Pyrolysis can effectively recover glass fibers from end-of-life wind turbine blades (WTBs) while producing reusable pyrolysis oil and syngas. The nonlinear dynamics involved in the pyrolysis of end-of-life WTBs bring challenges in accurately predicting the product distribution. This paper proposes an attention-based feature fusion prediction framework for pyrolysis product distribution of end-of-life WTBs. Firstly, a physics-informed neural network (PINN) incorporating the Arrhenius equation is proposed. Then, a product distribution prediction model for the fast pyrolysis of end-of-life WTBs is developed by integrating the extreme gradient boosting algorithm, multilayer perceptron, and the PINN, with an attention mechanism introduced to dynamically weight their output. Based on this, a dynamic weighted feature fusion algorithm is proposed to predict the pyrolysis product distribution of end-of-life WTBs. Finally, the superiority of the proposed method is demonstrated through fast pyrolysis experiments of end-of-life WTBs. The experimental results show that the proposed method achieves a notable improvement in prediction accuracy, reducing the root mean square error and mean absolute error by 86% to 99% compared to existing approaches.

Accurate prediction of tray hydrodynamics is essential for the design and optimization of modern distillation equipment. Conventional empirical correlations often show limited generalizability across diverse operating conditions, restricting their practical applicability. In this study, a data-driven modeling (DDM) framework integrated with Interpretable machine learning (ML) was developed to predict the hydrodynamic characteristics of a divided fixed-valve tray, including wet pressure drop, clear liquid height, weeping rate, and entrainment rate. A total of 760 experimental data points were obtained from cold-model experiments. Four machine learning algorithms―Random Forest, Extreme Gradient Boosting, Support Vector Regression, and a shallow Multilayer Perceptron―were trained and compared. Model performance was evaluated using the coefficient of determination (R²), root mean square error (RMSE), and a composite R²-based index (R_com). Among these, the SVR model achieved the highest predictive accuracy, with R_com values of 0.9750 and 0.9834 for the test and extension sets, respectively. Building upon the best-performing SVR model, an expanded feature set was constructed using physically informed transformations of the orifice kinetic energy factor and overflow strength. Pearson correlation and SHAP analyses were applied to quantify each feature's contribution, revealing the dominant hydrodynamic drivers and clarifying their positive or negative influences on tray behavior. The integrated modeling and interpretability framework not only enhances predictive reliability but also provides actionable insight for guiding tray design and operational optimization.

Proton exchange membrane water electrolyzers (PEMWEs) are considered a core technology for high-purity hydrogen production and renewable energy integration. Their performance and durability are strongly governed by electrode microstructural design. To address systematic studies on the role of the microporous layer (MPL) in electrolyzers gap, we develop a two-dimensional, two-phase, multiphysicscoupled model to investigate how MPL location, thickness, porosity, and wettability affect electrolysis performance, oxygen distribution, and the pressure difference across the membrane. The results show that the effect of the anode MPL is significantly stronger than that of the cathode, effectively improving oxygen distribution uniformity by 16.3%, reducing liquid water saturation at the anode, and optimizing gas—liquid co-transport. Increasing the MPL thickness markedly enhances the oxygen mole fraction in the catalyst layer and improves distribution uniformity; however, excessive thickness or extreme hydrophobicity/hydrophilicity leads to performance deterioration. More importantly, the presence of the anode MPL reduces the transmembrane gas pressure difference by up to 50%. In addition, the thickness, porosity, and hydrophobicity synergistic optimization can improve efficiency while enhancing safety and durability at high current densities. The optimal AMPL parameters are proposed as the thickness of 50—90 μm, contact angle of 80◦, and porosity of 0.2—0.3. This study provides theoretical insights and practical guidance for electrode microstructural design in PEMWEs, with important implications for large-scale applications.

Biochar-based catalysts show significant potential to replace toxic mercuric chloride in acetylene hydrochlorination. However, the mechanistic role of their non-metallic active sites remains scarcely investigated, particularly regarding the synergistic interplay between pore architecture and surface functionalities. Herein, a series of biochar based catalysts with rich microstructures were successfully prepared by using molten salt as medium, which were used in acetylene hydrochlorination. The method of preparing biochar by liquid medium of molten salt was optimized by adjusting the ratio of terpolymer salts, mesh number, constant temperature duration, reaction temperature and heating rate, etc. The materials were analyzed byBET, XRD, TGA, SEMand TEM. The results showed that the biochar materials had abundant pore structure and adjustable pore volume, and it was found that biochar with larger pore volume showed higher acetylene hydrochlorination conversion at the same pore size of 1.8 nm. Analysis suggests that biochar with large pore volume has more carbon “chambers” at the micropore size, which effectively promotes the “one-to-one” pairing of C₂H₂ and HCl molecules. This work found that the catalytic performance of acetylene hydrochlorination could be improved effectively by microstructural regulation of non-metallic catalysts.

Aqueous zinc-ion batteries (AZIBs) have emerged as a promising alternative in the field of energy storage due to their lower cost, enhanced safety, and environmental friendliness. However, the development of efficient and stable cathode materials remains a significant challenge. In this work, the MnO nanoflower network anchored on a two-dimensional lamellar carbon (MnO NN/LC) was synthesized via metal-organic framework-derived method. The lamellar carbon serving as the 2D conductive matrix facilitates faster ion diffusion and electron transfer, resulting in superior zinc storage performance. MnO NN/LC displays larger reversible capacity, superior rate capability, and much higher cycling stability compared to traditional bulky MnO/C (B-MnO/C) material. Especially, the MnO NN/LC demonstrates long-term cycling stability with the retained capacity as high as 104.2 mA·h·g^{- 1} after 1400 cycles at 1 A·g^{- 1}, presenting substantial enhancement over the capacity of 75.7 mA·h·g^{- 1} for B-MnO/C. Ex-situ experiments indicate that MnO during the zinc ion storage is electrochemically oxidized into MnO₂ species, and actually facilitates the intercalation/deintercalation of H⁺ and Zn²⁺. These findings underscore the potential of the MnO NN/LC composite as a promising cathode material for AZIBs.

Addressing energy crisis and environmental issues, fixing carbon dioxide (CO₂) into value-added cyclic carbonates via cycloaddition reactions is the most energy-efficient technology for overcoming the chemical and thermodynamic stability of CO₂. Herein, we report a robust fluorine-modified nanoporous framework of {[Sn₂(F₂-TPTA)₂(H₂O)₂]·3DMF}n(NUC-165) (F₂-H₄TPTA= 2′,3′-difluoro-[1,1':4′,1′′-terphenyl]-3,3′′,5,5′′-tetracarboxylic acid). In NUC-165, scarcely reported binuclear clusters of [Sn₂(COO)₈(H₂O)₂] unit are propagated via fluorine-functionalized organic modules of F₂-TPTA^4- into a three-dimensional structure with a void volume of 45.2%, which displays three kinds of windows:0.63 nm ×0.90 nm, 0.62 nm ×0.92 nm, and 0.65 nm ×0.6 nm along a, b and c axis. Interestingly, strong electron-withdrawing fluorine atoms are richly distributed the inner surface of the formed void volumes in the thermal activated NUC-165a, resulting in a Lewis acid-base functionalized hybrid material. Performed catalytic experiments confirmed that NUC-165a with the aid of n-Bu₄NBr cocatalyst could highly catalyze the cycloaddition of CO₂ with epoxides under relatively mild conditions (P_{CO2=0.9 MPa and T = 80 ◦C), which should be due to that rich open Sn⁴⁺ sites and electron-withdrawing fluorine groups could separately activate the substrates of epoxides and CO2. In addition, Knoevenagel condensation of aldehydes and malononitrile also could be catalyzed, which should be because open Sn⁴⁺ sites and electron-withdrawing fluorine groups could activate aldehydes and malononitrile, respectively. Therefore, this work may provide an insight into improving the specific performance of microporous MOFs through pre-functionalization on employed organic modules.}

This study presents a systematic approach for synthesizing hierarchical bio-NaY zeolite using rice huskderived silica (bio-SiO₂) as structural and compositional templates. The incorporation of bio-SiO₂ significantly increases mesoporous volume and optimizes the distribution of Lewis acid-base pairs within the zeolite framework. Comparative analysis demonstrates a marked improvement in CO₂ adsorption capacity for the bio-NaY zeolite (147.3 mg·g^{- 1}) over conventional NaY (138.3 mg·g^{- 1}). ZLC experimental results reveal that this enhancement is attributed to a dual mechanism: (i) the bio-SiO₂ template promotes the formation of a hierarchical pore system, improving mass transport; and (ii) it enhances the accessibility and exposure of active sites, facilitating CO₂ capture and intraparticle diffusion. Molecular dynamics simulations further reveal that the (100) crystallographic plane exhibits superior CO₂ adsorption affinity, kinetics, and selectivity compared to the (001) plane. Additionally, the integration of 3D printing technology enables the fabrication of mechanically robust monoliths (3D-bio-NaY), simplifying adsorbent handling and regeneration. These 3D-printed structures exhibit exceptional cyclic stability, retaining nearly 100% of their initial CO₂ capture capacity over eight consecutive cycles. The findings provide deep insights into the structure-property relationships of hierarchical zeolite and advance the design of efficient adsorbents for industrial CO₂ capture applications.

Surface modification of titanium dioxide (TiO₂) with transition metals is a feasible solution to enhance its ability to activate peroxymonosulfate (PMS) for environmental remediation. In this study, a novel composite catalyst comprising nano-CuS₂ and Cu₂O decorated anatase-TiO₂ (CuS₂-Cu₂O/TiO₂) was successfully synthesized via a hydrothermal method using thiourea as the sulfur source. The CuS₂-Cu₂O/TiO₂ catalyst exhibited excellent performance for the degradation of chloroquine phosphate (CQ) through a photo-assisted PMS activation process, achieving 99% removal efficiency within 10 min under UV irradiation. The effects of PMS dosage and solution pH on CQ degradation were investigated in detail. Mechanism studies, including active species quenching experiments, electron paramagnetic resonance (EPR), and electrochemical analysis, revealed that the redox cycling of Cu⁺/Cu²⁺ within the CuS₂-Cu₂O domains and the efficient photo-induced electron transfer derived from TiO₂ are the key steps in PMS activating. Reactive species, such as photogenerated holes (h+), hydroxyl radicals (·OH), and singlet oxygen (¹O₂) played essential roles in the oxidative degradation of CQ. Furthermore, liquid chromatography—mass spectrometry (LC—MS) analysis enabled the identification of intermediate products, based on which two plausible degradation pathways of CQ were proposed. This work demonstrates the feasibility of photo-assisted PMS activation for the removal of pharmaceutical pollutants and provides insights into the rational design of TiO₂-based composite photocatalysts for wastewater treatment.

Biomass valorization via electrosynthesis offers an eco-friendly route under mild conditions. Herein, propionic acid from 1-propanol was produced on nickel hydroxide electrodes (Ni(OH)₂/NF) using the 1propanol precursor in a diaphragmless electrolytic cell. Systematic optimization of key operational parameters―including current density, NaOH concentration, 1-propanol concentration, and reaction time―was carried out to maximize product efficiency. Under optimal operating conditions (0.35 mol·L^{- 1} of 1-propanol, 0.5 mol·L^{- 1} of NaOH, 40 mA·cm^{- 2} of current density and 5 h of reaction time), this multivariate strategy achieved a Faradaic efficiency of 94.11% and a yield of 70.42% for propionic acid. Notably, scalability was validated through gram-scale synthesis in a single batch, producing tens of grams of propionic acid and highlighting the practical viability of the diaphragmless configuration. Combined electrochemical analyses and density functional theory (DFT) calculations elucidate the reaction mechanism, revealing that Ni(OH)₂/NF facilitates the dehydrogenation and oxidative coupling steps critical to selective propionic acid formation. This study not only establishes a green and efficient route for value-added chemical production from biomass-derived alcohols but also demonstrates the industrial potential of diaphragmless electrolytic systems.

Phosphogypsum (PG) is a solid waste generated by the phosphate fertilizer industry. The decomposition of PG allows for the separate recovery of its Ca and S resources. In this work, the decomposition of PG and formation of minerals in the preparation of sulfoaluminate cement (SAC) were studied. Thermodynamics analysis reveals that the formation of SAC minerals accelerates the decomposition of PG by incorporating CaSO₄ and CaO into the reaction matrix. Experimental results revealed that the formation of SAC minerals effectively reduces the decomposition temperature of PG and increases its decomposition rate. The formation of C₂S has the strongest promoting effect on the decomposition of PG. The formation of generally has a weaker effect in promoting PG decomposition. In contrast, the formation of C₄AF and composite minerals not only facilitates efficient PG decomposition but also maintains system stability, preventing melting. The formation of SAC minerals is affected by the decomposition of PG, making it difficult to fully generate the target mineral. The kinetic mechanism of PG decomposition is three-dimensional diffusion reaction, while the mechanism changes to two-dimensional diffusion (cylindrical symmetry) reaction in mineral formation. This study presents novel methodologies for recycling Ca and S resources from PG, paving the way for its efficient utilization.

Mo vacancy (V_Mo) and Se vacancy (V_Se) are doped into Bi₂MoO₆ (BMO) and ZnSe, respectively, while they are mechanically ground and mixed to fabricate the dual S-scheme heterojunction. The lattice distortion is observed at the interface between V_Mo-BMO and V_Se-ZnSe/CdSe (V_Se-ZCS) while XPS results confirm the construction of the dual S-scheme heterojunction V_Mo-BMO/V_Se-ZCS (V_Mo+_Se-BZCS). DFT simulation demonstrate that the doping of V_Mo and V_Se lead to more electrons transferring spontaneously through the heterojunction interfaces and promote the IEF strength accordingly. Both in-situ XPS and fs-TAS characterization prove the presence of a fast photoinduced charge transfer pathway from V_Mo-BMO to V_Se-ZnSe under LED light irradiation. V_Mo and V_Se function as the holes trapping center in V_Mo-BMO and the electron trapping center in V_Se-ZCS, respectively, thereby effectively suppressing the electron-hole recombination, which enhances the redox capability of V_Mo+_Se-BZCS together with the fast charge transferring. During the photocatalytic degradation experiments for the wastewater containing both tetracycline (TC) and Cr(VI), both the TC and the Cr(VI) degradation efficiency of V_Mo+_Se-BZCS are competitive under either LED or xenon lamp irradiation in comparison with some reported catalysts. Dual doping of V_Mo and V_Se were testified to amplify the bi-directional promotion effects (BPEs) between TC and Cr(VI).

Understanding the proton transport mechanisms in polymer electrolyte membranes (PEMs) is crucial for optimizing proton exchange membrane fuel cells. In this study, classical molecular dynamics simulations are employed to systematically investigate the proton transport behavior in three representative membranes: Nafion, sulfonated polyethylene (P21SA), and sulfonated poly (ether ether ketone) (SPEEK). The results reveal that proton transport in Nafion is dominated by the classical hopping mechanism (CHM), facilitated by the extensive free volume, well-connected water channels, and highly dynamic hydrogen-bond network. In contrast, SPEEK exhibits limited free volume and narrow-twisted water channels, which can suppress hydrogen-bond network reorganization. The proton transport in SPEEK is primarily governed by the vehicle mechanism. P21SA shows intermediate features between Nafion and SPEEK, displaying a hybrid transport mechanism. This study establishes direct correlations between nanoscale morphology, hydrogen-bond network dynamics, and proton transport behavior, providing molecular-level insights for the rational design of PEM materials.

Current absorbable sutures face challenges in matching heterogeneous tissue healing timelines, leading to postoperative complications from delayed degradation. Thus, self-biodegradable polycaprolactone/polyurethane (PCL/PU) composite sutures via electrospinning, incorporating Burkholderia cepacia lipase (BCL) stabilized by random heteropolymers (RHP) was developed in this research. RHP can maintain BCL activity retention at 40%—90% in organic solvents. The PCL70/PU30 suture exhibited optimal mechanics (tensile strength was (28.44 ± 1.25) MPa and Young's modulus was (42.43 ± 5.3) MPa), following the incorporation of the BCL-RHP complex, the suture's key mechanical properties were largely maintained and remained within the range compatible with typical suture applications. Enzyme-loading gradients (0.05%—0.5% (mass)) enabled precise degradation control. 0.5% (mass) enzyme-loaded sutures fully disintegrated spontaneously in simulated wound fluid within 15 days, this timeframe aligns with the typical epidermal healing cycle (approximately 2 weeks), suggesting the potential for achieving dynamic degradation-healing synchronization in vivo. In addition, functionalization of self-biodegradable composite sutures was achieved by embedding thymol for synergistic bioactivity. Thymol achieved a cumulative release of 86.76% ± 1.34% over 120 h, endowing the self-biodegradable composite sutures with sustained antioxidant (79.85% ABTS⁺ scavenging rate) and antibacterial activity (significantly suppressing the growth of Staphylococcus aureus). Concurrently, the self-biodegradable composite sutures demonstrated favorable cytocompatibility in L929 fibroblast cell. The RHP-enabled enzyme stabilization strategy overcomes clinical-ecological limitations of conventional sutures, offering programmable degradation and multifunctionality for precision medicine.

Based on density functional theory (DFT) calculations, this study systematically investigates the stability and bifunctional catalytic activity (ORR/OER) of Ytterbium (Yb) dual-atom catalysts anchored on graphene with diverse vacancy defects (including single, double, and quadruple vacancies). Beyond structural screening, our analysis reveals that the specific N/N-N coordination linkage induces a robust synergistic interaction between the adjacent Yb atoms, conferring a distinct intrinsic advantage over single-atom analogues. Furthermore, surface functionalization with axial hydroxyl (OH) ligands is demonstrated to effectively modulate the electronic structure and optimize the adsorption energetics of reaction intermediates. Benefiting from this dual-optimization mechanism involving coordination synergy and surface electronic modulation, the identified candidates deliver exceptional bifunctional performance, achieving ultralow overpotentials of 0.30 V for ORR and 0.28 V for OER. This study provides valuable theoretical guidance for the rational design of efficient rare-earth dual-atom catalysts by leveraging coordination synergy and surface functionalization.

Zeolites are widely used in acetylene semi-hydrogenation to ethylene reaction due to their tunable acidity and ordered crystal porous structure. In this work, zeolites with different structures, including MTW, MFI, BEA, AEL, and MOR, were synthesized and impregnated with Ni. Characterization and performance evaluation of the catalysts were conducted for the acetylene semi-hydrogenation reaction. It was found that all catalysts had a high acetylene conversion rate. The Ni/H-Beta catalyst exhibited excellent catalytic performance at 150 ◦C achieving a 100% acetylene conversion rate and a 58% ethylene yield. The catalyst with BEA topology had the best performance. The results showed that Ni/H-Beta catalysts had large specific surface area and suitable microporous-mesoporous structure facilitate the formation of highly dispersed nickel species with fine particle sizes, and Beta zeolites had a larger proportion of medium and strong Lewis acid sites, which could effectively modify the electronic structure of Ni. This work investigated the efficacy of Ni catalysts supported on zeolites with different topologies for the semi-hydrogenation of high-concentration acetylene.

Integrating refinery planning and product blending scheduling under uncertainty is challenging due to multi-mode operating conditions and mismatched temporal scales. This work proposes a bilevel optimization framework that explicitly coordinates long-term refinery planning with short-term blending scheduling. To represent mode-dependent uncertainty in blending behavior, a data-driven robust optimization (DDRO) strategy is developed, in which mode-associated uncertainty sets are constructed from historical data using a multi-stage clustering (MSC) algorithm combined with weighted support vector machines (SVM). This enables uncertainty modeling that is adaptive to operating modes and less conservative than conventional holistic robust approaches. To solve the resulting bilevel robust model efficiently, a robust-buffer-based decomposition (RBD) algorithm is proposed, which iteratively introduces a specification buffer at the planning level to preserve scheduling feasibility under uncertainty. In the case study, the proposed multi-mode robust framework improves the net profit by approximately 1.0% compared to holistic robust model, while maintaining 100% feasibility in quality constraints and reducing computational time by more than 50% relative to the single-level formulation. These results demonstrate that the proposed framework effectively balances economic performance, robustness, and computational tractability in integrated refinery planning and scheduling.

The dynamic behavior and particle shape effects in the liquid spray zone were investigated through temperature standard deviation, liquid—solid contact efficiency, and electrical conductivity signals. Results indicate that temperature standard deviation increases with proximity to the nozzle. Elevated atomisation gas velocity (U_L) reduces droplet diameter and improves their dispersion, which leads to a more uniform temperature distribution and a resulting decrease in standard deviation. The temperature standard deviation is decreased and then increased with the increasing of fluidized gas velocity (U_f). Non-spherical particles had a higher temperature standard deviation than spherical particles. This resulted from particle agglomeration, where lower sphericity led to stronger fluctuations. The liquid—solid contact efficiency is enhanced with the increasing of spouted gas velocity (U_s), U_L, and U_f all. As the liquid spouted rate (Q_L) increased, the liquid—solid contact efficiency, determined by particle capture of droplets, first rose and then declined. Non-spherical particles exhibit higher liquid—solid contact efficiency than that of spherical particles due to longer residence times, and larger contact areas with droplets. Droplet fluctuations are intense near the nozzle, resulting in high electrical conductivity signal intensity. Increased U_s enhances airflow effects, causing frequent voltage signal fluctuations. Flake-like particles accumulate more droplets due to agglomeration, enabling droplets to reach higher bed positions. These studies provide promising research directions for the development of adsorbent pelletization in CO₂ capture.

5-Hydroxymethylfurfural (HMF) is a highly valuable platform compound derived from cellulose, enabling the synthesis of various premium chemical products through oxidative esterification, including dimethyl 2,5-furanedicarboxylate (FDMC). This process finds widespread applications across numerous industries. By adjusting the Si/Al ratio, we prepared diverse catalyst carriers and utilized the urea precipitation method to fabricate various catalysts with a low gold loading of 1% (mass). These catalysts were subsequently characterized by a range of analytical techniques. Notably, the Au/SiO₂-AlO(OH)-3 catalyst, characterized by its large specific surface area and abundant pore size, facilitated the highly dispersed presence of gold on the catalyst surface, exhibiting the best catalytic performance. Specifically, the Au/SiO₂-AlO(OH)-3 catalyst demonstrated high efficiency, achieving 99.9% HMF conversion and 95.2% FDMC yield at a 0.25 mmol scale of HMF within 6 h under 0.1 equivalent Na₂CO₃. This study proposes a mechanistic scheme for the conversion of HMF to FDMC via Au/SiO₂-AlO(OH)-3-catalyzed oxidative esterification. Furthermore, free radical inhibition experiments were conducted, and the results indicated that superoxide anion radicals play a significant role in the HMF oxidative esterification reaction. We also performed a series of substrate extensions, confirming the catalyst's excellent oxidative esterification effect on a wide range of substrates, including aromatic aldehydes and alcohols. These findings are expected to facilitate the development of oxidative esterification reactions of biomass-derived platform compounds.

Investigating the specific interactions between polymers and functional peptides allows for the rational discovery of polymer-binding peptides. These peptides can be applied to capture dispersed and dissolved nanoplastic particles in water. Molecular dynamics (MD) simulations require that the force field accurately describe the polymers' physicochemical properties. This study utilized the generalized AMBER force field 2 (GAFF2) to simulate the folding conformations of three common polymer chains―polyethylene (PE), polypropylene (PP), and polystyrene (PS) ― in an aqueous solution. The power law relationship between the radius of gyration and chain length was calculated to compare theoretical predictions. Additionally, the density and heat capacity of polymer melts were simulated and compared with experimental measurements. The simulation results confirmed the reliability of the GAFF2 in describing polymers. Subsequently, we examined molecular interactions between nanoplastic particles and polymer-binding peptides in the explicit-solvent MD simulations. Binding free energy calculations revealed that theHNKSSPLTAALPpeptide exhibited the strong affinity for PE particles, followed by the TSDIKSRSPHHRpeptide for PP particles, and the HWGMWSY peptide for PS particles. van der Waals interactions are essential for the specific recognition of molecules between peptides and polymers.

Achieving efficient gas—liquid countercurrent operation in microreactors faces multiple technical challenges, primarily due to the difficulty in forming stable countercurrent flow naturally, along with high flow resistance and substantial pressure drop. This study proposes a novel microscale gas—liquid countercurrent absorption method based on helical liquid-bridge flow. Micron-scale helical structures are employed to induce stable semi-constrained liquid-bridges, enabling controlled countercurrent contact. By adjusting helical parameters and feed configurations, the method optimizes liquid film distribution, residence time, and interfacial renewal, thereby enhancing mass transfer. Experiments in a CO₂—water system showed that the volumetric mass transfer coefficient increased by 1—2 orders of magnitude compared to conventional devices. A dimensionless correlation for the liquid-phase mass transfer coefficient was developed with less than 15% deviation. This work provides a theoretical and technical foundation for developing efficient microscale gas—liquid absorption devices, with broad applicability in process intensification and system integration of microchemical engineering.

Vacuum gas oil (VGO), an important raw material for catalytic cracking and hydrocracking units, undergoes hydrogenation process to remove sulfur and nitrogen compounds. However, the VGO hydrogenation process is limited by the gas-liquid mass transfer, resulting in a low reaction rate and high energy consumption. In this work, a HiGee-aided fixed bed reactor (HFBR) with excellent mass transfer performance has been developed and applied for VGO hydrogenation. The bed structure of HFBR was optimized and the effects of operating conditions on VGO hydrodesulfurization (HDS) and hydrodenitrogenation (HDN) efficiency were investigated. Compared with fixed bed reactor at equivalent removal efficiency, pressure in HFBR was reduced by 5% to 15% and H/O ratio was lowered by 35% to 60%. The macro-kinetic models for HDS and HDN of VGO were established and the deviations between the calculated and experimental values were within ±20%. This study provides guidance for the reactor design and process optimization of VGO hydrogenation.

Drying pretreatment is a widely adopted preprocessing method prior to the pyrolysis of oily sludge(OS). In this study, a tube furnace, thermogravimetric—infrared spectroscopy (TG-IR), and gas chromatography—mass spectrometry (GC-MS) were employed to evaluate and compare the pyrolysis behaviors of original and dried OS, and to analyze product distributions under various conditions. The results indicate that both original and dried OS undergo pyrolysis in five distinct stages, among which stages 2, 3, and 4 are the most significant. Kinetic analysis reveals that dried OS exhibits lower activation energies of 56.032, 152.166, and 211.462 kJ·mol^{- 1} for these three stages, corresponding to reaction mechanisms of D6 (3D diffusion), F4 (chemical reaction) and F4, respectively. In contrast, original OS exhibits higher activation energies of81.481,235.933, and214.194kJ·mol^{- 1}, associated with the mechanisms A8(random nucleation and growth), F4, and F1 (order of reaction), respectively. TG-IR analysis identifies H₂, CO₂, CO, and CH₄ as the primary gaseous products from dried OS, with the optimal methane-rich gas yield achieved at temperatures below 724.61 ◦C. Furthermore, GC-MS analysis of the pyrolysis oil obtained from dried OS at 600 ◦C reveals higher concentrations of hydrocarbons and oxygenated compounds, along with reduced levels of nitrogen-containing and hazardous constituents, suggesting its superior suitability and cost-effectiveness as a recyclable fuel.

Phosphogypsum, a large-volume phosphoric acid production by-product with significant environmental risks, demands urgent resource and high-value utilization. Reductive decomposition to high-activity quicklime is effective for this purpose. For high-quality products, improving CaO yield and inhibiting CaS formation enhances added value. Based on this, this study systematically investigates the reaction mechanism and regulation strategy of phosphogypsum decomposition to CaO under different atmospheric conditions. Special focus is placed on analyzing the effects of CO concentration, CO₂ concen tration, and P_{CO2/PCO partial pressure ratio on the reductive decomposition pathway and the products obtained from phosphogypsum. The results show that introducing CO2 into the CO reducing atmosphere can effectively promote the conversion of CaSO4·2H2O to CaO, increasing the decomposition mass loss rate from 43.10% to 63.83%, indicating that adding CO2 to the reducing atmosphere achieves directional regulation of CaO formation. When the PCO2/PCO partial pressure ratio increases from 0.15 to 15, the mass loss rate of CaSO4·2H2O rises from 55.66% to 62.50%, demonstrating that a higher PCO2/PCO ratio not only promotes the reaction between CaSO4 and CO to form CaO but also facilitates the conversion of generated CaS to CaO. Under the CO—CO2—N2 mixed atmosphere, the initial reaction temperature of phosphogypsum reductive decomposition decreases by approximately 300 ◦C, while the formation of CaS is inhibited, significantly increasing the CaO content in the products and realizing directional regulation of the thermal decomposition products of phosphogypsum.}

Particle deposition in the respiratory tract involves interdisciplinary dynamic processes such as fluid mechanics, biomedicine, and materials science, and is of great significance for disease transmission (e.g., SARS-CoV-2 aerosol infection), toxicant exposure (e.g., cigarette carcinogens), and pulmonary drug delivery (e.g., asthma therapeutics). In this study, the geometric structure of the upper respiratory tract from the nasal vestibule to the tracheal bifurcation was reconstructed using clinical computed tomography scan data and the structural repair was completed. Then, we adopted a computational fluid dynamics framework based on the Eulerian—Lagrangian approach to simulate the transport and deposition processes of aerosols. The results show that the simulation results are basically consistent with the experimental data, which confirms the reliability of the proposed model. The positions of deposition hotspots mainly depend on structural features. For example, areas with abrupt changes in the shape and direction of the flow channel, such as the nasal vestibule, piriform fossae, and laryngeal constriction, are prone to form deposition hotspots, which are related to the vortex intensity. The particle deposition rules under steady-state and cyclic breathing conditions are obtained through the analysis using multifactorial design of experiments and response surface methodology. Under steady-state breathing conditions, the particle size dominates the influence on deposition efficiency (order of influencing factors: particle size ＞ flow rate ＞ particle density), and there is a significant synergistic effect between particle size and flow rate. Under cyclic breathing conditions, respiratory frequency and inspiration-to-expiration ratio have equivalent effects on regulating inspiratory time, with a strong coupling effect between them, while postinspiration breath-hold has a limited effect on improving deposition efficiency. The results of this study have laid a solid theoretical foundation for aspects such as precise drug delivery and respiratory protection.

Polystyrene microspheres are widely utilized in automobiles, electronics and packaging due to their diverse characteristics, which are highly dependent on particle size. Traditionally, with the manipulation of suspension polymerization parameters, different sizes of microspheres ranging from 10 to 1000 μm can be prepared, with the coefficient of variation (CV) of particle size distribution ranging from 20% to 50%. However, emerging application fields such as pharmaceuticals and biotechnology have high demands for stability and require a narrow particle size distribution. To address this, researchers have proposed novel approaches. This review summarizes both well-developed traditional methods and emerging techniques for particle size control, analyzing their underlying mechanisms. The aim is to provide a reference for the development of preparation methods with controllable particle size. Firstly, the mechanisms of traditional particle size control methods, including optimization of stirring parameters, design of dispersant systems, regulation of oil-to-water ratio, utilization of salt effects and temperature control, are analyzed, and the mechanism of these methods in modulating microspheres size is concluded. Secondly, novel techniques such as membrane emulsification, microfluidic technology and acoustic field-assisted methods in controlling particle size distribution and enhancing reaction efficiency are introduced, mainly focused on their principle characteristics and potential application prospects. Finally, the future development of suspension polymerization technique in preparation of polystyrene microspheres is discussed.

The ejector, a key component of the jet loop reactor for efficient gas—liquid mass transfer, has its structural design and optimization as the core of process intensification. In this work, based on the self-designed down-jet venturi ejector, water—air is used as the working medium, and a swirler structure is added to the nozzle. Combined with the computational fluid dynamics (CFD) method, the changes of the internal flow field of the ejector in the presence of the swirler are analyzed in depth. The effects of liquid circulation rate (Q_L), nozzle size, and swirler angle on the performance of the ejector are investigated. The results show that under the operating conditions of 0.55 m³·h^{- 1}, the combination of a 3 mm nozzle and 30◦swirler can significantly improve the ejector's suction volume (Q_G) and gas—liquid interface area density (IAD). Q_G reaches 3.22 m³·h^{- 1}, and IAD is 5246.8 m²·m^{- 3}. This study reveals the internal hydrodynamic mechanism of the swirler to enhance the performance of the ejector. It provides theoretical guidance for the design and operation optimization of high-performance swirl ejectors.

Accurately predicting key product features is essential for process optimization and safety in petrochemical processes. However, conventional data-driven AI models often struggle to adequately capture the strong nonlinearity and multi-scale characteristics of these systems. To address this challenge, this paper proposes a multi-scale prediction framework that integrates variational mode decomposition (VMD), attention mechanisms, and temporal convolutional networks (TCN), referred to as DATCN. This framework facilitates the extraction of multi-scale features across temporal, spatial, and frequency domains, enabling cross-scale interaction modeling in complex processes. Comparative experiments on the Tennessee Eastman (TE) benchmark and industrial fluid catalytic cracking (FCC) long-term time-series datasets demonstrate that the proposed model achieves superior prediction accuracy (RMSE reduced by 24.75% to 37.26% versus other deep-learning models). The results demonstrate the framework's capability to address both nonlinear dynamics and spatiotemporal heterogeneity, offering a promising solution for intelligent optimization in petrochemical production.

Gas—liquid mixing and mass transfer in jet-driven tanks are crucial for multiphase systems. However, the understanding of these devices remains limited. Herein, a novel self-rotating hydraulic agitator with a semi-circular, multi-nozzle, and multi-layer jet design was integrated into a tank. High-speed imaging and dynamic gassing-in were used to characterize the bubbles and measure the volumetric mass transfer coefficient (k_La). The hydraulic stirring tank generated self-rotating vortices and strong shear forces, promoting bubble break-up compared to a mechanical stirring tank, reducing the Sauter mean diameter (d₃₂) by 25%—40%, increasing the deformation rate (Ē) by 7%—8%, and enhancing k_Laby 20%—45%. Higher gas and liquid rates intensified the flow disturbances and gas—liquid contact. Appropriate baffles suppress circulation and vortex cores while enhancing local turbulence. The counter-directional configuration of the hydraulic agitator and gas distributor enhanced radial flow and shear interactions, generating smaller, more spherical bubbles that decreasedd₃₂ by 4%—8%, increased the Ē by 4%—5.5%, and improvedk_Laby 3%—11%. The effect of pulsed intake mode on gas—liquid mass transfer was investigated, and no observable enhancement was observed under the tested conditions. Computational fluid dynamics(CFD)simulations were conducted to investigate the flow field and turbulence interaction. These findings reveal that the mechanisms enhancing tank performance include self-rotating vortices, high-velocity shear, multi-zone flow coupling, and gas—liquid interactions, thereby providing valuable insights for optimizing both the tank structure and agitator design of fluid-jet-driven apparatuses.

The flow regulation mechanism of bottom-blowing stirring is the key to enhancing the reaction efficiency of a molten bath. Herein, proper orthogonal decomposition (POD) is integrated with chaos theory for the first time to investigate the influence of asymmetric nozzle arrangements on flow field regulation and mixing performance during bottom-blowing smelting. The optimization effect of a 10◦asymmetric nozzle configuration (model III) is specifically examined through numerical simulation and analysis. The results indicate that model III effectively suppresses splashing while increasing splash height and optimizing the flow field structure, thereby markedly enhancing mixing efficiency. The Lyapunov exponent in the main flow region is 1.5—2.3 times higher than that of other models, and energy cascades across the full frequency range of 50—300 Hz. POD analysis reveals that approximately 98% of the total system energy is captured by the first 68 modes, while the first two modes together account for 71.36% of the total energy, indicating a highly efficient low-order energy representation and rapid energy transfer across dominant flow structures. The asymmetric vortex structure effectively coordinates large macroscopic vortices and small-scale eddies, thereby enhancing mixing performance. This work provides theoretical support for the optimization of bottom-blowing furnace stirring systems and demonstrates the potential of POD in metallurgical process analysis.

The spinel-structured LiNi_0.5Mn_1.5O₄ (LNMO) has become one of the most promising cathode materials for next-generation high-energy-density lithium-ion batteries. However, the commercial application of LNMO remains challenging despite decades of research. To address the challenge, developing eco-friendly, cost-effective synthesis methods for high-performance LNMO materials is of critical importance. In this study, we developed an innovative sol-gel synthesis approach utilizing cost-effective and environmentally benign soluble starch as a chelating agent. Investigation into the effects of different calcination temperatures (700, 800 and 900 ◦C) on LNMO materials revealed that the sample calcined at 800 ◦C for 3 h exhibited the best electrochemical performance. It delivered an initial discharge capacity of 136.88 mA·h·g^{- 1} at 1 C, maintaining 95% of its initial capacity after 500 cycles. To the best of our knowledge, few studies have reported such excellent electrochemical performance in LNMO materials. Morphological and structural analyses revealed that the excellent electrochemical properties of the LNMO material primarily originated from its truncated octahedral morphology and disordered structure. These findings provide valuable insights into the development of LNMO materials with high-rate capability and long-cycle-life performance.

This study investigates biogas as a renewable feedstock for green methanol production and compares three hydrogen—to—carbon (H/C) ratio adjustment strategies: (I)CO₂ removal before reforming, (II)CO₂ removal after reforming, and (III) green hydrogen supplementation. Each route is evaluated using high—fidelity process simulations, techno—economic analysis, and life cycle assessment. Route II achieves the lowest minimum selling price (419 USD·t- 1 at a capacity of 100 kt·a- 1)and lowest net greenhouse gas (GHG) emissions (144 kg CO₂ per tonne of methanol), due to superior energy efficiency and carbon utilization. Route III offers the highest production yield but depends heavily on low—cost green hydrogen. Our findings identify optimal pathways for deploying biogas—to—methanol technologies under varying economic and policy conditions.