered as a viable alternative for the green and efficient removal of toxic Cu(II) ions from wastewater.

A task matching model of photovoltaic storage system under the energy blockchain environment - based on GA-CLOUD-GS algorithm

Photovoltaic storage system (PVSS) has been spawned with the combined application of photovoltaic (PV), energy storage (ES) and energy blockchain (EB), which has also made important contributions to the energy structure adjustment, energy transaction security and ecological environment protection. The establishment of a reasonable task matching mechanism can further improve the operation efficiency and quality of the system under the EB environment, and this paper consequently constructs a task matching model of PVSS based on GA-CLOUD-GS algorithm. Firstly, the decision-making committee is set up and the index system is determined for the to-be-matched task. Secondly, the Genetic Algorithm (GA) comprehensive weighting method is introduced to integrate the subjective and objective weights to achieve the weight optimization. Thirdly, the cloud model is used to obtain the preference order and priority order of the to-be-matched subjects. Fourthly, the Gale-Shapley (GS) algorithm is used to obtain the task matching results. Finally, the operability, the stability and the effectiveness of the model are separately verified through numerical simulation, sensitivity analysis and comparative analysis. Corresponding suggestions for the task matching of PVSS in the EB environment are also put forward according to the research content.

Ba0.5Sr0.5TiO3/BaFe12O19 magnetic separation photocatalysts: Structural, optical, microstructure, photocatalytic activity, degradation pathway and mechanism

The Ba0.5Sr0.5TiO3/BaFe12O19 (BST5/BFO) magnetic photocatalysts were constructed by a polyacrylamide gel route combined with low temperature heat treatment process. The effect of different BFO contents on the phase, surface microstructure, magnetic and optical properties, and photocatalytic efficiency of BST5/BFO magnetic photocatalysts was investigated. The BST5, BFO and BST5/BFO magnetic photocatalysts were evaluated for the degradation of tetracycline hydrochloride (TC) under simulated sunlight irradiation for 120 min, pH=5, catalyst content of 1 g/L, initial TC concentration of 50 mg/L and the photocatalytic efficiency trend followed the order: pristine BFO < pristine BST5 < BST5/20%BFO < BST5/15%BFO < BST5/5%BFO <BST5/10%BFO. The improvement of photocatalytic efficiency of BST5/BFO magnetic photocatalyst is mainly attributed to the synergistic effect of optical absorption coefficient, squareness ratio (SQR), interface charge transfer and separation efficiency due to the impurity defect and magnetic field induced the formation of oxygen vacancy, hole, hydroxyl radical and superoxide radical. The reasonable photocatalytic mechanism of BST5/BFO magnetic photocatalysts and possible intermediate products were elucidated in detail on the basis of the first principles calculation, capture experiment, radical verification experiment, magnetic data and liquid chromatography-mass spectrometry.

Implication of Renewable Heat Policy on Reducing Carbon Emissions in China: A Dynamic CGE Simulation

In 2020, China pledged to achieve carbon emission peaking before 2030 and carbon emission neutrality before 2060. Renewable heat is a key solution for decarbonizing the heating sector, which is responsible for more than 40% of global CO2 emissions. Policy interventions are necessary for scaling up renewable heat deployment due to both economic and non-economic barriers faced, while the instrument selection should be taken into account carefully. Thus, a dynamic computable general equilibrium (CGE) model was built to evaluate and compare the effects with different renewable heat policy shocks. The scenario analysis method is applied to compare two types of policies relative to baseline scenarios, subsidy, and energy tax. The findings indicate that: first, both subsidy and energy tax have positive effects on CO2 emission reductions while economic factors should also be accounted for. Secondly, the selection of subsidy and energy tax should seek a balance between economic factors and environmental factors as they may also affect economic growth or sectoral output to some degree. The energy tax rate should be moderate to avoid high economic impact. Thirdly, energy tax levying in the medium-long term has a beneficial impact on GHG emissions, while the instruments should be adopted with a careful rate chosen to avoid unnecessary tax burden on sectors that impede the orderly transition of relevant industries. Fourthly, it's reasonable to set a relatively high subsidy rate in the initial stage and gradually reduce the intensity of the renewable heating subsidy rate. For the energy tax rate, it is necessary to connect with the carbon trading market to set a relatively reasonable rate-setting mechanism to meet the dynamic needs of different stages.

URRNet: A Unified Relational Reasoning Network for Vehicle Re-Identification

With the continuous improvement and optimization of security monitoring networks, vehicle Re-Identification (Re-ID) becomes an emerging key technology in the development of intelligent visual surveillance systems. Due to the influence of viewpoint variation and fine-grained differences, vehicle Re-ID is still a research topic worth investigating. To alleviate above problems, a novel end-to-end framework named Unified Relational Reasoning Network (URRNet) is proposed in this paper, which integrates global features with local features to obtain better recognition accuracy. For the proposed framework, to understand the overall semantics of the image, an algorithm based on the global feature graph-structure learning is designed. The pixel-level feature maps are transformed to the node features of graph in the interactive space by projection, then graph reasoning is performed by using the graph convolutional network to improve the representation of global features. Moreover, an algorithm based on multi-scale local feature relational reasoning is designed. Using keypoint and viewpoint to obtain the multi-scale partial characteristics of the vehicle, and the vehicle multi-view features are learned from the single-view vehicle images through relational reasoning and attention mechanism. The two algorithms are combined to obtain the overall model, which not only preserves the details of the vehicle, but also effectively solves the problem of viewpoint variation. Comprehensive experimental results on two public datasets (VeRi-776 and VehicleID) indicate that the proposed URRNet can practically improve the model's representation ability and generalization ability, which is comparable to the state-of-the-art vehicle Re-ID methods.

Development Dilemma and Governance Strategy of County General High Schools in Guangxi

In recent years, the construction of a high-quality, balanced, universal and inclusive senior high school education system has been placed in a more important position, especially for the development of county general high schools, which has been emphasized more and more strongly. This paper analyzes the reality of social conflict in the development process of county general high schools in Guangxi from the perspective of social conflict theory, and finds that there are multiple problems such as resource allocation conflict, internal structural conflict and value conflict. Therefore, this paper proposes three paths to resolve and avoid the real conflicts in the development of Guangxi county general high schools by establishing a reasonable resource allocation mechanism, constructing a county education community, and improving the quality of county general high school education, which not only faces the real conflicts in the development of county general high schools, but also tries to solve the diversified problems of the resource allocation mechanism, the construction of teachers’ talent team, and the education and teaching community in the county education system.

Optimal Trading Mechanism Based on Differential Privacy Protection and Stackelberg Game in Big Data Market

Big data has become a fundamental resource and a commodity in economic activities, thus, it is necessary to build a market model capable of supporting efficient data trading. However, two major challenges remain. Firstly, researches have considered constructing data trading mechanisms, while few of them are based on the method of measuring data value in multiple dimensions. Secondly, a data market involved an intermediary trading platform (i.e., a third party) which is honest but curious, results may be obtained due the the leakage of private information. In this paper, we design TM-OUE, a data trading mechanism based on Optimized Unary Encoding that enables reasonable trading mechanism and protects the privacy of data trading. First of all, we combine qualitative and quantitative methods to measure the value of data in multiple dimensions and formulate data trading model between the data provider and data users. Then, we utilize an Optimized Unary Encoding (OUE) protocol to protect the privacy of the data trading mechanism. Based on the above steps, we develop a two-stage single leader multi-follower Stackelberg game to jointly maximize profits of the data provider and data users. Experimental results demonstrate that TM-OUE can offer appropriate price for data and maximize benefits both for data providers and data users, which guarantees fair data trades while protecting privacy.

Economic dispatch of generation load aggregators based on two-stage robust optimization

Introduction: In recent years, with the rapid development of renewable energy generation, the stability of the power grid has been greatly reduced. In response to this problem, integrating the user side transferable load into the power market has become the key to the development of future power grid. At present, large transferable loads have entered the electricity market in some pilot areas of China, but the relevant research on small and medium-sized transferable users entering the electricity market is still few.Methods: This paper proposes the concept of generation load aggregators. A two-stage generation load aggregator robust optimization model is developed to obtain the scheduling scheme with the lowest operating cost under the worst scenario. The model consists of distributed renewable power, transferable load, self-provided power, energy storage, etc. Uncertainties of renewable energy and load are introduced in the model. By using the column constraint generation algorithm and strong pairwise theory, the original problem is decomposed into the main problem and sub-problems to be solved alternately, so as to obtain the scheduling scheme with the lowest operating cost in the worst scenario under different conservatism.Results: The solved results are compared with those without the generation load aggregator, illustrating the role of the generation load aggregator in relieving peak and valley pressure on the grid from the load side, reducing the cost of electricity for loads, and promoting the consumption of renewable energy. The comparison with the deterministic optimization algorithm shows a significant decrease in the total cost and validates the performance of the selected solution algorithm. The boundary conditions for the use of energy storage by generation load aggregators for peak and valley reduction under the time-sharing tariff mechanism are also derived.Discussion: This study can provide reference for the investors of generation load aggregators when planning whether to install energy storage or the scale of energy storage, and also help the power market management department to design a reasonable incentive mechanism.

PSCFormer: A lightweight hybrid network for gas identification in electronic nose system

Based on their powerful feature extraction capability, a convolutional neural network (CNN) has been gradually applied to gas identification in the electronic nose (e-nose) system. The responses of different intensities in the e-nose system are significantly correlated, and CNN extracts the local gas features by convolution while ignoring their global correlation. Transformer combines different responses and obtains the correlation between global features by self-attention. This paper proposes a lightweight hybrid network called Peak Search-based Convolutional Transformers (PSCFormer). First, combining the data characteristics of gas information, the Local Peak Search and Feature Fusion (LPSF) module is proposed to focus on the key gas features. Second, Transformer Encoder (TE) is proposed to obtain the global correlation between global features, and the parallel Convolution Encoder (CE) is proposed to capture the local dependence. Finally, a reasonable feature complementation mechanism is presented, and the preference of TE is alleviated for the slow-down response while solving the receptive field limitation of CE. This paper has evaluated three different datasets to validate the effectiveness of PSCFormer, all of which show stable and excellent performance with a good tradeoff between efficiency and complexity. The results prove that PSCFormer is an efficient and lightweight gas identification network, which provides a method to promote the engineering application of the e-nose system.

Synergistical thiourea and thiosulfate leaching gold from a gold concentrate calcine with copper-ammonia catalysis

Thiosulfate leaching is a non-toxic and eco-friendly alternative method to cyanidation. However, thiosulfate leaching was used to leach gold from the gold concentrate calcine, and gold extraction effect was poor. To achieve effective leaching of gold, thiourea was added to facilitate gold extraction. This research not only investigated the leaching conditions and leaching kinetics but also discussed the potential reason and reaction mechanism of thiourea improving gold extraction. Gold extraction efficiency within 2 h was close to that of cyanidation (24 h) under the conditions: 0.2 mol/L thiosulfate, 0.12 mol/L thiourea, 5 mmol/L copper ion, 0.6 mol/L ammonia, 3 of liquid to solid ratio, and 308 K of leaching temperature. The gold in the leached solution was effectively recovered by the resin. According to the mechanism analysis, the gold in the leached solution existed in the form of gold(I) thiourea complex and gold(I) thiosulfate complex. The reason responsible for improving gold extraction efficiency lied in that inhibited the form of passivation layer and synergistically leached gold, and rapid leaching speed may be due to synergistical leaching. Thiourea is added in the thiosulfate leaching process, and offers a feasible, efficient, and fast leaching method for green development of the hydrometallurgy industry.

Desorption of sulfamethoxazole from polyamide 6 microplastics: Environmental factors, simulated gastrointestinal fluids, and desorption mechanisms

Microplastics (MPs) can enrich pollutants after being released into the environment, and the contaminants-loaded MPs are usually ingested by organisms, resulting in a potential dual biotoxic effect. In this paper, the adsorption behavior of Sulfamethoxazole (SMX) on Polyamide 6 (PA6) MPs was systematically investigated and simulated by the kinetic and isotherm models. The effect of environmental conditions (pH, salinity) on the adsorption process was studied, and the desorption behavior of SMX-loaded PA6 MPs was focused on simulating the seawater, ultrapure water, gastric and intestinal fluids. We found that lower pH and solubilization of SMX by gastrointestinal components (bovine serum albumin (BSA), sodium taurocholate (NaT), and pepsin) can reduce the electrostatic interaction between the surface charge of PA6 MPs and SMX. The result will lead to an increase in the desorption capacity of SMX-loaded PA6 MPs in gastrointestinal fluids and therefore will provide a reasonable mechanism for the desorption of SMX-loaded PA6 MPs in the gastrointestinal fluids. This study will provide a theoretical reference for studying the desorption behavior of SMX-loaded PA6 MPs under gastrointestinal conditions.

In Situ Growth of High-Performance ZnAl-Layered Double Hydroxides/Al2O3 Composite Coatings on Aluminum Alloy

In this research, high-performance ZnAl-layered double hydroxides (ZnAl-LDHs) with different Zn2+ concentrations were prepared on the surface of an anodized 1060 aluminum alloy using the in situ growth method, and the influence of Zn2+ concentration on corrosion resistance and tribological behavior was further explored. The surface morphology, element distribution, phase composition, and mechanical performance of ZnAl-LDHs/anodic aluminum oxide (AAO) composite coatings were tested and analyzed. Subsequently, the investigation of the anti-corrosion properties and tribological behavior of as-prepared composite coatings and AAO were conducted experimentally. The results show that with the increase in Zn2+ concentration, the thickness and bonding strength of the coatings gradually increase, and the hardness progressively decreases. The ZnAl-LDHs/AAO composite coating with a Zn2+ concentration of 0.3 mol/L exhibits the best anti-corrosion ability, which has the minimum corrosion current density of 2.435 × 10−9 A/cm2. This can be attributed to the uniform and compact ZnAl-LDH films where the porous structure of the AAO is well sealed. Moreover, the excellent friction-reduction and anti-wear properties of ZnAl-LDHs/AAO composite coatings with larger Zn2+ concentrations are verified using a ball-on-disc rotating wear tester under dry wear. A reasonable mechanism for improving tribological properties of resulting ZnAl-LDHs/AAO composite coatings is proposed.

Efficient activation of peroxymonosulfate by CoMg2Mn-LDO for the degradation of orange Ⅱ: The important synergy of Mg

Advanced oxidation process (AOP) based on peroxymonosulfate (PMS) has aroused extensive discussion in the degradation of organic pollutants due to the strong oxidative ability of SO4•−. Great attention has been paid to developing transition metal catalysts for PMS activation. Still, few studies focused on the co-catalysis effect of non-redox metals. To study the co-catalysis of Mg and develop a more efficient metal catalyst, the CoMg2Mn-LDO was prepared by a co-precipitation method accompanied by calcination. The material showed an excellent ability for PMS activation. 97.1% of Orange Ⅱ was degraded within 15 min with the reaction rate constant (kobs) of 0.539 min−1 when pH equals 6.7, the dosages of CoMg2Mn-LDO and PMS were 90 mg L−1 and 100 mg L−1, respectively. By contrast, the value of kobs was 0.375 min−1 for the system of Co3Mn-LDO/PMS at the same experimental conditions. The electron paramagnetic resonance (EPR) and quenching experiments results proved the existence of O2•−, SO4•− and HO• in the CoMg2Mn-LDO/PMS system and the dominant role of SO4•− in Orange Ⅱ degradation. The synergistic effects among Co, Mn, and Mg were found to be responsible for the outstanding catalytic ability of CoMg2Mn-LDO. The presence of Mg could not only promote the formation of Mg–HSO5− and CoOH+ complexes but also reduce the leaching of Co and Mn, which accelerated the generation of free radicals and decreased secondary pollution risk. Based on the overall analysis, reasonable activation mechanisms of PMS and possible degradation pathways of Orange Ⅱ in this reaction system were proposed. This work proves that Mg could be applied as an effective co-catalytic element and provides new insight into developing transition metal catalysts for PMS-based AOPs.

Authority-enterprise equilibrium based mixed subsidy mechanism for the value-added treatment of food waste

There is a huge amount of food waste worldwide and proper disposal can provide value-added products to the society. Food waste treatment requires the authority’s financial support because of its high costs and the treatment methods need to be further explored, but there is no effective approach to help the authority determine reasonable subsidy mechanisms and help enterprises to identify the technology application strategies. Therefore, a bi-level optimization model was constructed to find decision strategies that would satisfy both parties in the interaction between the local authority’s subsidy design and the food waste treatment plant’s identification of technology applications, where a mixed subsidy mechanism and technology integrations were considered. The proposed model was applied to a case study in Shanghai, China to investigate its feasibility and applicability. The influence of total amount of food waste and the related attitude of the local authority were analysed and discussed. Some management suggestions for different decision makers were proposed. It was found that while performance subsidies are preferred over transport and treatment subsidies, mixed subsidies are more favourable. Multi-technology integration facilitates the treatment plants’s profitability, and the share of technology application needs to be determined based on the actual. Food waste treatment systems can reduce carbon emissions while achieving energy self-sufficiency.