Crystallization is an important technology for the separation and purification of materials. Currently, the parameters of crystallization processes are mainly monitored by off-line methods, which have some disadvantages, such as time lag and labor consumption. On-line monitoring based on process analytical technology (PAT) is of great significance for the optimization and control of crystallization, which can improve its production efficiency and product quality. In situ imaging technology can intuitively reflect the crystallization state, and the quantitative information provided by the image analysis algorithm can be used to study the mechanism such as crystallization kinetics. Although the analysis of in situ images is quite challenging, the recent AI technologies represented by deep learning have significantly enhanced the analysis accuracy. Following a brief introduction of some common PAT techniques for crystallization monitoring, this review summarizes the progress on in situ imaging technique with focus on the image analysis methods together with the revealed behaviors and mechanisms of crystallization. Finally, some future directions of in situ imaging technology are prospected for the intelligent monitoring of crystallization processes.

Lithium-ion batteries have gained widespread application in recent years due to their high energy density, low cost, and long cycle life, spurring rapid advancements in battery modeling. Compared to equivalent circuit models, physics-based models can provide high-precision predictions of battery performance under varying temperatures and operating conditions. However, the accuracy of these models is highly dependent on the precision of their parameters. Traditional invasive measurement methods are cumbersome and often fail to ensure sufficient accuracy. Consequently, parameter identification based on data such as voltage and current has emerged as a prominent research focus. This paper reviews the key steps of parameter identification of lithium-ion battery mechanism models, including model establishment, parameter sensitivity analysis and final parameter optimization.

Pressurized gas-solid fluidization has been widely applied recently. Computational fluid dynamics coupled with discrete element model (CFD-DEM) was used to investigate the effect of gas density on pressurized fluidization in terms of the minimum fluidization velocity, minimum bubbling velocity, bubble behaviors and pressure signals. Simulation results show that Group A particles exhibit a uniform fluidization regime across all pressure conditions, with the fluidization index increasing as pressure rises. In contrast, Geldart B particles consistently maintain a fluidization index below 1.1. Further, within Group B particles, an increase in gas density leads to a significant decrease in bubble size and a substantial increase in bubble count. Specifically, an 80-fold increase in gas density results in a 60% reduction in bubble size and a 2.5-fold increase in bubble count in a bed with 300 μm particles. However, in Geldart A particle beds, gas density shows almost no effect on bubble sizes or bubble count. Moreover, as gas density increases, both the standard deviations in the time domain and the amplitudes in the frequency domain of pressure drops decrease, with a more pronounced effect in Group B particle beds. Finally, the competition between gas-solid and solid-solid interactions is analyzed through particle collision forces and drag coefficients, which provides a reasonable framework for understanding the characteristics of pressurized gas-solid fluidization.

Particle material agglomerates are common in chemical processes. They often cause deformation and crushing due to internal interactions or collisions with reactors during transportation. Since these destructive processes occur over extremely short time spans, traditional experimental methods struggle to achieve effective observation. Numerical simulation tools, such as the discrete element method (DEM) and the finite element method (FEM), provide effective means to reveal such transient processes. Leveraging the strengths of both approaches, the combined finite-discrete element method (FDEM) has been proposed and applied in related research. This study employs an improved elastoplastic Timoshenko beam-bonded DEM model (referred to as the Shanghai Jiaotong bond model, SJBM) and an elastoplastic FDEM model to comparatively simulate particle collision and uniaxial compression processes. The results demonstrate that the SJBM model can more precisely capture stress concentration and evolution characteristics within particle systems, particularly revealing richer micro-mechanical details during dynamic deformation processes. FDEM ensures simulation accuracy while automatically transitioning material behavior and maintaining relatively low computational resource consumption. The comparison between these two methods provides a basis for selecting model tools to optimize more complex chemical processes and particulate processes.

The simulation of industrial-scale gas-solid particle systems always faces computational challenges. Coarse-graining methods, which group real particles into coarse-grained particle or parcel, improve the scalability of numerical simulations. As typical coarse-graining methods for gas-solid systems, coarse-grained discrete particle model (CG-DPM) and multiphase particle-in-cell (MP-PIC) each have their advantages. CG-DPM offers high simulation accuracy but is computationally expensive, while MP-PIC is faster but suffers from accuracy loss in dense systems due to simplified description of interparticle interactions. A coupled method based on domain decomposition, where CG-DPM is used in dense regions to maintain accuracy and MP-PIC is used in sparse regions to accelerate calculations, is proposed in this work. The accuracy and speed of the coupled method are validated in the simulation of bubbling fluidized bed, providing new insights into accelerated simulation methods for gas-solid particle systems.

Brick-built heat exchange chamber is a key equipment of tower zinc distillation furnace, which is mainly used for preheating incoming air and recovering flue gas waste heat. Due to the structural limitations of the brick-built heat exchange chamber, it has problems such as uneven gas velocity distribution and low heat transfer efficiency. Therefore, a brick-built heat exchange chamber of the zinc refining furnace is taken as the research subject in this paper, a comprehensive numerical study of the chamber is conducted by using CFD technology. Based on the field synergy theory, the evaluation is carried out by using indicators such as integral median synergistic angle, volume weighted average synergistic angle and comprehensive heat transfer enhancement coefficient, leading to the identification of an optimized structural solution. The study indicates that the uneven velocity distribution on the flue gas side is concentrated at the junctions of the heat exchange process, while the uneven velocity distribution on the air side is primarily observed in the bottom air ducts. Structural optimization should focus on the air ducts on the eastern side at the bottom layer. Expanding the air duct inlets can effectively enhance the uniformity of air flow within the chimney checkers, with the relative standard deviation reduced to only 17.5%, improving the overall performance of the heat exchange chamber. The optimal width for the air duct inlets on the eastern side at the bottom layer is 435 mm.

A laminar flow element with a guide cone and annular cross-section was designed to solve the problem of poor linearity in traditional laminar flow meters (LFM), and pressure-measurement position was directly put in the laminar flow section for further improving the linearity between pressure difference and flow rate. Using computational fluid dynamics (CFD) simulation technology to determine a reasonable guide cone angle is 30°. Analysis of the channel size reveals that it has a significant impact on the pressure difference in the measurement section, and the flow error decreases with the increase of the channel size. The applicability of laminar flow elements to different gases was explored using air, N₂ and CO₂ as working fluids, and the flow errors of the three were all less than 2%. By using CFD simulation technology to simulate the new laminar flow meter, detailed data on pressure loss along the flow channel and internal flow field can be obtained, which can provide useful flow details, feasible design ideas, and improve experimental efficiency.

For the increase alkali lignin solubility in choline chloride-lactic acid deep eutectic solvents (ChCl-LA) observed in the experiment when increasing the molar ratio of lactic acid, the intrinsic mechanism of the choline chloride-lactic acid molar ratio affecting the dissolution of alkali lignin in ChCl-LA was studied at atomic and molecular scales. Based on density functional theory, the electrostatic potential distribution of ChCl-LA, interaction and H-bond energy between choline chloride and lactic acid for different molar ratios of lactic acid were examined, and relationships between these factors and the capacity of ChCl-LA to dissolve alkali lignin were discussed. Using molecular dynamics simulations, interactions of lignin with lactic acid solvent and ChCl-LA with different molar ratios of lactic acid were investigated. The number of H-bonds, interaction energy, radial distribution function and spatial distribution function between each component of different ChCl-LA and LA solvent were calculated, and their effects on the process of lignin dissolution were analyzed. It was revealed that the choline chloride-lactic acid molar ratio affects the ability of ChCl-LA to form H-bonds with lignin and to catalyze the lignin depolymerization via the nature of active protons and H-bonds in ChCl-LA, resulting in its influence on the alkali lignin solubility in ChCl-LA. The above results provide theoretical support for regulating the ability of ChCl-LA to dissolve lignin, which is of great significance for the preparation and application of ChCl-LA and the green and efficient dissolution of lignin.

Thermal plasma technology shows great potential in the reforming reaction of CO₂ and hydrocarbon-rich gases due to its exceptionally high temperature, enthalpy, and electron density. In this study, numerical simulations were performed to elucidate the influence of feed ratios on the spatiotemporal evolution of species in the thermal plasma reforming system from both thermodynamics and kinetics and to predict the product composition. The simulation results indicate that the CH₄ and CO₂ reforming reaction is an ultra-fast process in thermal plasma, with complete conversion achieved within milliseconds. Owing to differences in bond dissociation energy, the dissociation of CO₂ is harder than that of CH₄, resulting in a lower formation rate of CO compared to H₂. Furthermore, as the CO₂ flow rate increases, side reactions such as CH₄ cracking are suppressed. Further experimental studies were conducted on the reforming behavior of CH₄ and refinery gas (containing CH₄, C₂H₆ and other hydrocarbons) with CO₂ in a thermal plasma reactor. The relationships were established between feed ratio, input power, and product composition. It was found that the predominant products of refinery gas reforming remained H₂ and CO. Under optimal conditions, the conversion rates of CH₄ and CO₂ reached 99.6% and 93.2%, respectively, with H₂ and CO selectivities of 83.7% and 98.3%. The above results provide a new idea for the synergistic conversion of refinery gas and CO₂ into high-value syngas.

Electrochemical ammonia synthesis seems potential to replace the traditional Haber-Bosch approach, owing to its more benign conditions, and quantitatively evaluating the whole process is especially desirable. Based on the lithium-mediated nitrogen reduction reaction (Li-NRR) and absorption-based ammonia separation, a complete process was modeled, simulated, and optimized with a 20-year operation cycle. The results show that the initial investment cost of the electrochemical method is much lower than that of the Haber-Bosch method, but the total cost is still higher than that of the Haber-Bosch method, of which the electricity cost of the electrochemical reaction accounts for more than 80% of the total cost. To make the electrochemical ammonia synthesis more practical, efforts should be made to increase the conversion rate and ammonia selectivity of the electrochemical reaction, and reduce the reaction voltage, in order to lower the operating cost of the process. Meanwhile, the content of precious metals in the electrochemical reactor should be reduced, or new alternative catalysts should be sought to further reduce the capital cost of the electrochemical reactor.

Methanol to aromatics is a feasible process to produce aromatics without using petroleum as feedstock, and the key to this process is developing high-performance industrial catalysts. This work builds a two-scale particle-resolved computational fluid dynamics model that describes transfer and reaction from industrial catalyst particle to packed bed reactor, considering the transfer process at the reactor scale would affect the overall performance of industrial catalysts. With this two-scale model, the effects of industrial catalyst structure on methanol to aromatics are investigated. The results show that the Raschig ring catalyst particles have a large bed void ratio and small diffusion restriction in the catalyst. Compared with other catalyst shapes, they have the lowest bed pressure drop and higher reactor outlet aromatics yield. Reducing catalyst particle size is effective in increasing the aromatic yield at reactor outlet, but significantly rises the pressure drop. The catalyst with 200 nm pore size and 0.5 porosity can effectively balance internal diffusion as well as catalyst amount and active site distribution, and thus its corresponding catalyst bed shows the highest aromatic yield at reactor outlet. These results in this work provide a powerful model and some important theoretical guidance for the development of industrial catalysts for methanol to aromatics.

A strategy for constructing a surrogate model for the global self-optimizing control (gSOC) problem was proposed. This strategy, tailored to the specific characteristics of the gSOC problem, integrates partitioned space design and a hybrid adaptive sampling method for sub-models, thereby improving construction efficiency. Based on this, the gSOC algorithm process was optimized by replacing inefficient process simulation software and accelerated the solution of the optimal combination matrix, thus extending the \mathrm{a}\mathrm{l}\mathrm{g}\mathrm{o}\mathrm{r}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{m}\mathrm{\text{'}}\mathrm{s} applicability to complex and large-scale processes. The improved algorithm was applied to the control structure design of a continuous catalytic reforming (CCR) unit. Using a reaction kinetic model comprising 27 lumped components, an Aspen dynamic model of the CCR process was developed. By integrating the improved gSOC algorithm with a simulation and heuristic integrated framework, the self-optimizing control structure of the CCR unit was systematically analyzed and designed, addressing key issues related to parameter uncertainty disturbances and faults, such as feedstock properties, recycle hydrogen flow rate, and reactor inlet temperatures. The results of dynamic simulation experiments show that the designed SOC structure exhibits significant real-time optimization performance. This research provides theoretical guidance for the control design of industrial CCR units.

Fluid catalytic cracking (FCC) disengager catalyst loss faults are complex, with multiple variables deviating from normal when occurring. These faults must be detected and mitigated promptly to ensure the long-term stable operation of the FCC unit. This study proposes an unsupervised run-off fault detection method (AEM) that integrates autoencoder (AE) and multi-scale symbol transfer entropy (MSTE), which fully considers the complex time dependency in time series data and the non-stationarity of the time series after the fault. The dual attention (DA) mechanism is incorporated into a long short-term memory (LSTM) network with an encoder-decoder structure. By applying the feature attention (FA) mechanism to assign weights to input feature variables, key features are dynamically emphasized, enabling the identification of the main fault variables. The temporal attention (TA) mechanism further enhances fault detection by assigning weights to capture dependency information at each time step along the time dimension. Additionally, a causal diagram is constructed for the nonstationary process using the MSTE method to reveal time delays between variables and eliminate indirect causal relationships. The effectiveness of AEM is verified by analyzing the perforation process of the fast-separating head of the settler, and the interpretability of the decision-making process is improved.

As the chemical industry develops towards intelligence, chemical reaction systems are frequently attacked by network attacks, resulting in serious consequences. Most of the existing industrial control security simulation research is conducted independently in the field of networks, lacking industrial control security simulation technology for chemical reaction systems. Therefore, in response to this issue, a simulation technology for industrial control safety virtual real fusion of continuous stirred tank reactor (CSTR), which is commonly used in chemical reaction systems, is proposed. Firstly, a CSTR control system model was established, and an industrial control security virtual real fusion simulation technology framework based on attack type analysis, attack simulation method, response analysis method, and attack monitoring and control method was proposed. Using the CSTR industrial control security simulation platform, attack simulation and response analysis for the CSTR system were implemented, and the proposed monitoring and control method for network attacks was verified, providing reference for promoting research on network security in the chemical industry.

To address the high loss of water-insoluble phosphorus in wet-process phosphoric acid, molecular dynamics simulations were employed to investigate the decomposition of phosphate rock at the microscopic level. This study established a two-stage molecular dynamics model based on the actual reactions of this process. The simulation results show that during the decomposition evolution of phosphate rock, \mathrm{H}\mathrm{P}{\mathrm{O}}_{\mathrm{4}}^{\mathrm{2}-} enters the CaSO₄ lattice to form eutectic phosphorus. This eutectic phosphorus embeds within the CaSO₄ crystals, entrapping phosphorus in the phosphogypsum and leading to phosphorus loss. CaSO₄ crystallization covers the surface of phosphate rock particles, and excessive CaSO₄ molecules encapsulate the phosphate rock, preventing its complete decomposition and resulting in precipitated phosphorus loss from unreacted phosphate rock. Furthermore, the effects of phosphoric acid and sulfuric acid concentrations on water-insoluble phosphorus (coprecipitated and precipitated phosphorus) were investigated. The results reveal that coprecipitated phosphorus decreases with increasing sulfuric acid concentration, while precipitated phosphorus reaches its minimum value at a sulfuric acid concentration of 3%.

Through molecular dynamics simulations, the underwater oleophobicity of dopamine-grafted zwitterionic trimethylamine N-oxide (DOPA-TMAO) was investigated and compared with that of dopamine-grafted sulfobetaine methacrylate (DOPA-SBMA) zwitterionic compound. The underwater oleophobicity of the DOPA-TMAO system was also explored under different salt concentrations. Simulation results show that, in terms of underwater oleophobic performance, the oil droplet contact angle of the DOPA-TMAO system is 20° higher than that of the DOPA-SBMA system, along with more hydrogen bonds. Compared with the DOPA-SBMA system, the DOPA-TMAO system exhibits superior salt-resistance, demonstrates stronger oleophobic performance under various NaCl concentrations. This could be attributed to the unique direct connection between the positive and negative groups in the TMAO molecule (without carbon chain spacing), which leads to significantly concentrated charge density at one end and stronger hydration capability compared with that of the SBMA molecule. Additionally, after grafting dopamine with zwitterions, the surface adhesion is significantly enhanced, with the surface adhesion performance improved by nearly 50% compared with that of the surface without DOPA grafting. Further investigation demonstrated that the catechol groups in DOPA significantly enhance surface adhesion performance through van der Waals forces and electrostatic interactions. This character combines with the hydration barrier function of TMAO to form an “anchoring-shielding” synergistic effect, ensuring stable oleophobic performance in the DOPA-TMAO system. Notably, the cooperative interplay between TMAO's superior hydration capability and salt-resistance mechanism guarantees consistent anti-oil properties even in high-salinity environments. Based on the mussel biomimetic strategy, this study successfully improved the stability of the zwitterionic surface in the underwater oleophobic process; and revealed the significant advantages of the new zwitterionic TMAO in oleophobic and salt resistance, providing a theoretical basis for its application in complex environments.

To tackle high regeneration energy consumption and underused low-grade waste heat in natural gas desulfurization-regeneration units, this study introduces a mechanical vapor recompression (MVR) heat pump distillation retrofit. A closed-loop system is designed where regenerator overhead vapor, pressurized via MVR, directly heats the reboiler, enabling waste heat upgrading and thermal self-balance. Using sensitivity analysis, response surface methodology, and NSGA-Ⅱ, a multi-objective optimization framework targets energy conservation, efficiency, emissions, and costs. Thermodynamic analysis identifies 320.0 kPa compressor pressure as a critical efficiency inflection point where waste heat recovery outweighs compression energy costs. Optimization results show: H₂S flow fluctuations ≤0.13%, regeneration energy consumption reduced by 39.86%, and carbon emissions down 30.66%, achieve annual operating cost savings of 546000 CNY, with a static investment payback period of 3 a. This scheme provides an innovative path for the low-carbon transformation of natural gas purification, with both economic and environmental benefits.

The influence of continuous-phase velocity pulsation on the generation and morphology of polymer droplets in microchannels is studied using three-dimensional direct numerical simulation. Based on the elastoviscoplastic Saramito model and the fluid volume method, combined with the local adaptive mesh refinement technology, the droplet generation process and morphological characteristics were analyzed. The results show that elastoviscoplastic velocity pulsation promotes droplet generation, and the maximum stretching length of the dispersed phase first decreases and then increases as the pulsation frequency rises. The pulsation amplitude shortens the stretching length of the dispersed phase. Under the influence of pulsation, the droplet morphology undergoes significant changes. When droplet velocity dominates, significant axial tensile stresses appear at the head and sides of the droplet. When the continuous-phase velocity dominates, the tensile stress on the sides of the droplet decreases significantly, and the droplet length is compressed. Furthermore, under velocity pulsations of the continuous phase, the average droplet length is adjustable between 102 μm and 193 μm. The average length and width of the droplets are controlled by pulsation frequency, with little influence from the pulsation amplitude.

Aiming to address the issue of low one-way conversion in traditional CO₂ hydrogenation to methanol, a new process of indirect hydrogenation of CO₂ to methanol by co-electrolysis coupling is proposed in this paper (Co-SOEC-CO₂tM). The process comprises a CO₂ capture unit, a co-electrolysis unit for syngas production, and a methanol synthesis and distillation unit. Based on the simulation data of the whole process, the utility engineering electrification transformation was carried out, and the technical and economic evaluation of the new process was carried out using element utilization, energy efficiency, CO₂ emissions, production cost indicators, etc., and compared with the traditional methanol synthesis process. The results show that the energy efficiency of the new process is up to 61.76%, which is significantly higher than that of other traditional processes. The hydrogen utilization rate of the new process is 70.99%, the carbon utilization rate is 80.84%, and the CO₂ emission can be as low as 0.197 t/t (MeOH), which is a significant advantage compared to other methanol synthesis processes. However, at the current renewable energy tariff of 0.35 CNY/kWh, the cost of the new process is high. With the vigorous development of renewable energy, when the tariff decreases to 0.1 CNY/kWh in the future, the cost of the new process can be reduced to as low as 1785.16 CNY/t (MeOH), making it economically feasible and advantageous.

The rectisol process has the problems of high operating energy consumption and insufficient CO₂ capture. In order to optimize performance and reduce energy consumption, a "two-stage reduced pressure flash coupled semi-lean liquid circulation" process is designed to reduce regeneration energy consumption while improving CO₂ capture efficiency. The results show that CO₂ production increases by 12.16%. Two "self-heat regeneration" optimization schemes are designed and their heat exchange network designs are carried out. The evaluation is carried out from several dimensions such as energy consumption, exergy loss, CO₂ emissions and annual operating costs. The results show that the two methanol scrubbing processes based on self-heating regeneration have improved scrubbing efficiency and optimized thermodynamic performance compared to the original process. Energy consumption is reduced by 36.98% and 37.20% respectively, and exergy loss is reduced by 26.72% and 26.86% respectively. Annual operating costs are reduced by 17.25% and 15.06% respectively, and unit CO₂ production cost reduced by 13.33% and 10.91% respectively. The improved rectisol process has better performance in terms of economy, energy conservation, emission reduction and environmental protection.

Batchwise distillation is widely employed in fine chemical, pharmaceutical, and food processing industries due to its operational flexibility and adaptability. However, its inherent non-steady-state characteristics and significantly varying operating conditions render traditional static models inadequate for accurately describing system dynamic behaviors, consequently leading to suboptimal separation efficiency of components within the column. To address this challenge, this study establishes a hybrid soft-sensor model (CNN-BiLSTM) integrating convolutional neural networks (CNN) and bidirectional long short-term memory networks (BiLSTM), specifically targeting the prediction of ethanol mass fractions in both distillate and bottom products of an ethanol-water binary mixture system. The model hyperparameters are systematically optimized through an improved snow ablation optimization (ISAO) algorithm, aiming to develop a reliable alternative to online measurement instruments for enhanced batch distillation control. The experimental results show that in the prediction of the mass fraction of distillate and bottom ethanol, the root mean square error and mean absolute error of the CNN-BiLSTM neural network after ISAO optimization on the test set are reduced by at least 82.27% compared with the initial model. This significant enhancement in dynamic prediction capabilities validates the proposed methodology's effectiveness in addressing the operational challenges inherent to batch distillation processes.

Chlorine gas is highly toxic and tends to diffuse along the ground after leakage. The non-uniform turbulent vortex structures often lead to inaccurate diffusion predictions, causing improperly designed safety measures and accidents such as personnel poisoning. In order to guide on-site rapid risk assessment, safety sign layout, emergency response and rescue, it is necessary to accurately predict the law of non-uniform diffusion of chlorine in large-scale dense scenes. This paper adopts the single-phase Eulerian and species transport equations, establishing a simulation and prediction method for non-uniform turbulent dispersion of high-risk chlorine gas based on the energy minimization multi-scale (EMMS) turbulence model. Taking the liquid chlorine release experiment of Jack Rabbit as the object, the simulation accuracy was verified and the non-uniform diffusion characteristics of chlorine gas under varying wind speeds, wind directions and leakage rates were investigated. The results show that the proposed simulation method effectively predict the non-uniform diffusion of chlorine gas in large-scale and high-density scenarios, with errors within 8%. Increased wind speed accelerates the diffusion of chlorine gas in open areas but has limited effect on the concentration distribution in the container-intensive areas. The wind direction deviating from the symmetry axis of the building causes the narrow tube effect, causing the local concentration to rise instantaneously. After the leakage increases, the high concentration area expands to form a barrier effect, and the area with a chlorine volume fraction of more than 0.045 increases by 36.6 %.

When industrial process operating conditions change, the data distribution of the new and old conditions is inconsistent, resulting in mismatch of the soft sensor model. Moreover, sample-scarcity of the current operating condition makes it difficult to accurately establish new soft sensor models. To address this issue, this paper proposes a domain adaptive broad learning system basal soft sensor modeling method based on parameter transferring to enhance model adaptability across different operating conditions. Under the framework of broad learning system, a learnable source-domain to target-domain parameter transformation mapping is designed to minimize distribution discrepancies and align the predictive output distributions of the target and source domains, facilitating the transfer of shared knowledge between domains. Regularization terms for output parameters, transfer parameters, and a maximum mean discrepancy-based distribution alignment regularization term are constructed to avoid negative knowledge transfer and overfitting in cross-domain soft sensor models. An alternating optimization algorithm for model parameters are proposed to achieve adaptive learning of output and transfer parameters. The effectiveness and accuracy of the proposed method are validated based on industrial penicillin fermentation and three-phase flow industrial processes. The results indicate that the proposed method demonstrates superior predictive accuracy and generalization performance compared to existing transfer soft sensor methods.

Aiming at the problem of energy waste caused by direct flare combustion of about 15000 m³/h (standard condition)impermeable gas produced by a large coal chemical plant as waste gas fuel, it is proposed to introduce solid oxide fuel cell (SOFC) thermoelectric system into the original coal-to-methanol system, and carry out research on coupling technology of coal chemical industry with SOFC and turbine power generation technology. The simulation software Aspen Plus is used to establish the process flow of SOFC coupling system for coal-to-methanol production. The influences of SOFC inlet temperature, current density, gas utilization rate and the circulation ratio of purge gas in methanol production process on the system power and efficiency are simulated, and the economic cost of the coupling scheme is calculated. The results show that compared with the original coal-to-methanol system, the non-permeate gas is recovered by 100%, of which 85% is used for fuel cell power generation. The system generates an additional 13000 kW of electricity, and the comprehensive energy utilization rate is increased by 2%. The system is superior in terms of efficient energy utilization and relieving the power pressure of chemical plants, providing ideas for the green transformation of the modern coal chemical industry and the commercial development of SOFC.

Mixed gas multistage membrane separation is an efficient separation technology, which achieves efficient separation of various components in mixed gas through the synergistic effect of multistage membrane system. However, optimizing its design requires establishing complex Mixed-integer nonlinear programming (MINLP) models, which are difficult to solve. This paper presents a global optimization method for multi-stage membrane separation systems for gas mixture. Using a decomposition algorithm, the complex MINLP problem is decomposed into a mixed-integer programming (MIP) problem and two nonlinear programming (NLP) problems. The separation sequences are enumerated via the MIP model, followed by the implementation of a multithreaded parallel computing approach where each thread sequentially optimizes the assigned sequences through two NLP models of distinct accuracy levels. The global optimal solution is determined by integrating all optimization results. Through a case study of natural gas sweetening, the total annual cost (tac) of the membrane separation system obtained is 7.35% lower than the optimal result in the literature. In addition, a case of CO₂ capture from blast furnace gas verifies that the method can be extended to the optimization of membrane separation system with variable pressure.

When fracture extension occurs in CO₂ pipelines, the influence of the decompression behavior of the medium inside the pipe on the process must be considered. Due to the high computational cost and convergence difficulty of the fluid-solid coupling method, this paper proposes a decoupling calculation method with partitioned load application, which can greatly simplify the complexity of the calculation of pipeline boundary conditions and reduce the computational time. This paper uses the shock tube model, decompression wave model and pipeline flap decompression empirical formula as the CO₂ decompression model, and applies pressure loads of different decompression forms to the crack tip and its front and back, respectively, to simulate the decompression behavior of CO₂ during the fracture process. At the same time, the model considers the influence of backfill and pipe deadweight on the fracture process, and adopts the structured grid transition technology to divide the grid, which greatly improves the calculation efficiency under the premise of ensuring the calculation accuracy. The calculated results of the model are compared with those of the burst test and the previous fluid-structure coupling model. The model can predict the initiation velocity better, and the peak velocity obtained is closer to the experimental value. The average fracture speed measured by the test is 108.21 m/s, and the average fracture speed calculated by the model is 114.18 m/s, with a relative error of 5.52%. The calculation results of this model reflect higher accuracy while considering conservatism.

With the widespread application of hydrogen as a clean energy source, its safety issues are increasingly valued. Due to the dangerous characteristics of hydrogen such as low density, high dispersibility and wide combustible range, it is easy to form a large flammable cloud after leakage, which may cause fire or explosion in case of ignition source, posing a serious threat to public safety. Conducting safety research on the diffusion pattern of liquid hydrogen leakage can prevent and reduce hydrogen leakage accidents, protecting people's lives and property. This study employs computational fluid dynamics (CFD) software Fluent, combined with the Lee model and the volume of fluid (VOF) model, to simulate the leakage and vaporization process of liquid hydrogen. The study finds that an increase in wind speed extends the downwind diffusion distance while reducing the vertical height. Based on the diffusion pattern of combustible hydrogen clouds and considering the limitations of hydrogen gas sensors, a new method is proposed to predict hydrogen concentration by monitoring environmental temperature changes using temperature sensors. By analyzing the mathematical relationship between temperature and hydrogen concentration during the initial leakage phase, a mathematical model is established to verify that the temperature sensors arranged on the 0.8 m height plane can quickly respond to leaks and improve the safety management level of hydrogen refueling stations.

As a renewable polymer compound with abundant reserves in nature, lignin has shown great application potential in the field of sewage treatment due to its unique structural characteristics and environmental friendliness. We review the preparation strategies, flocculation mechanisms, key influencing factors, and practical application challenges of lignin-based flocculants. Through chemical modification approaches such as graft copolymerization, amination, cross-linking, and sulfonation, the molecular weight of lignin can be effectively regulated, with functional group activity optimized, and spatial configuration tailored. As a result, the flocculation performance can be significantly enhanced. Flocculation mechanisms include charge neutralisation, adsorption bridging, and sweep coagulation. Flocculation efficiency is synergistically influenced by factors such as concentration, pH and temperature. Experimental studies have shown that lignin-based flocculants exhibit excellent performance in turbidity removal, dye removal, and heavy metal removal. For example, the removal rate of anionic dyes can reach more than 94%, and the removal rate of heavy metal ions (such as Cu²⁺, Pb²⁺) is close to 100%. Compared with conventional flocculants, lignin-based flocculants offer advantages of low toxicity and biodegradability. However, their practical application still faces challenges such as complex modification processes and potential residual toxic reagents. To promote large-scale application, further optimization of green modification techniques is required to balance performance requirements with environmental considerations, along with establishing efficient and sustainable synthesis pathways and application protocols.

The growth of the population and the advancement of industrialization have made the harmless treatment and resource utilization of industrial waste liquid a major challenge facing today's society. As a green, efficient, and environmentally friendly membrane separation technology, nanofiltration technology demonstrates great potential for industrial waste liquid treatment. However, in practical applications, traditional nanofiltration membranes are generally restricted by the "trade-off" effect between selectivity and permeability, as well as the problem of membrane fouling. In recent years, the introduction of nanomaterials with excellent physical and chemical properties into nanofiltration membranes has provided new ideas for solving the above-mentioned problems. This paper reviews the nanomaterials used in the preparation of nano-composite membranes, with a particular focus on the application of in-situ growth in the construction of separation layers or functional layers formed by nanomaterials in nanofiltration membranes. It elaborates in detail on its preparation strategies, structure regulation mechanisms, and performance optimization mechanisms, and introduces the application progress of the prepared nano-composite nanofiltration membranes in the treatment of industrial waste liquid. The aim is to provide theoretical guidance and technical reference for the design and preparation of high-performance composite nanofiltration membranes, and to promote technological innovation and industrial applications in this field.

With the annual increase in the output of organic solid waste, how to achieve its efficient treatment and resource utilization has become a research hotspot in the current environmental field. High-solids anaerobic digestion is regarded as the core technology to achieve the resourcefulness of organic solid waste, but faces problems such as system instability triggered by high solids loading and low gas production efficiency. Conductive materials are widely used in the field of high-solids anaerobic digestion of organic solid waste by virtue of their conductivity, pore structure and redox activity and other characteristics of regulating microbial metabolism and electron transfer. On the basis of existing studies, the enhanced effects of iron-based, carbon-based and iron-carbon composites on high solid anaerobic digestion were summarized, and the specific mechanisms behind the performance enhancement of the system by conductive materials were elucidated based on three perspectives: modulation of key enzyme activities, optimization of functional microbial communities, and enhancement of direct interspecies electron transfer. The potential application of machine learning models in the prediction of methane production efficiency and identification of key parameters is further explored, providing new ideas for the optimization of conductive material parameters. Meanwhile, the future research direction of conducting materials for enhanced high solid anaerobic digestion of organic solid wastes is also prospected.

Graphitic carbon nitride (g-C₃N₄), as a novel metal-free photocatalyst, has attracted considerable attention in the field of organic pollutant degradation due to its visible light response and environmental compatibility. However, its defects such as high intrinsic photogenerated carrier recombination rate, narrow spectral absorption range (<460 nm) and insufficient surface active sites lead to low photoquantum efficiency. By optimizing the band structure and directing the interfacial charge transfer, constructing heterojunction systems can significantly enhance the carrier separation efficiency and broaden the light response range. Compared with metal-based heterojunctions, g-C₃N₄-based metal-free systems not only avoid the risk of heavy metal leaching but also exhibit superior chemical stability. However, there is currently a lack of systematic reviews on the research of metal-free heterojunction materials composed of different types of metal-free materials and g-C₃N₄ in the photocatalytic degradation of organic pollutants in water. This paper reviews the structural characteristics, construction strategies, catalytic degradation efficiency, mechanisms, and properties of metal-free composite heterojunction materials formed by different metal-free materials with g-C₃N₄, such as carbon materials, black phosphorus, boron nitride, COF, perylene diimide (PDI), and carbon nitride. Finally, the challenges faced by current g-C₃N₄-based metal-free heterojunction composite materials are pointed out, and their future development prospects are discussed.

Carbonate-type brines are widely distributed in natural environments and industrial processes, where the development of novel resources and processes requires the supporting of systematic phase diagram and thermodynamic model. The alkali metal (Li, Na, K) carbonate brine systems represent typical and universal cases, necessitating supplementary phase diagram data to refine comprehensive thermodynamic models. This study first experimentally determined the phase diagrams of the Li₂CO₃-K₂CO₃-H₂O system at 273.15, 323.15 and 348.15 K to address data scarcity. Subsequently, on the basis of improving the thermodynamic models of the three binary systems of Li₂CO₃, Na₂CO₃ and K₂CO₃, the multi-temperature isobaric molar heat capacity parameters of the CO{}_{\mathrm{3}}^{\mathrm{2}}^- ion were re-obtained. Multi-temperature thermodynamic models were developed for three ternary systems: Li₂CO₃-Na₂CO₃-H₂O, Li₂CO₃-K₂CO₃-H₂O and Na₂CO₃-K₂CO₃-H₂O. All the multitemperature liquid-phase characteristic parameters of the Li⁺, Na⁺, K⁺ and CO{}_{\mathrm{3}}^{\mathrm{2}}^--H₂O systems (interaction parameters between three groups of ion pairs and water, and among three groups of ion pairs) and thermodynamic parameters of nine solid-phase species were obtained. The complete phase diagram structure of the ternary system was predicted. For the Na₂CO₃-K₂CO₃-H₂O system with poor consistency of phase diagram data, the judgments of the stable equilibrium phase regions of various salts were given. The results show that the obtained thermodynamic parameters are reasonable and thermodynamically consistent in expressing the solution properties and solid-liquid phase equilibrium laws of the carbonate brine system, which can meet the requirements of calculation accuracy.

In alkaline water electrolyzers, the generation and coalescence of gas bubbles on the bipolar plates will change the flow pattern of electrolytes and affect the velocity and temperature fields of the electrolytes, leading to local overcurrent and hot spots, further reducing the overall electrolysis efficiency. The gas-liquid two-phase flow state in the plate channel is simulated by the level set coupled volume of fluid (CLS-VOF) numerical technique. The generation, growth, and detachment of individual bubbles on the surface of the bipolar plate and the coalescence between bubbles are investigated in detail. The effects of current density, electrolyte flow rate, and cross-sections of channels on the gas content, surface gas coverage, and pressure drop in the polar plate channel are explored. The results showed that the bubble size, gas content, and surface gas coverage increase with the increase of current density and decrease with the growth of electrolyte flow rate.

The study on the influence of electric field on the diffusion and combustion characteristics of small-scale jets can provide guidance for the design of high-performance micro-power devices. A small-scale jet diffusion flame experimental platform for biodiesel-air is built to investigate the effects of positive and negative uniform electric fields on the flame stability range, flame height and width, and frequency of flame explosion. In addition, the effect of electric field on the depth of liquid interface inside the capillary is studied using visual methods. The results show that when an external electric field is applied, the lower and upper combustion limits of the flame increase and decrease respectively, and the effect of the reverse electric field is more significant than that of the forward electric field. As the voltage increases, regardless of whether a positive or negative electric field is applied, the frequency of flame explosion decreases, and the depth of liquid interface during stable combustion increases. When a positive electric field is applied, the height and width of the stable flame increases and decreases with increasing voltage, respectively, with the maximum variation amplitude of 10.18% and 11.14%. When the electric field is negative, it decreases and increases, with the maximum amplitude of change being 7.28% and 17.02%, respectively.

In order to reduce the safety risk in the preparation and production of high polymer bonded explosives (PBX) and promote the continuous and large-scale production of PBX explosives, five different ratio of polymer bonded explosives were designed with non-aluminum-containing PBX substitutes as the research object. The calculation model of the heat transfer coefficient between barrel/screw and material based on the change of physical property parameters, structural parameters and operating parameters is derived and established. At the same time, the direction of heat conduction in the screw metering section during the actual extrusion process and the contribution ratio of heat conduction to the temperature rise of the material were discussed. The results show that: The heat conduction is dominant in the heat conversion in the metering section of screw. Especially in the material system with energetic oxidizer∶aluminum powder 6∶2, the heat transfer of the cylinder in the metering section is more than 10 times the viscous heat generation. The heat transfer coefficient calculation model established in this paper is more comprehensive, and the calculated results are between the results of earlier heat transfer research theories. Under the same experimental conditions, the absolute error between the theoretical exit temperature predicted by this model and the experimental measured value is within 0.2℃, and the predicted temperature rise error is within 20%.

To optimize the oscillating flow field formed by the vibrating blade (VB) and improve fluid mixing and comprehensive heat transfer performance, a coupling structure of a vibrating blade with a flexible plate (VBFP) was proposed. The mechanism of fluid mixing and heat transfer enhancement is revealed through experiments, numerical simulations and chaos analysis. The results showed that the VB induces periodic vortex shedding and breakdown, forming a high-velocity oscillating flow with chaotic characteristics, which promotes chaotic mixing of the fluid. However, the uneven vortex distribution results in weaker heat transfer in the central region. Driven by the oscillating flow, the passive oscillation and deformation of the flexible plate induce secondary and near-wall vortices, generating a secondary high-velocity flow that enhances nonlinearity and energy cascade effects. This process further strengthens chaotic mixing and improves heat transfer performance. Compared to the smooth channel, the VBFP reduces the time-averaged maximum temperature(T_max,av) by 16.7℃, improves the time-averaged Nusselt number (Nu_av) by 69.1%, and ultimately enhances the comprehensive heat transfer performance factor (η) by 42%. Additionally, for comparable maximum temperatures, the VBFP reduces power consumption and noise by 6.4 W and 20 dB, respectively, offering significant energy-saving and noise-reduction advantages.

Polypropylene accounts for about 25% of plastic waste, and its selective conversion into high-value aromatic feedstocks is crucial for promoting a circular economy and achieving carbon neutrality. Although metal-zeolite catalysts have been shown to promote the catalytic conversion of polyolefins to aromatics, the reaction path of polypropylene cracking on the outer surface of molecular sieves and the effect of metals on the cracking reaction are still unclear. Here, metal-zeolite catalysts with selectively exposed external surface sites were designed to investigate the catalytic cracking behavior of the key intermediate 2,4-dimethyl-1-heptene on the catalyst's external surface. The results show that metals can significantly enhance the cracking degree of branched olefin intermediates on the zeolite external surface, leading to the diffusion of small olefin molecules into the zeolite micropores, where further aromatization occurs. This process improves the utilization of aromatization sites within the micropores. Under optimized conditions, the yield of aromatics from the catalytic conversion of polypropylene reaches 73%, with a sum yield of benzene, toluene, and xylene of 65%. This study establishes a relationship between the structure of metal-zeolite catalysts and the cascade polypropylene-to-aromatics process, offering valuable insights for designing highly efficient catalysts for the chemical recycling of polypropylene into aromatics.

In oil-water coalescing filtration, it is crucial to clarify the liquid distribution in the filter and pressure drop evolution for investigating the filtration mechanism and optimizing the filter structure. The liquid distribution characteristics and pressure drop evolution in filters with different pore sizes were examined. The effects of filtration velocity and loading rate on filter saturation and pressure drop were also evaluated experimentally. The results show that the liquid distribution and pressure drop changes during oil-water separation conform to jump-channel model. However, due to the presence of the liquid pool, an abrupt change of pressure drop occurs at the initial stage of the channel stage. The pore size determines the amount of liquid entering the filter, which in turn affects the liquid behavior and pressure drop variations. As the filtration velocity increases, the saturation in the large-pore filters gradually decrease, but the rate of decline gradually weakens. Meanwhile, the jump pressure drop gradually increases, while the channel pressure drop remains relatively stable. In contrast, the saturation in small-pore filter exhibits the opposite behavior. As the loading rate increases, the saturation of the large-pore filter, the jump pressure drop and the channel pressure drop increase. For the small-pore filter, as the loading rate increases, the saturation has a slight change, the jump pressure drop remains almost unchanged, but the channel pressure drop increases significantly. Finally, a prediction model for the liquid distribution in the filter was established, which can be used to quantitatively characterize the relationship between the channel saturation and the pore size, filtration velocity, and loading rate. This study provides a theoretical basis and technical support for optimizing the structure of the filter and the operating parameters, as well as reducing the maintenance costs.

Crosslinked polyethylene oxide (PEO) is one of the hot membrane materials currently used for CO₂ capture. However, a large number of hydroxyl groups are generated in the process of forming cross-linked PEO based on epoxy ring-opening polymerization, resulting in abundant hydrogen bonding between molecular chains, thereby reducing chain mobility, increasing the permeation resistance of gas molecules, and making the permeability of membrane materials unsatisfactory. In order to improve the CO₂ separation performance of crosslinked PEO membranes, 18-crown-6 (C6) small molecules are introduced into the PEO crosslinking network, forming a homogeneous mixture. Utilizing the cavity structure of C6 molecules and their interference with the hydrogen bonds between PEO molecular chains, both CO₂ adsorption and diffusion processes are facilitated. The CO₂ permeability is increased to 4.2 times that of the PEO membrane (636 Barrer), while maintaining a high separation selectivity (about 50), and the membrane performance remains stable during 300 h of continuous testing.

In this study, the UNIFAC method was employed in Aspen Plus to develop a vapor-liquid equilibrium model for the trioxane system. The model demonstrates high accuracy when temperature ranged from 343 K to 423 K, with formaldehyde concentrations below 65%(mass) and trioxane concentrations below 80%(mass), achieving a relative a0age deviation of less than 9.15%. The density, viscosity and phase change enthalpy of the system are fitted and estimated at the same time, and the maximum relative average deviation is no more than 8.17% compared with the literature value. Based on this model, the concentration column for trioxane production processes was designed and optimized, and the effect of feed methanol on the trioxymethylene concentration tower was discussed. The results indicated that the presence of methanol increases the energy consumption of the concentration column. Furthermore, a hydraulic verification of the concentration column was conducted to ensure its design integrity.

High energy density fuel is the core energy of aviation propulsion system, and the molecular structure design and composition optimization of fuel can significantly improve the range, load capacity and overall performance of aircraft. Photochemistry provides a green process for the synthesis of tensile structure fuels and multi-ring structure fuels, but it faces problems such as low efficiency of photogenerated charge separation and poor reaction performance. In this work, the photocatalytic [2+2] cycloaddition of norbornadiene and cyclohexenone mixed system was studied. The multi-component mixed fuel was synthesized by adjusting the reaction path to balance the contradiction between fuel density and freezing point. The synthesis of tetracycloheptane via intramolecular photocycloaddition of norbornadiene is promoted by photocatalysts and cyclohexenone sensitization. Compared with ZnO, ZnO/WO₃ heterojunction photocatalyst inhibits the formation of excited triplet cyclohexenone, and then inhibits the intermolecular [2+2] cycloaddition reaction process involving cyclohexenone. The fuels with different components are obtained through hydrodeoxygenation refining. When the mass ratio of QC/1-adduct in the blending fuel is about. 1.20, its density is 0.984 g/cm³, the calorific value is 43.17 MJ/kg, and the freezing point is <-60℃. This work provides new ideas for the development of an efficient and sustainable aviation energy system.

An experimental method for igniting solid propellants with combustible gas mixture was developed using a rapid compression machine (RCM), and the ignition characteristics of C₃H₆/O₂/Ar mixture and C₃H₆/O₂/Ar mixture + NEPE propellant system were studied. Transient pressure sensors and high-speed camera were employed to simultaneously obtain the pressure and high-speed images of the ignition process for both the C₃H₆/O₂/Ar gas mixture and the C₃H₆/O₂/Ar gas mixture + NEPE propellant system. The effects of different C₃H₆/O₂ concentrations and pressures on the ignition of the gas mixture and the gas mixture + NEPE system were analyzed. The mechanism of the gaseous C₃H₆/O₂/Ar mixture igniting NEPE propellant was revealed. The results show that the addition of C₃H₆/O₂/Ar gas mixture promotes the ignition of NEPE propellant containing graphene oxide and lowers its ignition limit. As the concentration of C₃H₆/O₂ increases, at a pressure of 20 bar, the NEPE propellant transitions from non-ignition to ignition, and a deflagration occurs under the condition of a 2% C₃H₆/9% O₂/89% Ar gas mixture (Mix3). With the increase of pressure, both the Mix4 and Mix4 + NEPE propellant systems transition from non-ignition to ignition, and the ignition delay time gradually shortens.

Large capacity storage battery with its advantages of high energy density has become the new type of energy storage systems, and one of the important development direction of new energy electric vehicles. This study focuses on the heat generation behavior characteristics and capacity attenuation mechanism of large-capacity energy storage batteries. The experimental test method is used to explore the relationship between the thermal behavior and performance decay of the battery under different charging and discharging conditions. The experimental results show that different working conditions (such as temperature, multiplication rate, etc.) have significant impact on the heat generation behavior of the battery. The maximum temperature rise of the battery was 21.64℃ for the high-rate 1.0C discharge, and only 3.5℃ for the low-rate 0.25C discharge. In addition, the multi-point temperature monitoring results showed that the temperature distribution of the large-size battery was obviously not uniform, and the temperature rise near the negative electrode was higher than that in other areas. In the high temperature environment of 45℃, the capacity decay rate of the battery is 2.26 times that of 25℃ after 100 consecutive charge and discharge cycles. Through this experimental study, it is expected to provide guidance for the safety of large size/capacity energy storage batteries and the design of battery management system.

In this study, the Wucaiwan high-alkali coal (WCW) from Zhundong was used as the raw material. SiO₂, Al₂O₃, Fe₂O₃, Na₂CO₃ and CaCO₃/CaSO₄ were used to prepare the synthetic ash. The samples were burned in the furnace. The ashes after burning were screened and analyzed by XRD and FTIR to explore the influence of calcium species on the sintering characteristics of high-alkali coal ash. The results show that the initial sintering temperature of the synthetic ash prepared by CaCO₃ (RR-1-Cal) is lower than that of prepared by CaSO₄ (RR-1-An), but the sintering tendency of RR-1-An is stronger than that of RR-1-Cal. The influence of CaCO₃ in ash on liquid phase sintering is because Na-Si-Al reacts to form albite, and after CaO reacts with Si/Al to form calcium-containing aluminosilicate, albite and calcium-containing aluminosilicate undergo low-temperature eutectic. Without the low-temperature eutectic between calcium aluminosilicates and albite, CaSO₄ contained in the ash add the sulfate radicals into the reaction, which make the silicon-aluminum structure more unstable at high temperatures and leads to the melting and sintering phenomenon easier to occur. During the solid-phase sintering process, CaCO₃ first destroys and then polymerizes the silicon structure of coal ash, while CaSO₄ promotes the polymerization of coal ash at lower temperatures.

Heat generation in lithium-ion batteries is crucial for the safe and stable operation of batteries at high energy and high power densities. This paper establishes a pseudo-two-dimensional electrochemical model (P2D) of lithium-ion batteries based on the COMSOL Multiphysics platform, and then investigates the effect of the volume fractions of active materials in the positive and negative electrodes, the thickness of the positive electrode, and the volume fractions of the separator electrolyte on battery heat generation, and combines this with the NSGA-Ⅱ multi-objective optimization algorithm, which is an evolutionary algorithm used to solve multi-objective optimization problems. It simulates the natural selection process to find a set of solutions called Pareto optimal solutions. Through this algorithm, the synergistic effects of the above key structural parameters on battery capacity and heat generation are analyzed systematically, thus providing theoretical support for the performance optimization design of lithium-ion batteries with high capacity and low heat generation.

To reduce the specific energy consumption of hydrogen liquefaction process and improve the utilization rate of cold energy in the deep-cooling stage, a novel cascade hydrogen liquefaction process based on dual mixed refrigerant deep-cooling is proposed. The process uses mixed refrigerant for pre-cooling and cascade double mixed refrigerant reverse Brayton cycles for deep-cooling. The process produces 300 t/d, and the para-hydrogen concentration of the product is more than 99%. The process was simulated using Aspen HYSYS software, and the genetic algorithm was called in Matlab to optimize the key parameters of the process with specific energy consumption as the objective function. The optimization results show that the specific energy consumption of the proposed process is 6.07 kWh/kg. The composite curves of heat exchanger are more matched, with a minimum internal temperature approach of 1.0—1.5℃. This process provides reference for the optimization and improvement of large-scale hydrogen liquefaction processes.

Polymer non-catalytic reduction (PNCR) denitrification agent and waste incineration bottom ash and fly ash generated during the application of the process were used as research objects, this study investigated the release and residual characteristics of elemental nitrogen in the thermal decomposition process of PNCR denitrification agent, characterised the structure of waste incineration bottom ash and fly ash, revealed the characteristics of nitrogen-containing pollutants in the bottom ash and fly ash of waste incineration after the application of PNCR denitration process, and probed the adsorption behaviour of the bottom ash and fly ash on ammonia and the characteristics of the release of pyrolysis. The results showed that the PNCR denitrator decomposed and released nitrogen almost completely under high temperature conditions, and the residual nitrogen-containing pollutants in bottom ash and fly ash were less than 0.5% (mass); GCMS and XPS showed that the nitrogen-containing substances in bottom ash and fly ash mainly existed in the form of inorganic nitrogen salts (nitrate, ammonium salts) and organic nitrogen (pyridines, pyrroles, and nitriles). Characterisation by TG-MS and in-situ IR as well as direct thermal desorption experiments revealed that the ammonia content released by heating was extremely low compared to other thermal desorption gases, the thermal decomposition products were mainly NO _x, and the residual capacity of free ammonia adsorption by fly ash and bottom ash was extremely low. The results of the study will provide theoretical support for the effective disposal of nitrogenous pollutants from solid wastes in the waste incineration industry, in order to promote the promotion and application of the PNCR denitrification process.