With the acceleration of the energy transition, new synthetic routes for converting alkanes into high-value products are emerging. However, the thermal safety of these new routes may not have been fully considered, potentially leading to dangers during the optimization of reaction conditions. This study reports, for the first time, a reactor explosion incident during the experiment of a new synthetic route for adipic acid: nitric acid oxidation of n-hexane. Differential scanning calorimetry (DSC), accelerating rate calorimetry (ARC), and corrective calculations were used to investigate the cause of the explosion. The results indicate that the polyparaphenol (PPL) liner material, which was used for the first time in the experiment, is unlikely to react with the system and cause the explosion. When the nitric acid concentration is increased from 3.7 mol·L^-1 to 5.4 mol·L^-1, the thermal stability of the system decreases, and the heat release surpasses the chemical explosion threshold (1000 J·g^-1). The maximum self-heat rate (dT=dt_max) increases by at least 7 times, and the maximum pressure rise rate (dT=dt_max) increases by at least 11 times. This led to the actual pressure in the reactor increasing from 4.96 MPa to at least 11.09 MPa, which far exceeded the rated pressure (3 MPa) and reached the rupture pressure (3.5 to 4 times their rated pressure), resulting in the explosion. This study aims to provide a warning regarding the safety of new synthetic routes involving the nitric acid-organic systems, particularly the conversion of alkanes, to prevent the recurrence of similar incidents.

The cycloaddition of CO₂ and epoxides to synthesize cyclic carbonates is a key strategy for CO₂ utilization, though heterogeneous catalysts often suffer from instability. Covalent organic frameworks (COFs) present a compelling alternative due to their excellent textural properties and abundant Lewis basic sites. Herein, triazine-based COFs (PC-COFs) were synthesized by optimizing reaction time and temperature and were applied to catalyze the CO₂ cycloaddition with epichlorohydrin (ECH) under solvent-free conditions, Instead of necessity of adding homogeneous co-catalyst, this study reveals a synergistic self-catalysis mechanism, where the carbonate product adsorbed on the Lewis basic PC-COF surface forms catalytic pairs with Lewis acidic carbonates, significantly accelerating the reaction. After five cycles, catalytic activity increased by 35% from 56.2% to 91.4%, and stabilizing over seven cycles. Under optimal reaction conditions, PC-COF-50-30 demonstrated outstanding catalytic performance, with a 98.7% ECH conversion, 97.6% selectivity to ECH carbonate and a CO₂ conversion rate of 9.0 g·g^-1·h^-1. This work provides a valuable example of high-performance CO₂ cycloaddition catalysts and a strategy to achieve enhanced catalytic efficiency through product-catalyst synergy.

The displacement of residual crude oil and enhanced oil recovery from reservoirs of mature oil fields are challenging worldwide and have received intensive attentions in oil and gas industry. In this work, a novel method for enhanced oil recovery by displacement of oil with bionanofluids was proposed. Micro-displacement hydrodynamics of crude oil in microchannel sand-packed porous media by the bionanofluid were investigated by high-speed imaging. The machine learning models with the extreme gradient boosting (XGBoost) algorithm was developed for the prediction of residual oil saturation during the micro-displacement processes. The residual oil droplets within the porous media after the waterflooding were effectively removed through bionanofluid-flooding, resulting in additional enhanced oil recovery of 39.0%, which is double the recovery achieved by waterflooding at the same displacement velocity. By wavelet-transform image enhancement and the XGBoost algorithm in the machine learning, the residual oil saturations along the porous media were predicted accurately with the mean squared errors of 0.0045 and 0.0030 in the waterflooding and the bionanofluid-flooding, respectively. The results indicated that the machine learning is effective in characterizing the displacement behaviors and the bionanofluid-flooding could be an interesting approach, and thus has potential applications in enhanced oil recovery of waterflooding reservoirs.

Coal-direct chemical looping (CDCL) is a promising CO₂ capture technology with low costs. Potassium modification can significantly enhance the reactivity of iron-based oxygen carriers and coal. However, potassium loss causes a decline in cyclic stability. To address this, we prepared a potassium hexatitanate-modified iron-based OC and conducted CDCL experiments in a fixed-bed reactor using Zhundong coal coke as fuel. The study examined the impact of potassium hexatitanate on carbon conversion, OC activity stability, and potassium maintenance. Additionally, FactSage was used to calculate potassium fugacity patterns at different temperatures, Fe₂O₃/C molar ratios, and OC reduction degrees. Results showed that potassium hexatitanate increased carbon conversion, achieving 50% conversion at 40% potassium addition. In multi-cycle tests, carbon conversion rose with increased cycle times, reaching 84%. This improvement is attributed to ion exchange between Fe³⁺ and Ti⁴⁺, which induces lattice distortion and creates oxygen vacancies, enhancing OC reactivity. Potassium content remained stable during multi-cycle tests, indicating the effective potassium retention capacity of potassium hexatitanate.

Sodium Y (NaY) zeolite is a promising adsorbent for carbon capture. The template-free synthesis of NaY zeolite has gained considerable interests to minimize its costs and environmental effects. However, NaY zeolites synthesized through template-free methods exhibited lower CO₂ adsorption capacities (～4.07 mmol·g^-1) compared to template-assisted counterparts, often requiring longer crystallization time and higher energy penalty. This study systematically compared the microstructural characteristics and CO₂ adsorption performance of NaY zeolites synthesized with and without templates, including those from the commercial markets. Through process optimization, the CO₂ adsorption capacity of the template-free NaY zeolite was significantly enhanced, surpassing those template-assisted samples. Notably, it achieved CO₂ adsorption capacities of 6.51 mmol·g^-1 at 25 °C and 0.1 MPa, and 7.40 mmol·g^-1 at 0 °C and 0.1 MPa, outperforming both commercial NaY and template-assisted samples. The structural differences, including crystal integrity, pore size distribution and surface properties, were systematically discussed. The optimized synthesis method increased the specific surface area and the ratio of microporous structures. The template-free NaY also showed superior CO₂ capture capacity, moisture resistance, breakthrough performance and stability, indicating its application potential for carbon capture.

Oxygen vacancy engineering is a valid strategy to boost the oxygen reduction reaction (ORR) performance of nanostructured electrocatalysts. Current methods for generating surface oxygen vacancies (V_os) in nanostructured MnO₂ is mostly lab-scale, which cannot meet the requirement of large-scale production. Herein, we employed a mechanochemical method of ball milling to introduce surface V_os into the β-MnO₂ nanoparticles. The ball milling process generated abundant surface V_os, which significantly facilitated the adsorption and activation of O₂. Consequently, the ORR performance of ball-milled β-MnO₂ was markedly boosted by varying the ball milling time. As an air cathode catalyst for zinc-air battery (ZAB), the β-MnO₂ ball-milled for 4 h displayed a high specific capacity of 804 mA·h·g^-1 and excellent cycling over 500 h at 5 mA·cm^-2, which were superior than those of pristine β-MnO₂-based ZAB. Our work offers a feasible strategy to enhance electrocatalytic ORR performance of MnO₂, which shows significant potential for large-scale production of efficient ORR electrocatalysts.

This study explores green and low-viscosity deep eutectic solvents (DESs) for the efficient extraction of quinoline (QUI) from wash oil. The hydrogen bond donors and acceptors constituting DESs were initially screened based on thermodynamic properties predicted by the conductor-like screening model for real solvents (COSMO-RS), followed by further selection considering the viscosity and cost of the formed DESs. Phase equilibrium experiments showed that the DES composed of triethylmethylammonium chloride and formic acid exhibited the best extraction performance among the selected candidates. Key extraction parameters were optimized experimentally, achieving a maximum QUI extraction efficiency of 97.18% under mild conditions. Molecular dynamics simulations revealed that the interactions between quaternary ammonium cations and QUI play a crucial role in the extraction mechanism. This study provides insights into the use of DESs for QUI extraction and demonstrates their potential for application to other coal tar derivatives.

Developing efficient bifunctional oxygen catalysts is critical for advanced rechargeable zinc-air batteries (ZABs). Here, we report a substrate-free spatial separation pyrolytic deposition strategy to synthesize highly dispersed metal nanoparticles (iron (Fe), cobalt (Co), nickel (Ni), and their alloys) embedded in N-doped carbon matrices (M@NC). By spatially separating precursor decomposition and product deposition, this method achieves controlled growth of carbon nanotubes with uniformly distributed nanoparticles while preventing metal and carbon aggregation. Among mono-/bimetallic composites, FeNi@NC catalyst emerges as a superior bifunctional oxygen electrocatalyst, achieving a low potential gap (ΔE = 0.81 V) for oxygen reduction and evolution reactions in 0.1 mol·L^-1 KOH. The excellent bifunctionality is attributed to Fe-Ni alloy-induced electronic modulation and interfacial charge transfer between the alloy core and graphitic carbon shell. When integrated into ZABs, FeNi@NC catalyst demonstrates a peak power density of 234 mW·cm^-2 and exceptional cycling stability (>700 cycles), outperforming Pt/C + RuO₂. Systematic studies reveal that bimetallic synergy reduces nanoparticle size and enhances CNT growth, while excessive metal loading or ternary systems degrade performance. XPS analyses confirm the critical roles of pyridinic/graphitic N and M-N-C covalent bonds in stabilizing active sites. This work provides a scalable synthesis paradigm and mechanistic insights into composition-structure-activity relationships.

The oversupply of diesel in China necessitates efficient separation of polycyclic aromatic hydrocarbons from fluidized catalytic cracking diesel for value-added utilization. However, purification is hindered by alkane and monocyclic aromatic interference. In this work, we propose a solvent-screening strategy for extractive distillation based on molecular polarity and interaction energy analysis. Quantum chemical calculations identified ethylene glycol (aromatic solubility) and N,N-dimethylformamide (alkane selectivity) as optimal solvents, with weak hydrogen bonds (e.g., O-H…π, C-H…π) governing aromatic interactions. Two process designs were developed: (1) solvent extraction followed by primary extractive distillation (purity >95.0% (mass)) and (2) direct two-stage extractive distillation (purity >92.0% (mass)). This work provides a flexible framework for polycyclic aromatic hydrocarbon separation tailored to market demands while elucidating solvent-solute interactions at the molecular level.

Microdispersion technology is crucial for a variety of applications in both the chemical and biomedical fields. The precise and rapid characterization of microdroplets and microbubbles is essential for research as well as for optimizing and controlling industrial processes. Traditional methods often rely on time-consuming manual analysis. Although some deep learning-based computer vision methods have been proposed for automated identification and characterization, these approaches often rely on supervised learning, which requires labeled data for model training. This dependency on labeled data can be time-consuming and expensive, especially when working with large and complex datasets. To address these challenges, we propose MicroFlowSAM, an innovative, motion-prompted, annotation-free, and training-free instance segmentation approach. By utilizing motion of microdroplets and microbubbles as prompts, our method directs large-scale vision models to perform accurate instance segmentation without the need for annotated data or model training. This approach eliminates the need for human intervention in data labeling and reduces computational costs, significantly streamlining the data analysis process. We demonstrate the effectiveness of MicroFlowSAM across 12 diverse datasets, achieving outstanding segmentation results that are competitive with traditional methods. This novel approach not only accelerates the analysis process but also establishes a foundation for efficient process control and optimization in microfluidic applications. MicroFlowSAM represents a breakthrough in reducing the complexities and resource demands of instance segmentation, enabling faster insights and advancements in the microdispersion field.

The research on scheduling and heat integration of batch process plays an important role in reducing energy consumption, improving production efficiency and enhancing the competitiveness of industries. The complexity and difficulty of the model solving are increased due to the comprehensive consideration of both scheduling and heat integration. In this paper, the mixed integer nonlinear programming (MINLP) mathematical model of multi-product plant heat integration optimization with the goal of energy-saving annual profit (EAP) is established. The simultaneous optimization and sequential optimization are carried out respectively by bi-level programming (BP) based on the genetic algorithm (GA), and the calculation results are compared. EAP better captures the trade-off relationship between scheduling schemes, energy-saving profits, and equipment costs. The bi-level programming approach based on GA categorizes variables into integer and real types, enabling structural optimization and parameter optimization of the heat exchanger network. This, in turn, enhances solution efficiency and overcomes the limitations of conventional optimization algorithms in terms of solution speed and quality. Two examples show that the EAP of indirect heat integration considering the storage tank are 21% and 2% higher than that of the direct heat integration, and EAP of the simultaneous optimization are 26% and 6% higher than that of the sequential optimization. The example demonstrates that the model and algorithm are applicable to batch multi-product plants, such as those in the chemical, pharmaceutical, and food industries, and possess strong practicality and innovation.

The Taylor-Couette reactor can achieve precise control of heat transfer, mass transfer, and reactions, and it has been widely used in chemical production fields. In this paper, computational fluid dynamics-discrete phase model (CFD-DPM) simulation was used to study the dynamic characteristics of bubbles in the Taylor-Couette reactor, and the results were verified by high-speed camera experiments. The effects of rotational Reynolds number Re, axial Re_a and bubble diameter d_g were considered. Then a quadratic polynomial model of bubble residence time in the reactor was established using response surface methodology (RSM). The results show that in the range of rotational Re = 3482-10446, the movement trajectory of the bubble in the Taylor-Couette reactor followed the cylindrical helix. The increase of rotational Re can strengthen the downflow of Taylor vortex and reduced the ascent rate of bubbles, resulting in the increase of bubble residence time. And there was a synergetic effect of the rotational Re and d_g on the residence time. Besides, Re_a had positive effect on the bubble residence time under the condition of low level of Re (Re = 3482, 6964). Finally, the quadratic polynomial model was proven to be feasible to predict the residence time of bubble in the Taylor-Couette reactor. This study contributes to a deeper understanding of the bubble dynamics within Taylor reactors and offers theoretical guidance for their operation.

This study presents a theoretical and experimental analysis of laminar flow behavior of high-viscous non-Newtonian power-law and Bingham fluids in multiple structural bifurcation channel distributors. Theoretical models are derived to describe velocity profiles, shear rate distribution, and pressure drop across specific channels. Modified pressure drop models are proposed based on experiments on 6 kinds of non-Newtonian fluids and 3 types of bifurcation channel distributors with different transition areas. Specifically, the deviations between the theoretical models and the experimental results are systematically analyzed, and models were modified with correction coefficients based on Reynolds number and dimensionless shape factor. The theoretical results, modified results and experimental data are compared and discussed to ensure the accuracy of the modified models, demonstrating a significant improvement in the prediction of pressure drops for high-viscous non-Newtonian fluids in certain types of bifurcation channels. Additional experiments and analyses were carried out to validate the modified models and the results suggest that the models offer a certain degree of universal applicability in bifurcation channel designs. It implies that for other types of bifurcation channel distributors, similar correction methods based on Reynolds number and shape factor may also be applicable even with different coefficients.

Phosphorylated sugars, recognized as central intermediates in carbohydrate metabolism and critical precursors for enzymatic synthesis of rare sugars, face significant technical barriers in their industrial-scale production. The multi-enzymatic preparation systems for these compounds inherently accumulate complex impurities, including protein-based catalysts, residual substrates, and oligosaccharide by-products, posing persistent challenges in product separation and biocatalyst recycling. To address this limitation, we conducted a systematic investigation of ultrafiltration-based separation strategies during the multi-enzyme-catalyzed synthesis of fructose-1,6-bisphosphate (FDP), with particular emphasis on membrane fouling mechanisms. By screening the ultrafiltration membranes, UE020 showed the best performance in the model system, achieving significant separation targets: 99.97% retention of bovine serum albumin, FDP/maltodextrin separation coefficient of 7.41, and FDP recovery of 93.63%. An analysis of the components of resistance revealed that concentration polarization induced by maltodextrin was the main factor constituting the resistance, irreversible resistance due to bovine serum albumin was a secondary effect, and the resistance constituted by FDP was negligible. A mitigation strategy employing powdered activated carbon for dynamic membrane formation significantly improved system performance, reducing irreversible resistance by 59.14% and enhancing flux recovery by 20.85%. In this study, ultrafiltration was strategically employed to achieve efficient separation of FDP and enzyme recovery. Significantly, we deciphered the synergistic fouling mechanisms arising from interactions within the multicomponent system containing phosphorylated sugars, oligosaccharides, and proteins. These findings provide a mechanistic framework for scaling up multi-enzymatic systems dedicated to phosphorylated sugar biosynthesis, effectively bridging the gap between laboratory-scale synthesis and industrial implementation.

Monolithic catalysts have been widely investigated for CO₂ methanation due to their fast mass and heat transfer rate, but the effect of the interaction between the catalyst layer and the monolithic support has been little studied. In this work, Ni/Al₂O₃/SiC monolithic catalysts, Ni/Al₂O₃ powder catalysts and Ni/Al₂O₃/SiC-M catalysts were prepared to explore the effect of Si-Al interaction between the catalyst layer and SiC ceramic for CO₂ methanation performance. Ni/Al₂O₃/SiC exhibited a CO₂ conversion of 53% and a CH₄ specific reaction rate of 0.05 mmol·g^-1·s^-1 under conditions of 0.1 MPa, 400 °C, and a WHSV of 60000 ml·g^-1·h^-1. The CO₂ conversion raised by 0.15-fold and the CH₄ specific reaction rate raised by 0.25-fold compared to Ni/Al₂O₃ with the same catalyst content. SEM, XRD, Raman, and other characterization results revealed that the formation of Si-Al interaction between the catalyst layer and SiC ceramic could weaken the interaction between Ni and Al₂O₃, thereby improving the catalytic activity of Ni/Al₂O₃/SiC catalyst. However, the Si-Al interaction was further strengthened during the high-temperature reaction process, which significantly weakened the interaction between Ni and Al₂O₃, thereby leading to a decline in the catalytic performance of Ni/Al₂O₃/SiC catalyst during an 80-h stability test. This study provides valuable insights for future research and development of monolithic catalysts.

The use of amine-based absorbers, such as N-methyldiethanolamine (MDEA), for CO₂ capture presents a promising strategy for emission reduction as global warming intensifies. However, high energy consumption and limited absorption/desorption efficiencies constrain its application. To address these challenges, this study developed a composite catalyst derived from fly ash (FA), which is alkali-modified and incorporates nickel (Ni) and iron (Fe) elements, with the aim of enhancing CO₂ absorption and desorption performance while reducing energy consumption. Experimental results indicated that the Ni/FA-AM catalyst significantly improved adsorption and absorption efficiencies, achieving an 8% increase in capacity, a 63% increase in peak adsorption rate, and a reduction of 6000 s in saturation time. Studies conducted in a wetted-wall column revealed that the absorption process predominantly occurs in the liquid phase. Additionally, the catalyst demonstrated a 19% improvement in desorption performance, a 10% increase in peak desorption rate, and a 24% reduction in energy consumption, while maintaining stability over five consecutive cycles. The alkali-modified and Ni/Fe-enriched fly ash was confirmed to form active acid-base sites, facilitating the formation and disappearance of bicarbonate, thereby enhancing CO₂ capture efficiency. This was validated through XRD, BET, TPD, PY-IR, TEM, and FT-IR with ¹³C NMR characterization. This study highlights the potential of modified fly ash as a low-cost and efficient catalyst for CO₂ capture.

Using thermogravimetric experiments, the kinetic characteristics of magnesite thermal decomposition were investigated under the condition of 10% (vol) CO₂ in the actual production atmosphere of an entrained-flow dynamic roasting furnace. Based on a multi - method collaborative framework, the three kinetic factors in the magnesite thermal decomposition process were systematically calculated through parameter cross - verification between the Hu - Gao - Zhang integral method and the Kissinger differential method. The kinetic mechanism was initially screened by the double equal and double step method and further determined by combining with the Malek maximum probability method. The study revealed that CO₂ in the atmosphere exerts an inhibitory effect on the decomposition of carbonate species within magnesite. Furthermore, the presence of impurities (e.g., calcium carbonate) was found to interfere with the determination of reaction mechanisms via Malek's method at elevated temperatures. The results show that in a 10% (vol) CO₂ atmosphere, the main decomposition temperature of magnesite ranges from 550°C to 650 °C, the average activation energy is 66.00 kJ·mol^-1, the pre-exponential factor is 1.05 × 10⁵ s^-1, and the decomposition process conforms to the random nucleation and growth model.

This study synthesizes and evaluates a novel polysulfone-based membrane doped with graphene oxide-polyethyleneimine-silicon oxide (GO-SiO₂-PEI), specifically designed for oily water treatment applications. The functionalization of graphene oxide with SiO₂ and PEI was rigorously confirmed through comprehensive XRD, FTIR, Raman spectroscopy, and XPS analyses, ensuring the integrity and expected functionality of the nanocomposite. This nanocomposite was integrated into the polysulfone (PSF) membrane matrix, significantly reducing the membrane's inherent hydrophobicity and propensity for fouling. The membranes were meticulously characterized using advanced surface and bulk sensitive apparatus including contact angle and SEM imaging to ascertain their structural and functional attributes. Performance evaluations conducted in a dead-end filtration setup revealed that incorporating 1.0% (mass) of the nanocomposite into the PSF membrane markedly enhanced its porosity and improved the water contact angle. This modification led to an 809% increase in the membrane's water flux and a 57% enhancement in flux recovery rate, while still maintaining a high oil rejection rate and a relatively low leaching rate of 5.3 mg·L^-1. Analysis through the Owens-Wendt-Kaelble model indicated a significant increase in polar surface energy, corroborating the improved oil rejection capabilities at elevated flux levels. Fouling behavior, analyzed using Hermia's model, identified cake formation as the primary fouling mechanism in most of the tested membranes. Leaching tests further highlighted those membranes with higher nanocomposite loadings exhibited increased leaching rates, suggesting a trade-off between performance enhancement and material stability.

Recovery of sulfur from efficient reduction of effluent SO₂ is of great significance considering the sulfuric resource utilization and environmental protection. Herein, a kind of mesoporous MoS₂-Al₂O₃ catalyst with high specific surface area and porous structure was developed by a modified one-pot evaporation induced self-assembly (EISA) method, using Pluronic P123 (M = 5800) as template reagent and anhydrous ethanol as solvent. The effect of Mo source, acidic environment and amount of citric acid additive on the physicochemical properties and consequential catalytic performance was systematically investigated by XRD, BET, ICP-OES, TEM, H₂-TPR and XPS. The specific surface area and sulfurization of catalyst could be remarkably enhanced with the increasing amount of citric acid additive. While the degree of sulfidation is closely related to the catalytic activity. As a result, the 10%MoS₂-Al₂O₃-AM catalyst with mesoporous structure showed excellent catalytic performance on the SO₂ reduction to sulfur, with 98.5% SO₂ conversion and 95.3% sulfur selectivity at 350 °C and 3000 h^-1. It should be helpful for the design of effective catalysts used in SO₂ recovery.

To effectively enhanced structural stability and cycling performance, a dual carbon protection strategy is proposed to fabricate Si nanoparticles encapsulated in citric acid (CA)-derived inner carbon layer and zeolitic imidazolate framework-67 (ZIF-67) derived outer carbon layer (Si@C-CA@c-ZIF). The results reveal that citric acid-derived carbon facilitates a uniform ZIF-67 coating on the Si surface and serves as the inner carbon precursor to reduce volumetric expansion of Si particles, more importantly, it can enhance the transport of electrons and ions between Si particles and ZIF-67-derived carbon. The ZIF-67-derived outer carbon layer further restricts Si particle expansion and enhances conductivity. Evaluated as anode material for lithium ion batteries, the Si@C-CA@c-ZIF anode demonstrates outstanding lithium storage performance, the high specific capacity is high to 924 mA·h·g^-1 at 1.0 A·g^-1 after 10 cycles of activation, and it still maintains a reversible capacity of 703.3 mA·h·g^-1 after 1000 cycles, along with a capacity retention of 76.1%. This work highlights the effectiveness of the dual carbon framework in addressing the volume expansion and conductivity limitations of Si, with potential applications for other high-capacity anode materials.

In response to the accelerating demands of industrial development, the scale-up of stirred reactors has become increasingly prevalent. Multi-shaft stirred reactors have emerged as a promising solution; however, a critical challenge remains in achieving efficient mixing while simultaneously minimizing energy consumption. Here, a novel approach based on differential rotation speeds to optimize mixing performance was proposed. Results demonstrate that a carefully configured rotation speed difference significantly enhances mixing efficiency, reducing mixing time by 17.89% and power consumption by 12.07%. This strategy not only amplifies flow field instability but also minimizes instability discrepancies, promoting a more uniform distribution of vortices across various scales. Furthermore, under this approach, the bottom impeller has the strongest impact on mixing, while the middle and lower impellers synergistically strengthen the weaker mixing regions and facilitate the redistribution of energy in the flow field. This method promotes efficient energy transfer from large-scale to small-scale vortices, ultimately improving overall mixing performance. This work offers a promising avenue for the optimal design and operation of multi-shaft stirred reactors, advancing both efficiency and energy sustainability.

Membrane-based vapor permeation (VP) is regarded as a highly efficient technology, featuring low energy consumption and free salt fouling. In this study, we have demonstrated upscaling chabazite (CHA) zeolite membranes on the 19-channel α-Al₂O₃ monolithic supports synthesized from high-silica gel (SiO₂/Al₂O₃ ratio of 200) for the dehydration of acetic acid by VP. The monolithic membrane presents higher surface-to-volume ratio and a-tenfold greater mechanical strength compared to tubular ones. The micromorphology and crystallinity of the monolithic CHA zeolite membranes were characterized by scanning electron micrographs and X-ray diffraction analysis. The single-gas permeation test and the effects of temperature, feed water content and feed flow rate on the VP separation performance of monolithic CHA zeolite membrane for dehydration of acetic acid were investigated. Moreover, the stability test of monolithic CHA zeolite membranes was carried out. The 19-channel monolithic membrane achieved a comparable separation performance (water flux of 0.63 kg m^-2·h^-1 and selectivity of 369 at 393 K) with the reported small-area zeolite membranes in water/acetic acid mixtures. It is demonstrated that the monolithic CHA zeolite membranes could be transformative candidates for industrial dehydration of acetic acid under harsh environments.

The high-acidity vanadium-containing solution contains high concentrations of iron and aluminum with pH around 0.5, the ketoxime extractant with the active ingredient of 2-hydroxy-5-nonylacetophenone oxime (HNAO, HL) was proposed to extract vanadium from the solution. Under the phase ratio (O/A) of 1:2, HNAO concentration of 0.542 mol·L^-1 at 25 °C for 10 min, 99.06% of vanadium was extracted after a three-stage countercurrent extraction, while the extraction of impurities was less than 1%, with the separation coefficients of vanadium from iron and aluminum were 137050 and 43197, respectively. The antioxidant properties of the extractant were studied. At 25 °C, the extractant basically did not undergo oxidative degradation. Besides, about 91.2% of the loaded vanadium was effectively stripped using 2.5 mol·L^-1 Na₂CO₃ solution. The extraction mechanism of vanadium was investigated through the slope analysis method, the spectral characterizations and density functional theory calculations. It has been observed that VO₂⁺ substitutes the H atom on the phenolic hydroxyl and coordinates with the N atom on the oxime and the O atom on the phenolic hydroxyl to form of a six-membered ring, and the extraction complexes were determined to be VO₂(H₂O)L and VO₂L.

The formation, evolution and modelling of organized flow structures (e.g., segregated regions and centre-surface vortices) and their destruction in unbaffled stirred tank reactors (UBSTRs) have been a hot research topic in the field of fluid mixing. In this paper, the relevant researches in the past 30 years were reviewed, focusing on the application of asymmetric mixing. In particular, by drawing on chaotic phenomena in nature and human society (e.g., kneading-dough, traffic flow, frightened school of fish), we propose a fluid mixing mechanism: squeezing-induced chaotic mixing, and further propose a bionics-imitation-simulation design concept for UBSTRs. This concept is also an important inspiration for the design of other chemical reactors.

Emulsions are widely used across various industries but often require surfactants for stabilization, leading to complex product formulations and environmental concerns. Continuous preparation of stable emulsions without surfactants is still a significant challenge. Herein, a secondary membrane emulsification system was developed to produce stable oil-in-water emulsions under surfactant-free conditions, where the first membrane module employed the cross-flow membrane emulsification to generate the primary emulsion, while the second membrane module employed the premix membrane emulsification to further reduce the droplet size, thereby improving the emulsion stability. The morphology and droplet size of the secondary emulsion significantly depend on the membrane pore size, membrane surface wettability, primary emulsion flow, and primary emulsion quality. The secondary membrane emulsification system demonstrates excellent operational stability over 12 h, with no obvious changes in the emulsion characteristics. The prepared secondary emulsion remains relatively stable up to 10 min without surfactants, significantly superior to the primary emulsion. Furthermore, the developed system successfully produces the Janus emulsion with homogeneous internal phase morphology. This research provides an effective approach for the continuous preparation of stable emulsions without surfactants.

Excessive fossil fuel use has increased carbon dioxide (CO₂) emissions, driving climate change and ocean acidification. This review evaluates the potential of higher alcohols as fuels for carbon circularity, comparing their properties, energy efficiency, and technology readiness with hydrogen, methane, and methanol. Higher alcohols, produced via CO₂ hydrogenation, exhibit advantages such as liquid-phase storage, higher energy density, and safer handling. Additionally, their clean combustion produces fewer pollutants like CO and NO_x. However, CO₂ hydrogenation to higher alcohols faces challenges, including high energy demands, kinetic barriers, and immature production technologies, resulting in lower energy efficiency compared to H₂, methane, and methanol. Higher alcohols, with their superior energy density and safety, hold promise as sustainable fuels, particularly when integrated with CO₂ capture technologies. However, improvements in catalyst performance, process integration, and production scalability are critical for their widespread adoption.

The emerging two-dimensional (2D) membranes offer a promising way to improve the water desalination performance of traditional membranes. MXene/graphene oxide (GO) composite membrane are known for their high separation performance and structural stability. In this study, molecular simulations are performed to investigate the desalination performance of the 2D MXene/GO membrane. The results reveal that the surface of the MXene nanosheet could induce the formation of ordered water structures, thereby accelerating the water transport in the 2D membrane. The higher rejection rate would be found in MXene/GO membrane with a larger GO oxidation degree owing to the steric-hindrance effect induced by the functional groups on the GO surface. Overall, the MXene/GO(20) membrane with the interlayer spacing of 0.9 nm shows the highest water permeability (37.22 × 10^-7 L·m^-1·h^-1·bar^-1, 1 bar = 0.1 MPa) and a salt rejection of 100%. The results could provide theoretical insights for developing 2D membranes for water desalination.

High phosphorus content in sewage sludge (SS) significantly affects the ash fusion temperature during the co-gasification of coal with SS. However, the mechanisms underlying the effects of phosphorus on the ash melting behavior remain unclear. In particular, there is no direct evidences to confirm that refractory mineral dissolution processes are affected by the phosphorus-bearing liquid phase formed during the initial stage of ash melting. In this study, different amount of calcium- and iron-phosphates were added to coal to investigate the effect of phosphorus on the coal ash fusion temperature. The phosphorus and mineral phase transformations, as well as the dissolution processes of refractory mullite particles in the phosphorus-bearing liquid phase, were determined using X-ray photoelectron spectroscopy, X-ray diffraction analysis, thermodynamic equilibrium calculations, and thermal platform microscope systems. The results indicated that the addition of 8% calcium-phosphate and iron-phosphate reduced the ash flow temperature (FT) from above 1500 °C to 1336°C and 1261 °C, respectively. The effect of iron-phosphate on the reduction of ash FT was more pronounced than that of calcium-phosphate. The phosphorus vaporization ratio increased with the temperature. Approximately 50% of phosphorus was retained in the samples to which 8% of calcium-phosphate and iron-phosphate were added at 1400 °C. Elevation of the temperatures promoted the conversion of PO₄^3- to molten slag-dissolved P₂O₅. The mechanism whereby phosphorus reduces the ash FT is primarily governed by the dissolution of refractory minerals in the liquid phase formed during the initial heating stage. This dissolution process was enhanced in the presence Fe compared to that in the presence of Ca.

Understanding the structure of coal is helpful to understand the diverse reactivity of coal at a molecular scale and offer support for clean and effective utilization of coal. The physical properties of a typical coal from east of Ningxia were characterized by some analysis methods such as elemental analysis, FT-IR, XPS, and ¹³C NMR. And the key parameters of the microstructure of the coal sample were obtained such as the type, valence and chemical bond and so on. The molecular composition of coal has been established as C₂₀₂H₁₅₃O₃₈N₃S₂, and a three-dimensional representation of its molecular structure was created. The molecular dynamics approach utilizing reactive force fields was employed to model the process of coal gasification. The influence of reaction force fields and temperature on coal gasification process were investigated, and the main small molecule products in different atmospheres were tracked. It was indicated that the consumption and consumption rate of raw coal and the production of primary products increased with increasing of the temperature. All carbon elements in coal were converted into fragments with less than three carbon atoms at the H₂O atmosphere and 3500 - 4000 K, and the C₁ content can reach 97.73% at 4000 K. It was proved indirectly that the gasification reaction process had been completed. In mixed atmospheres, the gasification condition closest to industrial scenarios was 500H₂O + 1500CO₂, yielding a CO/H₂ ratio of 3.52, matching actual outcomes. Molecular dynamics simulation of gasification process based on coal macromolecules is conducive to reveal gasification reaction mechanism.

The polycarbonate (bisphenol A)/acrylonitrile-butadiene-styrene (PC/ABS) features excellent mechanical properties, but its high flammability poses a potential safety hazard in practical applications. Although the incorporation of halogen-free additives enhances flame retardancy, it often leads to substantial smoke emission and compromises the mechanical properties of PC/ABS alloy. Therefore, simultaneous enhancement of both flame retardancy with low smoke and mechanical properties holds significant practical value for material development. Herein, a low-smoke PC/ABS composite with balanced flame retardancy and mechanical properties was achieved through an efficient ternary flame retardant system containing bisphenol A bis(diphenyl phosphate) (BDP), potassium-4-(phenylsulfonyl) benzenesulfonate (KSS), and 3-glycidyloxypropyltrimethoxysilane-modified boehmite (m-BM). PC/ABS/BDP6/KSS2/m-BM2 can achieve the same flame retardant level (V-0) as PC/ABS/BDP14, and the limiting oxygen index is increased to 26.8%. Meanwhile, the tensile strength and impact strength are increased by 16.1% and 81.4% respectively. The ternary system can significantly inhibit the release of smoke and heat, under the same flame retardant load (10% (mass)), the total heat release and total smoke production of PC/ABS loaded with ternary flame-retardant system decreased by 18.1% and 21.9% respectively compared to only BDP loaded. This ternary flame-retardant system provides a practical solution for developing high-performance, low-smoke flame-retardant PC/ABS composites.

With the increasingly stringent national environmental protection policies, the ultra-low emission transformation of industrial coal-fired grate boilers and the highly efficient utilization of biomass resources or wastes are becoming increasingly urgent in China. This study first proposes a novel and simple configuration for industrial grate boilers to integrate the decoupling combustion and flue gas recirculation or co-firing technologies, so as to reduce pollutant emission but improve thermal efficiency. Burning coal briquettes in the novel grate boiler, the original NO_x emissions can be remarkably decreased to as low as 56 mg· m^-3, corresponding to the reduction efficiency of 82.8% in comparison with the average value in traditional coal-fired grate boilers. Co-firing coal briquettes with straw pellets in the novel grate boiler, the strongest synergistic effect of NO_x reduction is observed at the blending mass fraction of 50%, in which the NO_x emissions can be further mitigated by at most 16.0% on top of the already reduced amount by decoupling combustion to reach less than about 165 mg· m^-3. The novel grate boiler allows co-firing Chinese medicine residue with high water content at the blending mass fraction of up to 30% on the premise of low NO_x and CO emissions. All experimental results in this study demonstrated the obvious superiorities of the novel grate boiler in reducing NO_x and CO emissions and mitigating both slagging tendency and slag carbon content, which can be attributed to either the cumulative effects of decoupling combustion with flue gas recirculation or the synergistic effects of co-firing coal-biomass blends. The newly-developed travelling-grate decoupling combustion technology can be expected to provide an economical and convenient measure for the ultra-low NO_x emission transformation of industrial coal-fired grate boilers as well as the clean and highly efficient consumption of biomass wastes with high water content or difficulty to burn in China.

In this study, a facile and effective hydrothermal approach was developed to synthesize magnesium oxide loaded aeolian sand (MOAS) with a high loading ratio as an environmentally friendly adsorbent for effective removal of fluoride from wastewater. The analysis of material morphology and structure revealed that the MOAS has a stacked structure and the magnesium oxide is successfully loaded on the surface of aeolian sand with high loading ratio (230%). The adsorption kinetics demonstrated that the adsorption of fluoride by MOAS followed the pseudo-second-order model. The adsorption isotherm conformed to the Redlich-Peterson model with a saturated adsorption capacity of 153.11 mg·g^-1. MOAS exhibited excellent defluorination performance over a wide pH range and in the presence of competitive anion, respectively. The density functional theory (DFT) theoretical calculations verify that the MOAS has strong affinity for fluoride. The adsorption mechanism was investigated through FTIR and XPS, revealing that hydroxyl exchange and coordination on the surface were responsible for the defluorination of MOAS. Finally, desorption, regeneration, adsorption column experiments and actual wastewater experiment further confirmed the practical potential of MOAS for defluorination applications.

Lithium extraction from salt lakes has become an environmentally friendly way of lithium acquisition. The development of new nanofiltration membrane is significant to enhance the separation efficiency of lithium from a high Mg²⁺/Li⁺ mass ratio brine. In this work, Fe³⁺/tannic acid-trimesoyl chloride-polyetherimide (Fe³⁺/TA-TMC-PEI) composite nanofiltration membranes were designed to study the separation performance of Mg²⁺/Li⁺ in a high Mg²⁺/Li ⁺ mass ratio simulated brine. Fe³⁺/TA separation layer was introduced through the rapid assembly of tannic acid and coordination mediated by Fe³⁺ on polyethersulfone supporting membrane. The polyamide layer was prepared through the reverse interfacial polymerization between TMC and PEI. The composite nanofiltration membrane has high cross-linking degree and positive charge and low pore size. The best performance of the composite nanofiltration membrane was obtained with 0.3% (mass) Fe³⁺ solution, 0.9% (mass) TA, and 2 g·L^-1 PEI 600 ethanol solution. The retention of bivalent ions was significantly greater than that of monvalent ions in single salt solution. The Fe³⁺/TA-TMC-PEI composite nanofiltration membrane showed a stable separation factor of 12.02 when the Mg²⁺/Li⁺ mass ratio was 120 in the mixed salt solution. This work deepens the understanding of the mechanism of lithium extraction in magnesia-lithium system, and the modification strategy provides a possible guide for the design of Mg²⁺/Li⁺ separation membranes with practical potential from the perspective of lithium extraction technology.

To address the critical need for safer and cleaner explosion suppression technologies in industrial settings, the suppression differences and mechanisms of the flame acceleration characteristics of CH₄, LPG and H₂ explosions by N₂-water mist two-phase medium were investigated. The flame acceleration characteristics and suppression mechanism of methane, LPG and H₂ explosions in N₂-water mist two-phase medium were studied qualitatively and quantitatively from both experimental and simulation aspects. The experimental results show that compared with single N₂ or water mist, the N₂-water mist two-phase medium is more effective in reducing the flame propagation speed and delaying the formation of flame hydrodynamic structure, thus slowing down the flame acceleration characteristics. The simulation results show that this two-phase medium exhibits a strong inhibitory effect on the thermal diffusion instability of CH₄ and LPG, and significantly weakens the hydrodynamic instability of CH₄, LPG, and H₂ simultaneously. Mechanistic analysis confirms that the N₂-water mist two-phase medium has both chemical and physical inhibitory effects, among which the physical inhibition plays a dominant role. In addition, the study reveals a linear correlation between the concentration of H radicals in the three combustible gases and the laminar burning velocity. Moreover, this two-phase medium can significantly reduce the reaction rate of the H radical chain reaction, thereby effectively suppressing the laminar burning velocity.

Accurate prediction of wastewater treatment plants (WWTPs) influent quality can provide valuable decision-making support to facilitate operations and management. However, since existing methods overlook the data noise generated from harsh operations and instruments, while the local feature pattern and long-term dependency in the wastewater quality time series, the prediction performance can be degraded. In this paper, a discrete wavelet transform and convolutional enhanced Transformer (DWT-CeTransformer) method is developed to predict the influent quality in WWTPs. Specifically, we perform multi-scale analysis on time series of wastewater quality using discrete wavelet transform, effectively removing noise while preserving key data characteristics. Further, a tightly coupled convolutional-enhanced Transformer model is devised where convolutional neural network is used to extract local features, and then these local features are combined with Transformer's self-attention mechanism, so that the model can not only capture long-term dependencies, but also retain the sensitivity to local context. In this study, we conduct comprehensive experiments based on the actual data from a WWTP in Shaanxi Province and the simulated data generated by BSM2. The experimental results show that, compared to baseline models, DWT-CeTransformer can significantly improve the prediction performance of influent COD and -N. Specifically, MSE, MAE, and RMSE improve by 78.7%, 79.5%, and 53.8% for COD, and 79.4%, 70.2%, and 54.5% for -N. On simulated data, our method shows strong improvements under various weather conditions, especially in dry weather, with MSE, MAE, and RMSE for COD improving by 68.9%, 48.0%, and 44.3%, and for -N by 78.4%, 54.8%, and 53.2%.