Lignin is the most abundant renewable aromatic resource in nature and the basic aromatic units are linked by C—O and C—C bonds. Oxidative depolymerization can significantly reduce the chemical bond energy, and is particularly effective in cleavage of C—C bonds in the lignin structure, and generates highly functionalized high-value products such as aromatic aldehydes, acids and ketones. According to the cleavage of different bonds, the desired products can be prepared in a directional way, such as the cleavage of C _β —O bond is easy to produce phenols and ketones, the cleavage of C _α —C _β bond is easy to produce aromatic aldehydes and carboxylic acid products, and the cleavage of C _α —C_ary bond can effectively remove side chain alkyls. The article reviews the current state of research on the above three types of chemical bonds, focusing on the perspective of bond-breaking pathways, and also describes the research on catalysts for various types of chemical bond-breaking as well as progress in the oxidative depolymerization of real lignin. On this basis, the future research direction of lignin oxygen decomposition polymerization is prospected to realize the high-grade transformation of lignin.

Ionic liquids (ILs) and deep eutectic solvents (DESs), as a new type of green solvent, have received widespread attention from researchers in the separation of mixtures due to their unique physical and chemical properties, and therefore have gradually become a research topic in the field of green chemistry. For a specific separation process, it is very important to select the appropriate solvent. However, because of the variety and complex structure of ILs and DESs, it is time-consuming, laborious, costly, and almost impossible to find the optimal choice through experimental method. Therefore, it is necessary to screen ILs and DESs by applying theoretical calculation models. The conductor-like screening model for real solvents (COSMO-RS model) is a prediction model that combines quantum chemical calculations with statistical thermodynamic method. It can predict the thermodynamic properties of liquid mixtures without requiring experimental data and has been widely used by researchers as a rapid screening tool for various separation problems. In this work, the COSMO-RS model was used to screen ILs/DESs for the extraction and separation of phenols, nitrogen-containing compounds, sulfur-containing compounds, terpenoids, natural vitamin E in various oils, as well as CO₂ capture and azeotropic mixtures. The results showed that the COSMO-RS model was fast and effective for the screening of extraction solvents for specific mixtures. This paper can provide a valuable reference for the pre-screening of ILs/DESs in the separation process of hard-to-separate mixtures.

Cross-coupling reactions are efficient methods for building C—C bonds, C—N bonds, and C—O bonds. Heterogeneous catalytic reactions with organic polymers as catalyst supporters possess the advantages of recyclable catalysts and high efficiency. This article reviews the application of covalent organic frameworks (COFs) to form heterogeneous catalysts by loading metals in various cross-coupling reactions. The catalytic efficiency and catalyst cycle times are described in detail, and pointed out the problems and challenges in this field.

With the large-scale decommissioning of lithium-ion batteries (LIBs), the secondary hazards of used batteries to the environment have become an urgent problem, and the recycling of valuable metals has received widespread attention and research. This paper reviews the latest progress in LIBs recovery processes, analyzes and summarizes the problems existing in recovery processes such as pyrometallurgy and hydrometallurgy. We focus on comprehensively analyzing and sorting out the current status of mechanochemical (MC) recovery of valuable metals in cathode materials, including study of mechanochemical techniques for recycling lithium iron phosphate (LFP), lithium cobaltate (LCO), lithium nickel manganese cobalt ternary (NCM), lithium manganese oxides (LMO), and other cathode materials, which provide references to the progress of the recovery process of LIBs.

In response to the problems of poor nitrogen removal, high operational energy consumption and serious membrane pollution in membrane bioreactor (MBR) and the technical defects of poor effluent quality and ineffective utilization of electricity produced in microbial fuel cell (MFC), electrochemical membrane bioreactor (EMBR), which couples MBR and MFC treatment technologies, can compensate for the shortcomings of both technologies and can achieve efficient removal of pollutants while mitigating membrane contamination, and has broad application prospects. This paper classifies EMBR according to its structural characteristics, it focuses on the strategies to improve the performance of EMBR wastewater treatment from the perspectives of selection of constituent materials and optimization of operating parameters, and elaborates on the current research status of EMBR in wastewater treatment from the aspects of pollutant removal, electricity production performance and membrane pollution mitigation. Finally, it points out the problems and shortcomings of EMBR treatment of wastewater, and puts forward suggestions and prospects from the development and use of new materials, the scale of the device, the mechanism of membrane pollution mitigation, the structural composition of the microbial community and metabolic mechanism, etc., with a view to provide scientific basis for the realization of large-scale application of EMBR treatment technology.

Self-optimizing control (SOC) is a control system design method that achieves real-time optimization of chemical processes by selecting controlled variables. It has the advantages of simple control structure and good optimization effect, and has developed rapidly in recent years. This paper elaborates the fundamental principle of SOC and its role in the process control system. The historical developments and current research status of SOC are comprehensively surveyed, mainly including controlled variable solution methods, measurement screening algorithms, active-set change problems, SOC for batch processes, hybrid real-time optimization schemes, and so on. Finally, the applications of SOC to chemical processes are systematically reviewed, and outlooks on future developments of SOC are presented, from both theoretical and practical perspectives.

Organic Rankine cycle (ORC) has attracted much attention due to its ability to convert low-grade heat to electricity. One of the important tasks to promote the application of ORC is to find efficient and environmentally friendly working fluids to replace high-GWP (global warming potential) hydrochlorofluorocarbon (HCFC) and hydrofluorocarbon (HFC). In this article, a prediction model for the thermodynamic properties of ORC hydrocarbon working fluids based on graph neural networks (GNN) is constructed. GNN is used to learn the characteristics of molecular structure, and the combination of molecular structure characteristics and temperature is used to build a prediction model of molecular structure and properties using multilayer perceptron (MLP). The model is based on a training set of 2508 linear, cyclic, and aromatic hydrocarbons with carbon chain lengths ranging from 2 to 10. The obtained model achieves better prediction results than previous literature on predicting critical temperature, evaporation enthalpy and gas-phase and liquid-phase molar heat capacity. In addition, the resulting model was applied to predict the thermodynamic properties of over 430000 hydrofluoroolefins.

The basic thermodynamic data of each component in the complicated esterification system comprised of adipic acid, 2-ethylhexanol and trimethylolpropane were estimated by using group-contribution method, and the influence of temperature on standard enthalpy change, entropy change, Gibbs free energy change and equilibrium constant of these reactions was also investigated, the thermodynamic analysis results indicated that all the esterification reactions were endothermic and spontaneous processes under the specified temperature condition, increasing temperature is beneficial to promote the positive reaction. The kinetics of the esterification reactions of adipic acid and 2-ethylhexanol and adipic acid mono-2-ethylhexanol ester and trimethylolpropane catalyzed by stannous oxide were studied. The experimental results demonstrated that the two main reactions were both controlled by kinetics and which match the second-order irreversible reaction kinetics characteristics within a certain conversion range, the activation energy and pre-exponential factors of the reactions were determined as well, the established kinetic model can relatively accurately describe the synthesis process of complex polyolester.

High-temperature heat pumps have become a key energy-saving technology for low-temperature waste heat reuse because they can convert low-temperature waste heat into high-temperature thermal energy. To find a ternary zeotropic mixture suitable for the high-temperature heat pump, this paper proposes a comprehensive selected method that integrates considerations, including operating pressure, glide temperature, flammability, and energy efficiency. The results revealed that, with the optimal refrigerant selection, a ternary zeotropic mixture of CO₂/R600a/R1234ze(Z) with mass fraction of 0.1/0.1/0.8 is selected as the working medium for the high-temperature heat pump, resulting in a significant enhancement in performance. Under the specified conditions, the high-temperature heat pump system attains impressive performance metrics, including maximum coefficient of performance (COP_h) of 4.31, volumetric heat capacity (VHC) of 2766 kJ/m³, and exergy efficiency (η_ex) of 0.50. This study strongly advocates for the implementation of the high-temperature heat pump technology within the domain of low-grade industrial waste heat utilization. Through refrigerant selection, the high-temperature heat pump can effectively reclaim waste heat generated during industrial production processes, and making substantial contributions to the dual-carbon target.

In order to further improve the heat transfer characteristics of the flow boiling process and fundamentally solve the problem of premature drying out downstream, in this study, the short flow passage counter-flow microchannels (SFCM) is proposed and designed based on the concept of counter-flow microchannels by dividing the conventional parallel-flow microchannel (CPM) into two segments. The flow boiling heat transfer characteristics of deionized water are experimentally investigated at the mass flux of 118—219 kg/(m²·s) with inlet subcooling of 50℃, and the results are compared with the CPM. It is found that the critical heat flux (CHF) and average heat transfer coefficient (HTC_ave) can achieve a 160.6%—204.4% and 91.2%—115.4% enhancement, respectively. Meanwhile, compared with CPM, the pressure drop and pumping power of SFCM are reduced by 76.9%—80.4% and 44.9%—48.2%, respectively. More importantly, flow boiling instabilities can be effectively suppressed in SFCM.

As an important energy-saving component of the CO₂ refrigeration/heat pump system, the working ability of the ejector has an important impact on the improvement of system performance. Despite the structural simplicity of the CO₂ ejector, its internal flow is intricate and encompasses physical phenomena like non-equilibrium phase transitions, transonic and Mach waves. To this end, a homogeneous relaxation model (HRM) for two-phase flow of CO₂ was developed in this study, and the reliability of the model was verified by experimental data, from which a numerical study of the adjustable ejector was conducted to analyze the effects absence or presence of needle, needle position, and operating condition variations on the performance and internal flow of the adjustable ejector. The results demonstrate that the needle increases the irreversible loss of the primary flow and also alters the expansion state of the primary flow at the nozzle outlet. By adjusting the nozzle throat area through the needle, it improves the ability of the ejector to adapt to different operating conditions, so that the ejector maintains the optimal running state under different conditions. Consequently, compared with fixed ejectors, adjustable ejectors exhibit an average efficiency improvement of 10.74%.

The temperature, curvature of the vapor-liquid interface and the microscale heat transfer mechanism near the evaporating meniscus region have important effects on the accurate prediction of heat transfer performance of heat pipes. The heat transfer at the evaporation end of the trapezoidal grooved copper-water heat pipe was simulated by coupling the microscopic heat transfer in the evaporation meniscus area with the macroscopic area heat transfer. The effects of gas-liquid interface temperature, curvature and microscopic heat transfer in the evaporation meniscus area on the radial heat transfer coefficient at the evaporation end of the heat pipe were studied. The results show that effects of the curvature of the vapor-liquid interface and the adhesion force between solid-liquid molecules (disjoining pressure) on the interface temperature cannot be ignored. The heat and mass transfer in the micro region has significant influence on the apparent contact angle and in the macro region and the macroscale temperature distribution in the heat pipe wall. The temperature difference in the macro solid region is smaller if considering the heat and mass transfer in the micro region. If the vapor-liquid interface temperature T_iv is assumed to be equal to the vapor saturation temperature T_sat, the radial heat transfer coefficient may be greatly overestimated. If the vapor-liquid interface temperature T_iv is equal to the vapor saturation temperature T_sat, the calculated radial heat transfer coefficient is h_rad =7.8 W·cm^-2·K^-1, and a radial heat transfer coefficient h_rad =4.2 W·cm^-2·K^-1 can be obtained after considering the heat and mass transfer in the micro region.

This article focuses on the experimental study of convection heat transfer of supercritical carbon dioxide in mini-type heating tube with inner diameter of 0.75 mm under the different flow directions. The experimental results show that the local convection heat transfer coefficient has the same trends between horizontal flow and vertical upward flow when the system pressure, mass flow rate, heating power and inlet temperature remain constant, and the local convection heat transfer coefficient in horizontal flow is always higher than the local convection heat transfer coefficient in vertical upward flow. However, in vertical downward flow, the local convection heat transfer coefficient increases significantly with the increase of dimensionless temperature, and presents the best heat transfer effect at the maximum dimensionless temperature. Under the different flow directions, the local convection heat transfer coefficient increases significantly with the increase of mass flow rate, but decreases significantly with the increase of heating power and inlet temperature. However, in horizontal flow and vertical upward flow, when the fluid temperature is less than its pseudo-critical temperature, the local convection heat transfer coefficient decreases significantly with the increase of system pressure. The local convection heat transfer coefficient increases with the increase of system pressure when the fluid temperature is greater than its pseudo-critical temperature. When the fluid temperature is greater than its pseudo-critical temperature, the local convective heat transfer coefficient gradually increases with the increase of system pressure.

The application of microchannel boiling cooling for electronic devices has attracted much attention in recent years. An experimental study of the flow boiling in sintered microchannels was carried out, focusing on the effects of channel width on the flow boiling performance. Sintered microchannels were sintered by 150 μm dendritic copper powder by the pressurized sintering. Three types of parallel microchannels with channel widths of 1.8 mm, 0.6 mm, and 0.2 mm were prepared, corresponding to channel number, 11, 22, and 33, respectively. It was found that there exists the optimal channel width for the sintered microchannel, which could achieve the maximum heat transfer coefficient of 200 kW/(m²·K), and the largest critical heat flux of about 170 W/cm² at a flow rate of 4 L/h. Visual research found that the channel width has a great impact on the pressure pulsation curve. A moderate channel width pressure pulsation curve is more orderly, which greatly alleviates the pressure pulsation and thereby improves the boiling heat transfer performance of the microchannel.

In this paper, waste sponges were used as carbon material precursors, and a series of sulfonic acid functionalized carbon-based solid acids were synthesized through inert atmosphere carbonization and grafting of sulfonic acid groups, which were used for rapid pyrolysis of cassava residue to prepare LGO. The as-prepared waste sponge derived carbon-based solid acids were systematically analyzed by using various physicochemical characterizations, including X-ray diffraction (XRD), infrared spectroscopy (FT-IR), liquid nitrogen adsorption and desorption, and scanning electron microscopy (SEM), and so on, so as to identify the structural characteristics. The experimental results indicated that waste sponge derived carbon-based solid acid prepared at 500℃ and carbon-to-acid ratio of 1 g∶0.5 ml had rich porous structures and sulfonic acid groups, thus facilitating the selective pyrolysis of cassava residue into LGO. Under the catalysis of above mentioned carbon-based solid acid, the mass yield of LGO achieved 12.93% from cassava residue pyrolysis. This study presents a new idea for the resource utilization of waste sponges, which also promoted the application of solid wastes derived carbon materials for high-value transformation of agricultural and forestry wastes.

Direct electrolytic bicarbonate can avoid the energy-intensive step of CO₂ desorption, thus offering a promising route to convert CO₂ into value-added chemicals. It is an important task to find cheap and efficient electrolytic bicarbonate catalysts to replace noble metal catalysts (e.g., Ag). In this study, nickel-nitrogen-carbon (Ni-N-C) catalysts were introduced into the electrolytic bicarbonate system. Ni-N-C catalysts with abundant pore structure were prepared by anchoring Ni single atoms on active carbons, which provided abundant catalytic active sites and sufficient material transport channels for electrolytic bicarbonate. When operated in the N₂-saturated 3.0 mol·L^-1 KHCO₃ solution, the Ni-N-C catalyst obtained a Faraday efficiency for CO production (FE_CO) of 57.2% at 100 mA·cm^-2, while the Ag catalyst only obtained a FE_CO of 42% under the same condition. This study proves that Ni-N-C catalyst can replace Ag in the electrolysis of bicarbonate system to convert bicarbonate into CO.

In the industrial production process, ethyl acetate/ethanol/water ternary azeotropic system containing a large amount of water is often encountered. Extractive distillation is a common means to achieve effective separation of azeotropes. For the separation of ternary azeotropes with one large component content, the introduction of preconcentration can significantly improve the process economy. In this paper, conventional three-columns extractive distillation (TCED), four-columns extractive distillation with pre-separation (FCED), and three-columns extractive distillation process with one integrated distillation column with both preconcentration and solvent recovery functions (TCED-IDC) are established for the separation of ethyl acetate/ethanol/water ternary azeotropic systems containing large amounts of water. Following that, the processes proposed are optimized to minimize the total annual cost (TAC) by using genetic algorithms with penalty function. The economic optimization results shows that the TCED-IDC can save 27.1% of TAC and 29.7% of energy consumption compared with the conventional TCED process, and 9.9% of TAC and 13.0% of energy consumption compared with the FCED process considering preconcentration.

In order to solve the problem of the complicated process of downhole oil-water separation hydrocyclones connection in parallel, a new structure of multi-stage spiral separator is proposed based on the principle of tandem hydrocyclone separation. Response surface method combined with computational fluid dynamics is used to build a mathematical relationship model between the structural parameters and the separation efficiency of a multi-stage spiral separator, resulting in an optimal structural parameter, and systematically explored the optimal structural model within a certain range. The separation performance changes corresponding to different inlet flow rates, oil phase volume fractions and split ratios. Indoor separation performance experiments are conducted to verify the accuracy of numerical simulation results and the efficiency of optimization results. The results showed that the optimized structure could increase the separation efficiency from 91.0% to 96.2%. Comparison of separation performance at different inlet flow rates, the optimal inlet flow rate of 2.5 m³/h was obtained; within a certain range, with the increase of oil phase volume fraction and overflow split ratio, the separation efficiency showed a tendency of increasing and then decreasing, of which the simulated efficiency could reach up to 99.72%, and the experimental efficiency could reach up to 97.70%, which further verified the reliability of the simulation results and the efficiency of optimization results.

Neighborhood preserving embedding (NPE) is a commonly used unsupervised learning method and has been widely applied in fault detection. However, the features extracted by NPE cannot explain the relationship between input and output data, which limits its application in quality-related fault detection in chemical processes. Moreover, NPE ignores the representation of dynamic information while extracting data manifold structure. To address these issues, this paper proposes a quality-related fault detection method called twin-space parallel regression (TSPR) based on NPE and slow feature analysis (SFA) algorithm, which can simultaneously extract manifold features and velocity information. First, the original process space is divided into serial correlated subspaces and serial correlated subspaces based on mutual information strategy to deal with the differences in time series correlation caused by sensors. Secondly, the proposed neighborhood preserving-slow feature embedding (NP-SFE) algorithm and NPE algorithm are used to extract the effective structural features in two subspaces, and the regression relationship between process variables and quality variables is constructed by using least square regression in both feature subspaces to characterize the change trend of process variables and quality variables. Then, the covariance matrix of the regression coefficients is decomposed to obtain the quality-related subspace and quality-unrelated subspace, and monitoring statistics and control limits are established and estimated respectively. Finally, the proposed method is tested and verified on typical cases to illustrate the effectiveness and rationality of the proposed method.

For the heat exchanger network (HEN) with source/sink parameter variation, a systemic disturbance response/parameter adjustment method is proposed to maintain the heat balance of the system, identify the bottleneck restricting energy recovery and propose corresponding debottlenecking strategy. Based on topology analysis, feasible response objects and disturbance propagation paths of the system are enumerated, and the load-shift laws of heat exchangers are clarified. The relationship between heat exchanger thermal resistance requirement (R^req), area increment (∆A), total annual system cost (Ct) and heat capacity flow rate fluctuation coefficient (α) is derived. The thermal resistance demand change trend diagram and economic change diagram are constructed. With the optimal cost taken as the goal, the best response object is selected, and its heat load change value is determined. The system energy bottleneck caused by thermal resistance restriction during the adjustment of the response variable is located, and the area increment required to solve the bottleneck is determined. The proposed method can determine the change of the heating/cooling medium’s flow rate and that of each heat exchanger’s area demand under the disturbance state without complex simulation calculation, which is intuitive and efficient and can guide the design, optimization, or retrofit of chemical processes. A benzene alkylation process is analyzed to illustrate its application. When α locates in the interval [0.75, 0.88] and [0.88, 1.35], two heaters are the optimal response objects, saving the total annual cost up to 19400 USD∙a^-1 and 24024 USD∙a^-1, respectively.

The modeling of actual chemical processes has characteristics such as multi-variability, nonlinearity, and dynamism, which can lead to increased model complexity and the generation of redundant information and temporal distribution shift when extracting features. Therefore, an ordered neurons long short-term memory network (ONLSTM) model based on time series transfer and dual stream weighting is proposed. First, temporal transfer is used to match feature distributions to adaptively represent feature distribution information and training is performed by dividing the time domain with the largest difference in feature distribution to reduce timing distribution mismatch, thereby solving the problem of timing distribution drift. Secondly, a dual stream weighted ONLSTM model is embedded within the time series transfer framework, and the ONLSTM main forgetting gate and main input gate are weighted separately to more accurately control the transmission of information. Further combining the dual flow structure to design the corresponding gating unit for dual information flow control, reducing the coupling effect during parameter adjustment, reducing model complexity, and improving its predictive performance. Finally, the proposed model was applied to soft sensing modeling of SO₂ concentration in the sulfur recovery process and the flue gas emissions from a certain thermal power plant desulfurization process, and compared with other deep learning networks to verify the effectiveness of the model.

This paper proposes a flexible heat exchanger network model for multiple factories and periods, aiming to solve the problems of inflexibility and inability to adapt to changing production environments in existing heat exchanger network designs. The model consists of two sub-models: the first sub-model uses a multi-factory superstructure heat exchanger network model to solve the heat exchanger network structure for each period, and the second sub-model solves the multi-period heat exchanger network design for each factory with the annual total cost as the objective function. In each factory, all heat exchangers are shared and the network structure can be easily changed to meet the heat exchange demand by adjusting the logistics flow when the period or conditions change. The case test shows that the minimum total annual network cost is 210919.4 USD·a^-1, and 13 shared heat exchangers need to be installed, including 6 in factory 1, 4 in factory 2, and 3 in factory 3. The flexible heat exchanger network model proposed in this paper has the characteristics of high design flexibility and strong ability to respond to changes in production environments, providing industrial enterprises with a more intelligent and efficient heat exchanger network design method.

The scheduling optimization of large-scale maintenance tasks has extensive applications in practical production processes such as optimizing maintenance scheduling for coal bed methane wells, well repair operations scheduling, and fracturing operations scheduling. This problem is large-scale and difficult to solve, which is a difficulty and challenge for real-time scheduling optimization. A well-designed schedule for large-scale maintenance tasks is of significant importance for ensuring smooth production and reducing costs in oil and gas fields. To effectively address this issue, an optimization algorithm based on ALNS-TS has been proposed, and its effectiveness has been verified through cases of different scales. The experimental results demonstrate that the solving time for representative cases with 10, 50 and 100 maintenance tasks is 0.03, 8.33, and 74.32 s, respectively, providing reasonable scheduling solutions within minutes. As the problem scale increases, the ALNS-TS based algorithm outperforms traditional algorithms in efficiency and is capable of finding lower objective function values and optimal solutions.

The multimode characteristics of batch processes make the soft sensor model without considering mode factors have low prediction accuracy. The existing batch processes mode partitioning methods are sensitive to initial parameters and do not consider the influence of abnormal data on the mode partitioning results. The unreasonable partitioning results are an important factor restricting the improvement of the prediction accuracy of the multimode batch process soft sensor model. In this paper, a soft sensor method for multimode batch processes based on weighted destiny and similar label allocation density peaks clustering-relevance vector regression (WSDPC-RVR) is proposed. First, the local density of data points in low density areas is weighted according to the density contribution of different data points, the cluster center is accurately selected, and the ε-nearest neighbor is introduced to combine the distance between data points and the local density to construct an allocation strategy for the remaining data points. Then, the mode evaluation index is defined and the statistical characteristics of different modes are analyzed, and the abnormal mode discrimination strategy is constructed to obtain the number of effective modes and complete the mode partitioning of batch processes. Finally, the RVR soft sensor model of each effective mode is established to realize the online prediction of the dominant variables of batch processes. The simulation results of penicillin fermentation process show that the proposed method can achieve reasonable mode partitioning and effectively improve the prediction accuracy of the soft sensor model.

Hydrate-based solidified natural gas (SNG) technology provides a promising method for natural gas storage, but high-pressure production environment makes it difficult to separate and store the formed hydrate, causing difficulty in achieving continuous hydrate production. In order to promote its application, it is of significant importance to enhance the formation kinetics of hydrate, while hydrate efficient production, separation and storage are also anticipated. In this work, a novel spiral-agitated hydrate formation setup was proposed, and the integrated hydrate formation, separation and storage was fulfilled. Two nano promoters of —\mathrm{S}{\mathrm{O}}_{\mathrm{3}}^{-}@PSNS and —COO^-@PSNS were prepared via emulsion polymerization method, which enhance hydrate later formation kinetics, giving rise to hydrate efficient production. It was found that hydration efficiency under a mild condition of (5 MPa, 275.15 K, 30 r/min) was significantly enhanced by the synergictic effect of nano promters and spiral agitation, in the two nano promoter systems of —\mathrm{S}{\mathrm{O}}_{\mathrm{3}}^{-}@PSNS and —COO^-@PSNS, hydrate induction time is only 1.59 and 6.48 min respectively, while gas storage capacity in hydrate is up to 128.38 m³/m³. Compared with —COO^-@PSNS, —\mathrm{S}{\mathrm{O}}_{\mathrm{3}}^{-}@PSNS performs better on enhancing hydration efficiency. In addition, low energy consumption was required in the spiral-agitated hydrate formation setup, it takes 3.69×10^-2 and 6.81×10^-2 kW·h to form and separate 1 kg hydrate, and compared with —COO^-@PSNS, the energy consumption in —\mathrm{S}{\mathrm{O}}_{\mathrm{3}}^{-}@PSNS system can be saved by 45.81%. This study makes it possible to efficiently and continuously prepare hydrates, providing theoretical guidance for the application of solid natural gas technology in the field of natural gas storage.

The development of power battery thermal runaway propagation passive suppression technology is of great significance to solve the spontaneous combustion accident of electric vehicles in the static state. Existing passive technologies are based on thermal barrier mechanisms, but the resulting large thermal resistance will seriously affect the daily battery thermal management performance. This paper proposes a pseudo-passive power battery heat removal system based on pump drive cooling and thermoelectric conversion, which converts part of the heat generated by the battery system into electrical energy to achieve pseudo-passive heat removal. On this basis, it is combined with a thermal barrier to reduce the thermal resistance required to block the spread of thermal runaway. This article develops a test prototype, conducts experiments to analyze the heat removal process under different battery system heating power conditions, and explores the impact of heating power distribution. When the heating power is reduced by 33%, the steady-state values of dissipation in the cooling process of the pump drive, heat absorption in the thermoelectric conversion process, and electric energy generation are reduced by 30%, 27%, and 15%, respectively. The research in this paper will help to significantly improve the safety performance of electric vehicles.

Based on the composition characteristic of the syngas produced through supercritical water gasification of coal, a novel CO₂ near-zero-emission power system with integrated supercritical water gasification of coal with solid oxide fuel cell (SOFC) is proposed. Solar energy is used to heat the gasification chamber water supply and provide coal gasification reaction heat. The gasified syngas enters the SOFC to generate electricity. The exhaust gas from the anode of the SOFC is combusted with pure oxygen in the combustor of the gas turbine, and CO₂/H₂O mixture is produced. CO₂ can be easily separated and captured. The influences of key parameters such as coal-water-slurry concentration in the gasifier, working temperature of the SOFC, and reforming temperature on the system performances are studied. The distribution pattern, transfer and transformation mechanisms of the energy and exergy in the system are revealed. As the previously mentioned key parameters are 11.3%(mass), 1000℃, and 750℃, respectively, the power efficiency can reach 47.59%. This research achieves near-zero CO₂ emissions through the complementary cascade utilization of coal chemical energy and solar energy, combined with electrochemical reactions in SOFC and oxygen-rich combustion technology in the combustion chamber, which is of great significance to achieving the dual-carbon goal.

Under the national goal of “carbon peaking and carbon neutrality”, the carbon-free alternative utilization of fossil fuels has become very important. Metal fuels are a new type of carbon-free fuels, among which micron iron powder is considered to be the most potential metal fuel. However, the current understanding of the combustion mechanism of iron powder is still in its infancy. In order to study the combustion characteristics of single iron particle, a new type of iron powder burner was designed based on the principle of vibration-entrainment flow. It realizes the single iron particle supply and ensures its rapid combustion in a hot environment. The ignition and combustion processes of single iron particle with the diameter mainly distributed within 50 μm to 65 μm in the fuel-lean methane/air flame environment were investigated. It was observed that the combustion process of single iron particle was mainly divided into three stages: combustion retardation, normal combustion and product solidification. The combustion history of single iron particle was captured by using a high-speed digital camera, and typical combustion brightness anomalies were found. The sharp variation of the motion speed of iron particle was observed in the later period of combustion. In addition, the intermediate and final products of combustion were analyzed. It indicates that single iron particle melts in the initial of combustion, then the gas generates and expands during the combustion process, and the product particle bursts and becomes a hollow thin-walled sphere eventually.

Based on the flame spectroscopy diagnostic platform, a spectral imaging system was utilized to obtain the OH*, NH₂* and NH* radiation distributions of the ammonia/methane diffusion flame. The reaction mechanism was explored in the CHEMKIN. The results show that compared with pure methane combustion, the OH* radiation distribution zone and radiation intensity of the flame after ammonia blending are significantly reduced, and the distribution pattern extends outwards downstream of the flame. With the increase of ammonia blending ratio, the radiation distribution zone of NH₂* was raised to the downstream of the flame, and the radiation intensity increased. NH* radiation distribution zone was basically unchanged. The radiation intensity of NH* increased and then decreased with the increase of ammonia blending ratio. NH* radiation intensity reached the maximum when the ammonia fraction was from 0.2 to 0.3. The radiative intensity of the three radicals increased with the equivalence ratios, in which the distribution of OH* was biased toward the oxidant side, while NH₂* and NH* were biased toward the fuel side. With the addition of NH₂* and NH* reaction mechanisms, the simulation show that the main source of NH₂* was the dehydrogenation process of ammonia. The changes in the ammonia blending ratio directly affected the generation of NH₂*. The maximum production reaction of NH* indicated that the rate of the reaction generation of NH* was affected by the mixing ratio of ammonia and methane.

Based on electrical impedance tomography (EIT) technology, a membrane fouling in situ monitoring device with bilateral array electrodes was designed and applied to dynamic membrane fouling process monitoring. The electrode bilateral array method relies on the ion flow and external current to generate additional potential difference, which makes the monitoring more sensitive, and the correlation coefficient between the reconstructed image and the real image is 0.89, which enables more accurate information about the fouling to be obtained. Using kaolin, sodium alginate (SA) and lake water as model foulants, the different fouling characteristics of ultrafiltration (UF) membrane surface were explored, and flux changes and membrane fouling imaging were obtained. The results showed that kaolin was first concentrated near the inlet, and then migrated to the intermediate region and outlet, flocculated lake water was mainly distributed near the outlet, and SA was mainly concentrated in the inlet. The quantitative relationship between impedance change and the thickness was obtained by reconstructing images from EIT signals. The results showed that the rate of growth of impedance change values increased with increasing thickness.

The air-cooled proton exchange membrane fuel cell (PEMFC) has the characteristics of self-humidification, light mass, and simple system operation, and is suitable for use in fields such as drones. Hydrogen intake pressure plays an important role in the performance of the air-cooled PEMFC stack. Based on 1 kW air-cooled PEMFC stack, the influence of different hydrogen inlet pressures on the performances of the single cell voltage and distribution, output voltage and power of stack, and hydrogen utilization efficiency were considered. The experimental results indicate that the values of the single cell voltage, output voltage and power of stack are an upward trend with improving inlet gas pressure. Besides, the single cell voltage is in good agreement under high current. Moreover, increasing the inlet pressure decreased the hydrogen utilization while the experiment uses drainage method to collect exhaust gas and calculate hydrogen utilization rate.

The large amount of CO₂ emitted by the burning of fossil fuels contributes to global climate warming. CO₂ mineralization is one of the most effective technologies for CO₂ terminal emission reduction in recent years. CO₂ mineralization can use natural alkaline minerals or industrial alkaline solid waste for transforming acidic CO₂ gas into carbonate. Despite its promise, many reported CO₂ mineralization methods remain plagued by excessive energy consumption and cost. This study introduces an innovative, environmentally friendly, and energy-efficient air-driven membrane electrolysis technology, tailored for efficient CO₂ mineralization and the production of high-quality porous silica materials. The key advancement of this technology hinges on the simultaneous occurrence of the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) at the anode and cathode, respectively, within the electrolytic environment. This unique feature results in low-energy water ionization, generating both alkaline and acidic solutions. Crucially, this developed electrolytic technology demonstrates a substantial reduction in electrolytic voltage, at least 0.5 V lower than conventional electrolytic processes under equivalent current densities. By combining the acidic solution from the anode with a moderately alkaline solution from the cathode to dissolve wollastonite, the resultant mixture yields high-quality porous silica. Subsequently, the filtrate and remaining alkaline solution at the cathode effectively absorb CO₂, yielding calcium carbonate as the mineralization product. This breakthrough technology offers a compelling pathway to efficient CO₂ utilization through mineralization, addressing both environmental concerns and energy efficiency challenges.