This research investigates the potential of blending complementary lard oil with rubber seed oil as feedstock for biodiesel production. Rubber seed oil, obtained through hexane extraction using the Soxhlet method, contains the major fatty acids of oleic acid (C_18:1), palmitic acid (C_16:0), linoleic acid (C_18:2), and stearic acid (C_18:0), while rubber seed oil primarily consists of linoleic acid (C_18:2), oleic acid (C_18:1), linolenic acid (C_18:3), palmitic acid (C_16:0), and stearic acid (C_18:0). The least acid value of lard oil (0.55 mg KOH/g) can benefit of reducing soap formation of rubber seed oil during transesterification process in biodiesel production due to its substantial-high acid value (16.28 mg KOH/g). Blending at ratios below 80:20 volume ratio produced biodiesel exceeding 85%, utilizing CaO as a catalyst. Lard oil demonstrated a higher reaction rate constant (11.88×10^-3 min^-1) than rubber seed oil (2.11×10^-3 min^-1), indicating a significant difference in performance. High acid value and free fatty acids in rubber seed oil correlated with lower reaction rates. Maintaining a mixture ratio below 80:20 volume ratio optimized reaction rates during biodiesel production. Biodiesel obtained from blends below 80:20 volume ratio met ASTM D6751 and EN 14214 standards, demonstrating suitability for bio-auto fuel. The drawbacks of using rubber seed oil as a raw material for biodiesel production are overcome by blending with lard oil, giving rise to expanding renewable energy options for rural communities, community enterprises, and large-scale biodiesel production.

This research was performed to investigate the optimization of copper recovery from copper smelting slag (CSS) with a deep eutectic solvent as a green reagent. The effect of important parameters on the leaching efficiency of copper and zinc (as well as dissolution of iron), such as leaching time, leaching temperature, solid/liquid ratio, and particle size was studied. In order to model the copper recovery, an optimization method was used. According to the chemical analysis of CSS, the slag contains 0.9% copper, 3.3% zinc, and 36.7% iron. Also, it was found that the CSS is mainly composed of Fe₂SiO₄, Fe₃O₄ and SiO₂. Copper-containing structures were determined as CuO and CuS. As a result of leaching experiments, 80% copper and 61% zinc recoveries were obtained at 48 h, 95 ℃, 1/25 g·ml^-1, and -33 μm. It is noted that the iron and silicon dissolution remained negligible under the selected conditions. According to the mathematical model, the highest copper leaching efficiency (up to 100%) could be under optimum working conditions as 48.5 ℃ leaching temperature, 40.1 h leaching duration, and 62.3 ml·g^-1 solid/liquid ratio. Also, the proposed model revealed that a wide range of experimental levels can be used as leaching parameter to get desired metal leaching efficiency.

Poly(4-methyl-1-pentene) hollow fiber membranes (PMP HFMs) are commonly used in gas separation membrane and artificial lung membrane in extracorporeal membrane oxygenation (ECMO), and its porous structure and mechanical properties have a significant impact on the performance of the membrane material. In our work, PMP HFMs were prepared by thermally induced phase separation method. Subsequently, through characterization analysis of powder X-ray diffraction, universal tensile machine, scanning electron microscope and other instruments, the effects of PMP concentration, diluent ratio, quenching temperature, air gap distance and winding speed on the membrane performance were systematically investigated to obtain optimal preparation conditions for PMP HFMs. The results showed that the PMP HFMs prepared under optimal conditions possessed good gas permeability with a nitrogen flux of 10.5 ml·MPa^-1·cm^-2·min^-1, a surface dense layer, and a good tensile strength of 9.33 MPa. We believed that this work could provide useful references for the application of PMP membranes in the medical field.

The circulating water system is widely used as the cooling system in the process industry, which has the characteristics of high water and power consumption, and its energy consumption level has an important impact on the economic performance of the whole system. Pump network and water turbine network constitute the work network of the circulating water system, that is, the fluid machinery network. Based on the previous studies, this paper proposes a stepwise method to optimize the fluid machinery network, that is, to optimize the network structure by using the recoverable pressure-head curve of the branch, and consider the recovery of adjustable resistance at the valve of each branch, so as to further reduce energy consumption and water consumption. The calculation result of the case shows that the topology structure optimization can further reduce the operation cost and the annual capital cost on the basis of the fixed structure optimization, and the total annualized cost can be reduced by 30.04%. The optimization result of different flow shows that both the pump network and the water turbine network tend to series structure at a low flow rate whereas to parallel structure at a high flow rate.

Hydrothermal liquefaction (HTL) is a promising method for sustainable waste management and renewable energy production, converting mixed feedstocks into bio-crude, a precursor to various biofuels. A study focused on mixed residential waste (MRW) as an HTL feedstock investigated temperature ranges (280-360 ℃) and residence times (30-90 min), achieving a maximum bio-crude yield of 39.16% at 340 ℃ and 75 min. Also, a thorough investigation of the synergistic relationships between all subcomponents of the MRW feedstock was conducted and concluded that the mixed waste (MW) feedstock samples containing a higher proportion of food and plastic wastes and MRW sample presented with a co-liquefaction percentage (CE) of around 60% and 107% respectively for production of bio crude. Also, solvents such as ethanol, glycerol and aqueous phase (AQ) were tested for their potential as hydrothermal mediums and found that bio crude yield of 46.19% was obtained in case of AQ phase recirculation. Further, the quantitative and qualitative effect of usage of four different catalysts were tested individually and in combination with AQ phase recirculation and found that, although individually nanoporous ZnO and diatomaceous earth (DE) yielded bio crude in the range of 46.86% and 42.68% respectively, when used in combination, DE cat-HTL with AQ resulted in maximum bio crude yield of 54.35%. Furthermore, qualitatively, the bio crude from DE cat-HTL with AQ presented with a high carbon and energy recovery percentage of 62.20% and 72.95% respectively and a high hydrocarbon content of 58.98%.

The traditional methods for synthesizing flexible heat exchanger networks (HENs) are not directly applicable to inter-plant HEN challenges, primarily due to the spread of system uncertainty across plants via intermedium fluid circles. This complicates the synthesis process significantly. To tackle this issue, this study proposes a decomposed stepwise methodology to facilitate the flexible synthesis of the inter-plant HENs performing indirect heat integration. A decomposition strategy is proposed to divide the overall network into manageable sub-networks by dissecting the intermedium fluid circles. To address the variability in intermedium fluid temperatures, a temperature fluctuation analysis approach is developed and a heuristic rule is introduced to maintain the temperature feasibility of the intermedium fluids. To ensure adequate flexibility and cost-effectiveness of the designed networks, flexibility analysis and network retrofit steps are conducted through model-based optimization techniques. The efficacy of the method is demonstrated through two case studies, showing its potential in achieving the desired operational flexibility for inter-plant HENs.

A simple and convenient preparation method with high catalytic reduction activity is crucial for the remediation of nitrate contamination. In this study, the innovation for fabricating a nanoelectrode was developed by calcinating the anodized plate to alter the surface crystalline phase of the material. The prepared calcined Ti nanopores (TNPs) electrode could effectively remove up to 95.1% nitrate from simulated groundwater at 30 mA·cm^-2 electrolysis for 90 min, while under the same conditions, the removal efficiency of nanoelectrode prepared by conventional methods was merely 52.5%. Scanning electron microscopy images indicated that the calcined TNP nanoelectrode was porous with different pore sizes. The higher nitrate removal efficiency of TNPs-500 (95.1%) than TNPs-400 (77.5%) and TNPs-550 (93.4%) may resulted from the positive nonlinear response of the larger electrochemical active surface area, the improved electron transfer and suitable surface structure, and not the “anatase-to-rutile” of surface TiO₂ nanotubes. After 90 min of electrolysis, using RuO₂ as an anode and adding 0.3 g·L^-1 NaCl solution, 87.5% nitrate was removed, and the by-products (ammonia and nitrite) were negligible. Increased temperature and alkaline conditions can enhance the nitrate removal, while higher initial nitrate concentration only improved the nitrate removal slightly. Moreover, The TNPs-500 electrode also exhibited excellent nitrate removal performance in real groundwater with the efficiency at 82.9% and 92.1% after 90 and 120 min, which were 0.87 (removal efficiency = 95.1%), 0.92 (removal efficiency = 100%) of the efficiency for simulated groundwater, indicating the widely applicable conditions of the TNPs-500 electrode. This approach of surface-bonded elements and structure modification through calcination significantly improves catalytic activity and will guide the simple designing of functional nanostructured electrodes with wide application conditions.

CO₂-based carbon-neutral organics production processes could potentially reshape the chemical industry. However, their feasibility and net carbon footprint rely strongly on the sources of H₂. Herein, we present a comprehensive comparative techno-economic analysis of CO₂-based methanol (CO₂TM) and α-olefins (CO₂TO) manufacturing using various feedstock supply modes: (1) the standalone mode with external CO₂ but H₂ from on-site water electrolysis, (2) the integrated mode with both CO₂ and H₂ recovered from coal-chemical plants, and (3) the integrated mode with recycled CO₂ but H₂ from on-site water electrolysis. The integration of CO₂TM and CO₂TO into coal-to-olefins (CTO) and coal-to-methanol (CTM) facilities is currently cost-effective and can reduce net CO₂ emissions by 65.7% and 68.5%, resulting in a three-fold and two-fold increase in carbon efficiency, respectively. As carbon tax policies and electrolysis technologies continue to evolve, standalone CO₂TM and CO₂TO are projected to become more economically competitive than CTO and CTM by 2035-2045.

The selective hydrogenation of dimethyl toluene-2,4-dicarbamate (TDC) to methyl cyclohexyl-2,4-dicarbamate (also called hydrogenated TDC, HTDC) is an essential process for non-phosgene synthesis of methylcyclohexane-2,4-diisocyanate. Herein, we prepared a series of supported Rh-based catalysts by the excessive impregnation method and investigated their catalytic performance for the selective hydrogenation of TDC. The emphasis was put on the influence of support properties on the catalytic performance. Among the prepared catalysts, Rh/γ-Al₂O₃ performed the best: a HTDC yield of 88.4% was achieved with a 100% conversion of TDC under the conditions of 100 ℃, 3 MPa and 1 h. Furthermore, Rh/γ-Al₂O₃ could be repetitively used for 4 times without a significant loss of its catalytic activity. TEM, XRD, N₂ adsorption-desorption, H₂-TPR, NH₃/CO₂-TPD, XPS and ICP characterizations were employed to distinguish the properties of the prepared catalysts and the results were correlated with their catalytic performance. It is indicated that the yield of HTDC shows a positive relevance with the percentage of moderate-to-strong acid sites and the content of Rhⁿ⁺ (n ≥ 3) in the catalysts. High values of the percentage and the content can promote a strong interaction between Rh nanoparticles and the supports, facilitating both the transfer of electrons from Rh to the support and the formation of Rhⁿ⁺ species. This is conducive to activating the benzene ring of TDC and thereby improving the yield of HTDC.

Gas-phase polyethylene (PE) processes are among the most important methods for PE production. A deeper understanding of the process characteristics and dynamic behavior, such as properties of PE and reactor stability, holds substantial interest for both academic researchers and industries. In this study, both steady-state and dynamic models for a gas-phase polyethylene process are established as a simulation platform, which can be used to study a variety of operation tasks for commercial solution polyethylene processes, such as new product development, process control and real-time optimization. The copolymerization kinetic parameters are fitted by industrial data. Additionally, a multi-reactor series model is developed to characterize the temperature distribution within the fluidized bed reactor. The accuracy in predicting melt index and density of the polymer, and the dynamic behavior of the developed models are verified by real plant data. Moreover, the dynamic simulation platform is applied to compare four practical control schemes for reactor temperature by a series of simulation experiments, since temperature control is important in industrial production. The results reveal that all four schemes effectively track the setpoint temperature. However, only the demineralized water temperature cascade control demonstrates excellent performance in handling disturbances from both the recycle gas subsystem and the heat exchange subsystem.

Catalytic carbon dioxide (CO₂) desorption has emerged as a promising approach to enhance the efficiency of CO₂ capture while minimizing energy demands, crucial for advancing chemical absorption methods. This study investigates the catalytic potential of three metal phosphates (aluminium phosphate (AlPO₄), cobaltous phosphate (Co₃(PO₄)₂), and zinc phosphate (Zn₃(PO₄)₂)) in improving the MEA (monoethanolamine) -based CO₂ absorption-desorption performance. Among the catalysts tested, AlPO₄ demonstrated superior performance, enhancing CO₂ absorption capacity by 4.2% to 9.3% and desorption capacity by 12.3% to 22.7% across five cycles. Notably, AlPO₄ increased the CO₂ desorption rate by over 104.4% at a desorption temperature of 81.3 ℃, simultaneously reducing the required sensible heat by 12.3% to 22.7%, compared to processes without catalysts. The improved efficiency is attributed to AlPO₄'s ability to effectively transfer hydrogen protons from protonated MEA to carbamate, thereby facilitating the decomposition of carbamate and regenerating CO₂. This research introduces a viable, cost-effective, and eco-friendly solid acid catalyst strategy for CO₂ desorption, contributing to the development of more energy-efficient CO₂ capture technologies.

Refined risk prediction must be achieved to guarantee the safe and steady operation of chemical production processes. However, there is high nonlinearity and association coupling among massive, complicated multisource process data, resulting in a low accuracy of existing prediction technology. For that reason, a real-time risk prediction method for chemical processes based on the attention-based bidirectional long short-term memory (Attention-based Bi-LSTM) is proposed in this study. First, multisource process data, such as temperature, pressure, flow rate, and liquid level, are preprocessed for denoising. Data correlation is analyzed in time windows by setting time windows and moving step lengths to explore correlations, thus establishing a complex network model oriented to the chemical production process. Second, network structure entropy is introduced to reduce the dimensions of the multisource process data. Moreover, a 1D relative risk sequence is acquired by max-min deviation standardization to judge whether the chemical process is in a steady state. Finally, an Attention-based Bi-LSTM algorithm is established by integrating the attention mechanism and the Bi-LSTM network to fit and train 1D relative risk sequences. In that way, the proposed algorithm achieves real-time prediction and intelligent perception of risk states during chemical production. A case study based on the Tennessee Eastman process (TEP) is conducted. The validity and reasonability of the proposed method are verified by analyzing distribution laws of relative risks under normal and fault conditions. Also, the proposed algorithm importantly improves the prediction accuracy of chemical process risks relative to that of existing prediction technologies.

The construction of Co-Mn mixed-metal oxide catalysts derived from bimetallic metal-organic frameworks (MOFs) has great significance for catalytic destruction of toluene. Hence, a series of Co_aMn_bO_x-MOFs with different physicochemical properties were successfully synthesized via pyrolysis of Co—Mn bimetallic MOFs. Attributing to the higher specific surface area, more active sites (Co³⁺ and Mn³⁺), stronger reducibility, and abundant defect sites, the as-prepared Co₁Mn₁O_x-MOFs displayed an optimal catalytic performance, especially the excellent water vapor resistance. The result of the in situ diffuse reflectance infrared Fourier transform spectroscopy demonstrated that toluene can be degraded at relatively low temperatures (＜100 ℃). Benzyl alcohol, benzaldehyde, benzoic acid, and maleic anhydride were the main intermediate products in toluene degradation process. This work reveals the value of bimetallic MOFs derived Co—Mn oxides for toluene oxidation and presents a novel avenue for designing mixed-metal oxide catalysts with potential applications in volatile organic compounds (VOCs) catalytic oxidation.

This work aims to develop a model that will improve the performance and energy efficiency of a novel electrocoagulation (EC) process utilized in wastewater treatment to extrapolate the findings to an industrial scale. Utilizing Design of experiments (DOE) allows us to maximize treatment efficiency while minimizing energy consumption. This evaluation was conducted by employing aluminum electrodes as sacrificial anodes. The main factors identified in preliminary experiments are the pH of the medium, the applied potential, and the treatment time. A three-level (3³) factorial design was employed to examine the relationship between efficiency performance and energy consumption. Under optimal conditions, treatment efficiency is around 66% for biological oxygen demand within 5 days (BOD₅), 98% for chemical oxygen demand (COD), associated with a minimum energy consumption of 2.39 kW·h·mg^-1 of COD. The parameters most significantly influenced by the mathematical models obtained were the potential or applied current, treatment time, and their interaction. The modeling results were also correlated with the experimental results and there were minimal discrepancies. The modeling results were also correlated with the experimental results to assess the accuracy and validity of the model's predictions and there were minimal discrepancies. The results provide promising possibilities for advancing an environmentally friendly wastewater treatment methodology and an economically viable technological solution.

Non-Newtonian fluids have variable viscosity in response to shear rate, and the presence of polymers and nanoparticles further modifies their flow characteristics. In this paper, the effects of polymers and nanoparticles on mass and heat transfer control, drag reduction, boundary layer flow development in a polymeric finitely extensible nonlinear elastic-Peterlin (FENE-P) fluid, and the significance of nanoscience in modern day life are discussed. We examine the behavior of polymer additives by utilizing a dispersion model in conjunction with the polymeric FENE-P model. Our work includes a comparison with Cortell's earlier work, which only looked at the behavior of polymer’s inclusion into the base fluid. This research investigates numerically how the inclusion of polymers and nanoparticles into the base fluid reduces drag while increasing heat and mass transfer. The observed variations in skin friction, reduced Nusselt, and Sherwood numbers indicate an intriguing correlation between the rates of heat and mass transport and surface drag. More precisely, as the heat and mass transfer efficiency improve, the surface encounters less resistance, which is commonly referred to as drag. In summary, the research highlights the capability of polymers and nanoparticles to effectively modify fluid dynamics, minimize drag, and enhance mass and heat transfer inside the flow region.

This work synthesized a series of Ni/CeO₂/Al₂O₃ catalysts with varying CeO₂ doping amounts to enhance low-temperature CO₂ methanation. The introduction of CeO₂ weakens the interaction between Ni and Al₂O₃, leading to the formation of Ni-CeO₂ active sites. This results in a high dispersion of Ni and CeO₂, improved catalyst reducibility, increased number of active sites, and enhanced the CO₂ methanation. This work further investigated the impact of WHSV and catalyst stacking configuration to enhance the reaction. When the catalyst is stacked into three segments with a temperature gradient of 330 ℃, 300 ℃, and 250 ℃ under WHSV = 9000 ml·h^-1·g^-1, the CO₂ conversion significantly increases to 95%, which is remarkably close to the thermodynamic equilibrium (96%).

This paper conducts a comparative analysis of the anti-wetting properties and degassing performance of both homemade and commercial membranes. Additionally, it introduces a unique approach to hydrophobic modification of high-flux membranes. The study involved the utilization of Hyflon AD40L for multiple coatings on the surface of polypropylene (PP) hollow fiber membranes. Several variables, including modification solution concentration, temperature, coating duration, number of coating cycles, polymer type, and the choice and concentration of the pore-blocking agent, were systematically investigated to establish the optimal modification process. Characterization of the modified membrane and degassing experiments revealed significant improvements. Specifically, the contact angle increased from 95.5° to 113.1°, while the trans-membrane differential pressure surged from 10.7 kPa to 154.6 kPa, marking a remarkable 14.4-fold enhancement. This enhancement is attributed to the improved anti-wetting capabilities of the modified membrane. In the degassing experiments, the modified membrane-based module demonstrated an impressive 95.0% dissolved oxygen removal rate, with a corresponding mass transfer coefficient reaching 18.01×10^-3 m·h^-1. These results underscore the substantial potential of the Hyflon AD40 L/PP membrane for applications in membrane degassing.

Natural gas is increasingly recognized as a clean energy source due to its high quality, low pollution levels, and abundant availability. However, certain gas fields contain complex components that require purification for efficient transportation and utilization. Addressing these issues involves efficient gas-liquid separation technology. Existing gas-liquid separation units face challenges such as efficiency, liquid entrainment, energy consumption, and the need for consumable replacement. This study focuses on a novel cyclone-coalescence separator that combines centrifugal and coalescence principles. Implemented in a high-acid natural gas purification plant in China, the cyclone-coalescence separator demonstrated efficiency primarily influenced by gas velocity and diameter. Optimal performance was observed with a 75 mm diameter reactor at velocities of 8-12 m·s^-1, achieving a peak efficiency of 96%. The hydrophilic glass fiber with a monofilament structure can coalesce droplets effectively. In practical industrial use, under operational conditions, the hydrocyclone's liquid discharge rate is 89.6 kg·h^-1 with an inlet concentration of 382.7 g·m³. Over a 400-h cycle, the cyclone-coalescence separator demonstrated superior separation performance with an average liquid discharge volume of 9.09 mg·kg^-1, compared to 4.93 mg·kg^-1 for the precision filter. This successful industrial implementation presents a promising approach to natural gas purification.

High-concentration phenol wastewater is pollutant of concern that pose significant risks to human health and the environment. Three-dimensional electrocatalytic oxidation is one of the most promising wastewater treatment technologies because of its high treatment efficiency, low energy consumption and low secondary pollution. Lower-cost and higher-performance particles still faces great challenges. In this work, metal oxide particle electrodes were prepared using granular activated carbon (GAC) as a substrate to study the degradation of phenol by three-dimensional electrocatalytic oxidation. GAC particle electrodes loaded with different monometallic oxides (Mn, Fe, Co, Ce) and bimetallic oxides (Fe and Ce) were prepared by the impregnation method. The effectiveness of the particle electrodes in degrading phenol was greatly improved after active components loading. Among all monometallic oxide particle electrodes, the concentration degradation efficiency was in the order of Ce/GAC > Co/GAC >Mn/GAC > Fe/GAC, and the COD degradation efficiency was Ce/GAC > Fe/GAC > Co/GAC >Mn/GAC. After optimizing the loading metal type and loading amount, it was found that the 1.1% Fe-2.7% Ce/GAC particle electrode perform the best, with a phenol degradation efficiency of 95.48%, a COD degradation rate of 94.35%, an energy consumption of 0.75 kW·h·kg^-1 COD. This lower-cost and higher-performance particle highlights a reliable route for solving the problem of particle electrode materials limiting the efficient treatment of phenol-containing wastewater.

Polylactic acid (PLA) is a potential polymer material used as a substitute for traditional plastics, and the accurate molecular weight distribution range of PLA is strictly required in practical applications. Therefore, exploring the relationship between synthetic conditions and PLA molecular weight is crucially important. In this work, direct polycondensation combined with overlay sampling uniform design (OSUD) was applied to synthesize the low molecular weight PLA. Then a multiple regression model and two artificial neural network models on PLA molecular weight versus reaction temperature, reaction time, and catalyst dosage were developed for PLA molecular weight prediction. The characterization results indicated that the low molecular weight PLA was efficiently synthesized under this method. Meanwhile, the experimental dataset acquired from OSUD successfully established three predictive models for PLA molecular weight. Among them, both artificial neural network models had significantly better predictive performance than the regression model. Notably, the radial basis function neural network model had the best predictive accuracy with only 11.9% of mean relative error on the validation dataset, which improved by 67.7% compared with the traditional multiple regression model. This work successfully predicted PLA molecular weight in a direct polycondensation process using artificial neural network models combined with OSUD, which provided guidance for the future implementation of molecular weight-controlled polymer's synthesis.

Photocatalytic oxidation technology is a promising green technology for degrading volatile organic compounds (VOCs) due to its non-toxic, environmentally friendly, energy-saving and affordable characteristics. In this paper, Ag/TiO₂@PANI-MC with high stability and activity was synthesized by the mechanochemical method. The designed Ag/TiO₂@PANI-MC were of high specific surface area, light absorption capacity and low recombination rate of electron-hole pairs, which was demonstrated by various characterizations. When applied in photocatalytic toluene oxidation, the conversion is 17% at 20 ℃ under 100 W high-pressure mercury lamp. This photocatalytic performance is with less temperature sensitivity and significantly improved compared with Ag/TiO₂ or TiO₂ catalysts. Furthermore, the reaction routine was also confirmed by gas chromatography-mass spectrometry and toluene was mineralized to CO₂. More importantly, the Ag/TiO₂@PANI-MC indicated good reusability after three cycles, which was verified by the Fourier transform-infrared spectroscopy comparison with fresh and used catalysts. Our work proves a potential way of constructing nanocomposites based on mechanochemical synthesis for enhanced toluene photocatalytic degradation.

Constructing a three-dimensional (3D) network of fillers with high thermal conductivity is considered to be an effective strategy to obtain ideal thermal management materials (TMMs). However, 3D filler network is often disrupted by the subsequent processing and forming processes, and it is difficult to incorporate high levels of fillers into lyophilized aerogels, which is a key factor limiting their widespread use. In this work, boron nitride@polymethylacrylimide/epoxy (BN@PMI/EP) composites with a stable 3D BN network were prepared by freeze-drying and hot-pressing. A water-soluble copolymer quaternary ammonium salt has been synthesized by the solution polymerization. A BN@PMI aerogel was obtained by the freeze-drying of ammonium salt and BN solution and thermal imidization. The BN@PMI aerogel has a six-membered imine ring structure that can be loaded with a high content of BN, which ensures the stability of the 3D BN network structure and facilitates the subsequent impregnation of EP in vacuum, which is one of the innovations of this work. The stable and complete 3D BN network leads to the enhancement of thermal conductivity, and the out-of-plane and in-plane thermal conductivities of BN@PMI/EP reach 1.21 W·m^-1·K^-1 and 2.76 W·m^-1·K^-1 at a BN mass loading of 40%, respectively. Meanwhile, the excellent mechanical properties and results of finite-element simulation and actual experiments confirm that BN@PMI/EP is a potential TMM.

Timely and accurate gas load forecasting is critical for optimal scheduling under tight winter gas supply conditions. Under the background of the implementation of “coal-to-gas” for winter heating in rural areas of North China and the sufficient field research, this paper proposes a correction algorithm for daily average temperature based on the cumulative effect of temperature and a set of combined forecasting models for gas load forecasting based on machine learning and introduces its application through a detailed case study. In order to solve the problems of forecasting performance degradation and complexity increase caused by too many influencing factors, a combined forecasting model back-propagation-improved complete ensemble empirical mode decomposition with adaptive-noise-gated recurrent unit based on residual sequence analysis is proposed. Back propagation (BP) neural network is used to analyze the main influencing factors, so that the secondary influencing factors are reflected in the residual sequence generated by the forecasting. After decomposition, reconstruction, and re-forecast, the mean absolute percentage error (MAPE) of the combined models for the daily gas load in the case study has been controlled under 1.9%, which is significantly improved compared with each single algorithm. The forecasting error before and after the temperature correction are also compared. It is found that the MAPE with the temperature correction is reduced by 1.7%, which reflects the effectiveness of the temperature correction to eliminate the impact of temperature cumulative effect and its contribution to the improvement of the forecasting accuracy for the combined forecasting models.

The Chinese standard method of GB/T 4000-2017 was unable to accurately measure the coke thermal properties in the large blast furnace. Therefore, the coke compressive strength (CCS) test at a high temperature was designed to examine the coke thermal properties. Then, the large-scale coke model (sp²C₁₇₄₂₁sp³C₆₅₇₉) was established. After, the ReaxFF molecular dynamics simulations were implemented to mimic the coke solution loss (CSL) and the CCS at the high temperature. It was found that the adsorption energy and the diffusion energy of micropores were greater than those of mesopores and macropores, indicating that the CSL reaction mainly happened in the coke micropore. It was discovered that the CSL reaction mechanism was the sp³ C oxidization mechanism with the transient state of ketene structure. And, it was detected that the CCS process was divided into the plastic deformation, the instantaneous fracture and the elastic deformation and yield, which was caused by the local reconstruction, the overall folding and the center stretching of carbon layer, respectively. By comparing simulated results with experiments, it was proved that obtained mechanisms were valid. The proposed experimental and simulated methods provided a novel method to measure and understand the coke thermal properties.

In order to treat the polluted discharge from El-Jadida, Morocco, a method of electrocoagulation using aluminum electrodes was used. This approach was coupled for the first time with high-frequency electrochemical impedance spectroscopy (EIS). Significant pollutant abatement was observed after 30 min, at a current density of 190.5 A·m^-2, with a specific electrical energy consumption of 1.58 kW·h (per gram of eliminated carbon organic demand (COD)) and specific aluminum consumption of 0.11 g ·g^-1: electrocoagulation proved to be particularly effective, achieving 85.7% elimination of COD and a decrease of total dissolved solid (TDS) and electrical conductivity (EC) levels from 2430 mg·L^-1 to 1773 mg·L^-1 and from 4230 μS·cm^-1 to 3210 μS·cm^-1, respectively. As for USP and ORP, they decreased from 2.5 to 1.87 and from 244.6 mV to 51 mV, respectively. The inductance of the electrocoagulation system measured by EIS was modeled through an electrical equivalent circuit. When the applied intensity increased, the coagulation resistance increased suddenly when the applied electrical current reached 0.2 A (current density: 95.2 A·m^-2). At this point, the rate of COD abatement versus SEEC (specific electrical energy consumption decreases which shows that the EC process should be combined with another process to improve its efficiency, such as ultrasound.

Absorption refrigeration systems driven by low-temperature waste heat is one way to achieve “carbon neutrality.” Meanwhile, the keto-benzene dewaxing equipment needs a cooling capacity of 5 MW, with refrigeration temperature of -10 ℃ and -25 ℃. This paper researches the feasibility of dual-stage evaporation-ammonia hybrid compression-absorption refrigeration system (DSE-AHCARS) replacing the vapor compression refrigeration system for keto-benzene dewaxing process based on energy, exergy, economic, and environmental (4E) analysis. At the primary- and secondary-stage evaporation temperature of 0 and -23 ℃, respectively, the coefficient of performance (COP) reaches the maximum value of 0.85; however, COP-electricity reaches the minimum value of 8.1. When the secondary-stage refrigeration temperature is -23 ℃, CO₂ emission increases from 1150 t·a^-1 to 3600 t·a^-1, and life cycle climate performance increases from 3.29×10⁴ to 7.7×10⁴ t, with the primary-stage refrigeration temperature being -15-0 ℃, as well as matching three parameters to ensure the 4E compromising performance by the multi-objective optimization. To guarantee that the life cycle climate performance is less than 5.5×10⁴ t, the payback period is <2 a, and COP is >0.6 at the optimal operation ranges, such that the refrigeration temperature difference between primary stage and secondary stage is within 20 ℃. The power of DSE-AHCARS was reduced by 77% compared with the vapor-compression refrigeration system. Therefore, the DSE-AHCARS can reduce CO₂ emissions by about 6250 t·a^-1 and save 1.2×10⁵ t of CO₂ in the life cycle climate performance term. This result shows that the DSE-AHCARS can completely replace the vapor-compression refrigeration system.

The current study presents for the first time the preparation of a NiAl (68% (mass) Ni) intermetallic compound through the induction heating technique as a cathode for alkaline water electrolysis. The high-purity target was confirmed by X-ray diffraction and scanning electron microscopy combined with energy dispersive X-ray analysis. The chemical activation of Al from the NiAl electrode was achieved in a 25% NaOH solution at 353 K for 72 h. The performance and stability tests in a 1 mol·L^-1 KOH solution at 298 K demonstrated that the enhancement of the hydrogen evolution reaction was 13 times higher in the activated NiAl electrode than in the non-activated NiAl electrode. In addition, the electrochemical tests showed that the activated NiAl electrode exhibited the best hydrogen evolution reaction performance. Based on the findings, it is believed that the induction heating technique is a promising route for preparing a highly active and cost-effective NiAl electrode for green hydrogen production.