The rapid development of semi-conductor industry calls for the production of organometallic precursors with ultrahigh-purity and low cost. TiO₂ film is an important high-k materials, but its atomic layer deposition (ALD) precursor tetrakis(dimethylamino)titanium (TDMAT) still suffers from low industrial synthesis yield and inadequate purity. Herein, by optimizing the lithium displacement method in TDMAT synthesis, much milder synthesis conditions have been achieved with higher yield (91.00%) and ultra-high organic purity (＞99.9%). In the purification optimization, a new coupled process combining alkali metal salt and rectification was proposed, based on which ultra-high inorganic purity (99.99993%, Cl^- content ＜10^-5, 6N) and high TDMAT yield (93.70%) can be obtained. Finally, by using the assynthesized precursor, wafer-scale TiO₂ film under ALD process has been fabricated, which was characterized bySEM, EDS, AFM, XPSand spectral ellipsometry (SE). Specially, AFM validates its ultrasmooth surface without any extra holes or agglomerations (RMS: 0.303 nm). This work will be significant for the development of ultrahigh-purity semi-conductor materials.

The formation dynamics of shear-thinning non-Newtonian droplets in microchannels remain insufficiently characterized, particularly regarding the wettability effects of the channel wall. This study investigates the formation dynamics of shear-thinning non-Newtonian droplets in T-junction microchannels with varying contact angles by means of three-dimensional numerical simulations. The non-Newtonian rheological behavior is modeled using the Cross power-law constitutive equation. The two-phase interface evolution is tracked using the volume-of-fluid method with an adaptive mesh refinement algorithm. Compared with experiments, the established method demonstrates strong predictive capability for shear-thinning droplet formation. The results show that higher wall contact angles tend to transform squeezing flow and jetting flow into dripping flow. In the dripping flow regime, increasing the contact angle leads to a decrease in the stretch length of the dispersed phase and formation frequency, while the droplet volume tends to increase. With the shear-thinning time constant increases, the viscosity and stretch length of the dispersed phase decrease, leading to larger droplet volume. A smaller contact angle enhances the adhesion of the dispersed phase to the channel surface, whereas a larger contact angle diminishes the adhesive forces between the dispersed phase and the channel wall, implying that the shear force of the continuous phase leads to earlier droplet detachment. Furthermore, predictive modeling of droplet properties is established considering the shear-thinning parameters and channel contact angle. The findings contribute to meeting the demand for a fundamental understanding of complex fluid dynamics and in industrial applications.

Ensuring the generalizability of fault diagnosis models is critical for maintaining the long-term safety of industrial systems operating under diverse conditions. This study presents a novel method, termed the Generalizable Class-Consistent Network (GCCNet), designed to enhance diagnostic robustness under previously unseen operating conditions. Specifically, GCCNet incorporates a mutual information based feature disentanglement mechanism to extract task-relevant representations. To further promote feature invariance, auxiliary samples are constructed using same-class fault data under different excitation intensities, and a class-consistency regularization is applied during training to enforce consistent predictions. This guides the network to purify task-relevant features into transferable and robust representations. Extensive experiments conducted on the Tennessee Eastman process and industrial dataset validate the effectiveness and generalization ability of the proposed method.

The direct hydroxylation of benzene with hydrogen peroxide (H₂O₂) over titanium silicalite-1 (TS-1) offers an environmentally benign route to phenol, though its efficiency is highly dependent on the solvent environment. By integrating experimental and theoretical approaches, this study reveals the underlying mechanism. Water uniquely boosts benzene conversion to 45.8% through synergistic effects. It serves as a proton-transfer mediator to lower the activation barrier (ΔG), enhances the electrophilicity of Ti-active sitesvia increased maximum electrostatic potential (ESP_max), and leverages the hydrophobic pores of TS-1 to enrich benzene near the active sites. However, this multifunctional enhancement also promotes over-oxidation, limiting phenol selectivity to 42.8%. In contrast, the organic solvents suppress consecutive oxidation and achieve high selectivity above 70% due to their largerHOMO-LUMOenergy gaps (E_gap). Yet they exhibit low activity owing to higher energy barriers, weaker electrophilicity, and competitive adsorption. This work further establishes quantitative correlations between catalytic performance and key descriptors such as ΔG, ESP_max, and E_gap, providing a predictive framework for rational solvent selection in TS-1 catalysis.

Corrosive liquids formed by the condensation of acidic gas components below the dew-point temperature can cause localized electrochemical corrosion on metal surfaces. However, the lagging response of dew-point monitoring and nonlinear coupling effects between complex process parameters render the synergistic mechanisms of these parameters poorly understood. The joint mechanism of dew-point temperature and pH was revealed through electrochemical experiments. A dew-point corrosion database which includes 21 process parameters was created by integrating multi-source data through incremental learning. The performance of five models, including the Particle Swarm Optimization -eXtreme Gradient Boosting (PSO-XGBoost), was compared, with Shapley's Additive Explanations (SHAP) used to quantify the contributions of process parameters. PSO-XGBoost delivered the most accurate predictions for dew-point temperature and pH, with R² values of 0.9987 and 0.9754, respectively. Quantitative analysis of the SHAP values showed that an increase in parameters such as oil flow rate decreases the dew point temperature, and that the optimal reduction effect is achieved when the ratio of water flow rate to stripping steam flow rate is 0.92. Additionally, the molar fraction of CO₂ in noncondensable gas was identified as the primary factor leading to the reduction in dew-point pH.

Ruthenium-based catalysts, valued for their oxygen vacancies and reducible oxygen species, are widely employed in the catalytic degradation of chlorinated volatile organic compounds (CVOCs). This paper reports a simple method for optimizing the positioning of Ru nanoparticles on Fe₂O₃ and CeO₂ by controlling the pH, thereby synthesizing a series of Ru/FeCe nanospheres (NS). The Ru/FeCe NS-2 exhibits outstanding catalytic performance in TCE oxidation reactions (T_50% = 64 ^◦C, T_90% = 95 ^◦C). Furthermore, under an air atmosphere at 200 ^◦C, the Ru/FeCe NS-2 catalyst exhibits remarkable stability, maintaining its catalytic activity for as long as 1400 min. Based on GC-MS experimental results, the primary intermediates in TCE oxidation were identified, and a plausible reaction mechanism for TCE catalysis by the Ru/FeCe NS-2 mixed oxide catalyst was proposed. Importantly, the catalyst effectively degrades low-concentration CVOCs from contaminated soil, the catalyst demonstrates satisfactory degradation performance and resistance to chlorination poisoning, indicating its significant potential for practical applications.

Global demand for sodium dithionite (Na₂S₂O₄, TDS) has been steadily rising, as it is an effective flame retardant, bactericide, and bleaching agent. However, conventional manufacturing methods often involve high operational costs, excessive use of reducing agents, and significant environmental pollution, which hinder sustainable industrial production. To address these issues, this study focused on the design of efficient electrochemical reactor, optimizing reaction parameters, investigating the electrochemical reaction mechanisms, and developing high-performance carbon-based electrocatalysts. A micro-gap-flow electrochemical reaction system for the electrosynthesis of TDS was successfully developed. This system integrates traditional chemical synthesis with electrochemical reduction, enabling the efficient creation of TDS in an aqueous sodium bisulfite solution. The current efficiency of this electrical synthesis process was notably improved, increasing from 85% to over 90%. Furthermore, the energy consumption for TDS production was 0.81 kW·h·kg^{- 1} when using the Cu/NC electrode. The processes and pathways of TDS electrochemical synthesis were explored using electrochemical tests and theoretical calculations.

The utilization of CO₂ resources is an important way to mitigate excessive release of CO₂ and addressing energy shortages. In this work, a series of metal- and halogen-free imidazole-based hypercrosslinked polymers (HCPs) featuring hydrogen bond donors were constructed by one-step Friedel-Crafts alkylation using imidazole derivatives 4-(imidazole-1-yl)aniline (PYIM-NH₂) and 4-(imidazole-1-yl)phenol (PYIM-OH) containing hydrogen bond donors (—NH₂, —OH) as functional monomers. The synthesized HCPs possess a high specific surface area, an abundance of multi-level pore channels, and excellent adsorption capacity and selectivity for CO₂. The optimal catalyst Imi-HCP-NH₂(14:1) synthesized using PYIM-NH₂ as the functional monomer demonstrates a high catalytic activity for fixing CO₂ into cyclic carbonates under additive-free conditions. Notably, the catalyst exhibits a satisfactory catalytic activity even under diluted CO₂ concentration and mild conditions. The excellent catalytic performance, along with good cycling stability and the broad applicability of epoxides, make it a competitive catalyst for catalyzing the CO₂ cycloaddition reaction.

The process of exploiting natural gas hydrates involves complex phase changes, multiphase seepage, and intricate heat transfer processes. A comprehensive understanding of the heat transfer characteristics in natural gas hydrate reservoirs is crucial for enhancing their exploitation efficiency. However, at present, there is a limited amount of research on the effective thermal conductivity (ETC) of complex component systems in marine natural gas hydrate reservoirs, which directly restricts the optimization of natural gas hydrate exploitation technologies in marine sediments. This study proposes a method to predict the ETC of marine natural gas hydrate reservoirs based on machine learning (ML). This method constructed an ETC dataset under the conditions including reservoir environmental characteristics (temperature, pressure, salt concentration), reservoir physical property characteristics (quartz sand content, montmorillonite content, illite content), and reservoir structural characteristics (initial water saturation, hydrate saturation, component phase). In this work, a dataset containing 200 data points from various literature was compiled. Six ML models were employed to predict the ETC of the reservoirs based on this dataset with a high-precision ETC prediction model being derived through ML training. The SHapley Additive exPlanations (SHAP) method was subsequently applied to conduct interpretability analysis on the model prediction results. This has not only confirmed the model's reliability but also quantitatively highlighted the sensitivity of key reservoir characteristics to ETC. The research results show that the Gradient Boosting Decision Tree (GBDT) model is particularly effective for predicting the ETC of marine natural gas hydrate reservoirs, as evidenced by its coefficient of determination (R²) exceeding 0.95. Sensitivity analysis reveals that the reservoir's salt concentration and illite content are the primary determinants of its overall ETC. The prediction method established in this study can provide effective technical support for the real-time evaluation of reservoir ETC during the on-site exploitation of marine natural gas hydrate reservoirs.

The microchannel heat sinks exhibit significant potential in the thermal management of electronic devices. Compared to traditional enclosed microchannel heat sinks, open microchannel heat sinks offer advantages such as enhanced heat transfer capacity, reduced pressure drop, and improved flow stability. However, research on flow boiling enhancement in open microchannels remains relatively limited. In this study, a multilevel synergistic enhancement strategy for flow boiling in open microchannels has been proposed, incorporating a trapezoidal cover plate coupled with laser-processed micropillar structures (TOMC). Amicrochannel heat sink was fabricated with a surface featuring visible micropillars, microspheres, and microcavities, with sizes ranging from 1 μm to 50 μm. The flow boiling characteristics of three open microchannel heat sinks, COM, TOM, and TOMC, were tested at different subcooling degrees and mass fluxes usingHFE-7100. Compared with the other two configurations, the critical heat fluxes (CHF) of the TOMC heat sink were substantially increased by 35.9%to 170.6%, and the wall temperatures were decreased by 17.5 K. The average heat transfer coefficients (HTC) of the TOMC heat sink were increased by 66.1% to 122.0%. The laser-processed micropillar configuration provided effective nucleation sites and enhances capillary wicking capability, thereby maintaining wall wettability. The trapezoidal cover plate increased downstream flow velocity, accelerating bubble detachment and phase separation processes. Visualization results indicate that the multilevel synergistic enhancement of the TOMC heat sink, which sustained Type-I stratified flow over a broader range of heat fluxes, was critical to preventing heat transfer deterioration. Furthermore, by employing various comprehensive performance evaluation methods, the TOMC heat sink achieved outstanding overall performance, with a COP exceeding 20000. This work integrates multiple heat transfer enhancement techniques, offering new insights for efficient thermal management applications in electronic devices.

The pursuit of environmentally benign and cost-effective hard carbon (HC) anode materials has been expedited by the growing demand for sustainable sodium energy storage solutions. Herein, a waste-tovalue method is pioneered to produce HC from walnut kernel (WK) biowaste from agro-industries, via pre-hydrothermal carbonization in a KOH/water solvent system, followed by post-high temperature treatment at 1200 ^◦C (H-WKHC-KW-12). The influence of synthesis parameters on the structural characteristics and interfacial sodium storage behavior ofH-WKHC-KW-12 was systematically investigated. As an anode material for sodium-ion batteries (SIBs), the optimized H-WKHC-KW-12 electrode exhibits impressive electrochemical properties including a high reversible capacity of 311.95 mA·h·g^{- 1} at 0.1C, excellent rate performance with 247.7 mA·h·g^{- 1} retained at 10 C, and robust long-term cycling stability, retaining 98.87% of its capacity at 0.1C after 100 cycles and 92.36% at 1C after 1350 cycles. Furthermore, the material delivers a favorable initial Coulombic efficiency (ICE) of 81%, demonstrating its viability for practical sodium storage applications. The study demonstrates the feasibility of converting WK processing waste from agro-industries into high-performance HC anode materials, supporting circular economy principles and furthering the creation of affordable, environmentally friendly SIBs technology.

The fouling problem has attracted much attention in many industrial fields and daily life scenes. Traditional antifouling methods have limitations such as environmental pollution, health hazards, and poor durability. Biomimetic surface micro-textured superhydrophobic surface antifouling technology came into being. This technology does not depend on harmful chemicals, but provides innovative solutions for antifouling, self-cleaning and other fields by imitating the special micro-nano structure of biological surface and utilizing its own physical characteristics. Micro-textures inspired by plants and animals, such as lotus leaves, rose petals, shark skin, etc., can change the wettability of the material surface and reduce the adhesion of dirt. Processing technologies such as laser, wire cutting and template method can be used to construct micro-textures with superhydrophobic properties. These technologies have the advantages of simple process, high processing efficiency and environmental friendliness. Numerous research cases have shown that bionic micro-texture technology has great application potential and value in many fields. In the future, with the continuous advancement and innovation of micro-nano processing technology and the strengthening of interdisciplinary cooperation, bionic microtexture technology is expected to achieve breakthroughs in more fields and provide more innovative ideas and solutions for solving the fouling problem.

Perhydro-benzyltoluene (H12-MBT), a promising hydrogen carrier, faces a slow dehydrogenation rate dilemma, thereby hindering its wide application. Sn-incorporated Pt/Al₂O₃, a common propane dehydrogenation catalyst, was introduced into H12-MBT dehydrogenation reaction. And it was essential to understand the role of Sn in this reaction. A series of Pt-Sn/γ-Al₂O₃ catalysts was synthesized by controlling the Sn loading and changing impregnation sequence of Pt and Sn. Results from various characterization tools like, XRD, TEM, and XPS, showed that the structure and electron density of the catalyst varied with different synthetic conditions. The increasing amount of Sn loading led to a decreased activity on the Pt-Sn/γ-Al₂O₃ catalyst when the Sn component was impregnated Al₂O₃ before the Pt impregnation (named reversed sequential impregnation). For the same Pt and Sn amounts on the catalyst, it was found that the reversed sequential impregnation case exhibited good dehydrogenation performance compared to the catalysts prepared with sequential impregnation. Density functional theory calculation results showed that the downshift of the d-band center of the active component can be identified with the introduction of Sn. Both of the experimental and the theoretical calculation results help better understanding the role Sn for Pt-Sn/γ-Al₂O₃ catalyzed H12-MBT dehydrogenation, and thus better design and synthesis better catalyst for this dehydrogenation reaction.

Process safety management level evaluation is a key tool for identifying risks and hazards and improving accident prevention. Accident rates can be reduced by objectively assessing compliance and management gaps. The current chemical enterprise process safety management level assessment methods rely on post-accident data and subjective judgment of experts. This method lacks foresight, the system is incomplete, and the results of safety integrity is difficult to be quantified. An approach for constructing key performance indicators (KPIs) that fuses incident data with expert knowledge is proposed. Accident topics are mined through latent dirichlet allocation (LDA). Decision making trial and evaluation laboratory-interpretive structural modeling(DEMATEL-ISM) is used to construct elemental causal networks. A semantic mapping-based filtering model for highly relevant metrics has been developed. The cloud model is used for the final quantitative evaluation of the safety level of the organization. An assessment of the safety integrity level of a large refining company is used to study the performance of this model. The results show that the method can effectively identify management weaknesses, and the quantitative assessment results are highly consistent with the actual grade, realizing an automated assessment process.

This experiment aimed at the synergy effect of ripple flame arrester and water mist on hydrogen doped methane explosions. By comparing the dynamic flame resistance process and changes in explosion parameters, the mechanism of synergy inhibition was clarified. Result explains that both synergies enhanced the protection efficiency of gas explosions. Spray conditions could greatly affect the propagation velocity of flames entering narrow channels, thus affecting its stagnation time inside the ripple hole and quenching probability. The synergy was attributed to the combined action of mist parameters on weakening and enhancing effects. As the nozzle type enlarged, the increase in mist parameter promoted a decrease in pressures at both ends, even the complete inhibition was achieved. Inhibition effect was gradually enhanced as the spray time prolonged, and explosion-resistance parameters were also greatly decreased. But the inhibition result showed a variation process of “failure-success-failure”as the spray pressure enlarged, and explosion-resistance parameters also displayed a change of first reducing and then rising. Under the synergy effect, the inhibition could be achieved as the generation rate of free radicals was lower than the destruction rate and flame temperature at the ripple hole outlet was lower than the critical flame resistance temperature.

To improve the dispersibility and emulsification performance of magnetic nanoparticles, this study first synthesized three modified magnetic nanoparticles (Co₃O₄@HPAM) with different monomer ratios and characterized their physical properties. On this basis, the effects of the modified magnetic nanoparticles with different monomer ratios on the emulsification and viscosity reduction of thick oil were investigated by stability and rheology; finally, the emulsification and viscosity reduction mechanism was revealed by combining the zeta potential, surface tension, contact angle, and oil droplet distribution. The results showed that Co₃O₄@HPAM with three different monomer ratios was successfully synthesized and exhibited good dispersibility. With the increase of monomer ratio, the emulsion water fraction decreased first and then increased, and the viscosity reduction decreased first and then increased. At a mass fraction of 0.04%, the sample with a 15% monomer ratio exhibited the lowest water separation rate (6.45% at 4 h) and the highest viscosity reduction rate (97.93%). This phenomenon occurs because, at a 15% monomer ratio, the modified magnetic nanoparticles have a higher negative charge, a larger contact angle, lower oil-water interfacial tension, and smaller, more uniformly distributed oil droplets. This study offers a theoretical foundation for using magnetic nanoparticles in heavy oil emulsification to reduce viscosity.

Lithium-ion batteries (LIBs) have become pivotal in modern energy storage systems, attributed to their superior energy density and environmentally friendly nature. Among anode materials, tin disulfide (SnS₂) stands out due to its high theoretical capacity and affordability. However, its widespread use is hindered by significant volume fluctuations and limited intrinsic conductivity. Herein, we report a yolk-shell SnS₂/CoS₂ composite encapsulated within a nitrogen-doped carbon matrix (YS-SnS₂/CoS₂@N_xC), designed as an advanced LIB anode. The incorporation of cobalt ions, together with the highly conductive N-doped carbon scaffold, contributes to improved charge mobility and structural robustness. Moreover, the cooperative interaction between dual-metal sulfides and the engineered shell architecture effectively accommodates volume variation and preserves electrode integrity. Electrochemical analyses show that the composite maintains a stable capacity of 803.4 mA·h·g^{- 1} after 300 cycles at 0.5 A·g^{- 1}, and delivers 425.9 mA·h·g^{- 1} even after 800 cycles at 2 A·g^{- 1}, with nearly full Coulombic efficiency. These outcomes underscore the material's outstanding rate capability and long-lasting cycling performance.

Although neural network-based soft sensing in biomanufacturing processes shows substantial promise, many existing approaches either fail to encode physical prior knowledge or do not make effective use of unlabeled data. These limitations hinder both the generalization of the model and its adherence to physical consistency. To address these issues, this study proposes the Physics-Informed Variational Autoencoder Regression (PIVAER)-based soft sensing, which improves the VAE by incorporating: (1) monotonicity constraints on specified input—output relations to ensure that predictions respect known monotonic trends, and (2) embedded differential constraints derived from the kinetic equation. Soft penalties in the form of physics residual and monotonicity terms are embedded within a unified objective function, thereby enabling semi-supervised training that integrates both labeled and unlabeled data. Through this design, the PIVAER achieves improved physical consistency and generalization capability. Its effectiveness has been demonstrated by experiments conducted on both simulated and real penicillin fermentation datasets. Comparative experiments using state-of-the-art methods demonstrate superior predictive accuracy and enhanced generalization capability.

Biodiesel as a high-quality alternative to petrochemical diesel, has attracted much attention due to its environmental friendliness and renewability. However, a large amount of by-product crude glycerol occurs in the production process. Membrane separation, as a green and efficient technology, has a wide range of applications in crude glycerol desalination. In this work, the thermo-responsive zwitterionic nanocapsules with amino groups (HZNs-NH₂) were prepared by Reversible Addition Fragmentation Transfer (RAFT) living radical polymerization and amino-functionalization. HZNs-NH₂ were embedded in the polyamide (PA) active layers to prepare extra transport channels in nanofiltration (NF) membranes with a polysulfone ultrafiltration membranes as support layer. At the same time, amino groups on the surface of HZNs-NH₂ reacted with trimesoyl chloride (TMC) to improve the interfacial compatibility of HZNs-NH₂ with the polyamide matrix. The effects of loading concentration, amino group content, core/shell ratio of HZNs-NH₂ on the structure and separation performance of thin film nanocomposite (TFN) membranes were investigated. The prepared thin-film nanocomposite nanofiltration membrane with HZNs-NH₂(HZNs-NH₂-TFN) had fine Turing structure and highly water flux of 123 L·m^{- 2}·h^{- 1}, which was 5.4 times higher than that of the pristine nanofiltration (TFC) membrane without nanocapsules, and Na₂SO₄ rejection rate is 96%. Moreover, for desalination of crude glycerol with Na₂SO₄, the prepared HZNs-NH₂-TFN had a glycerol flux of 90.81 L·m^{- 2}·h^{- 1}, which was 2.36 times higher than that of the TFC membrane, and without losing its salt rejection rates. Meanwhile, it was found that the HZNs-NH₂-TFN has thermo-responsiveness behavior, with a maximum temperature change range of 30- 35 ^◦C and a flux change slope of 4.47 (ΔT =5 ^◦C), which was 6.48 times higher than that of the TFC membrane. A new way to construct transport channels and TFN membranes with thermo-responsiveness was created by this work, which is very promising for desalination of high viscosity systems.

Tetragonal ZrO₂ (t-ZrO₂) with abundant oxygen vacancies offers a viable approach to support Ni catalysts for enhanced catalytic performance in dry reforming of methane (DRM). However, the application of t-ZrO₂ is limited by its inherent thermal instability. Herein, we evaluated Ni₃Fe₁ alloy supported on m-ZrO₂ and t-ZrO₂ stabilized with CaO or Y₂O₃ for DRM. Ni₃Fe₁/m-ZrO₂ showed inferior activity, while Ni₃Fe₁/Y₂O₃—t-ZrO₂ retained t-ZrO₂ structure but exhibited poor stability. In contrast, Ni₃Fe₁/CaO—t-ZrO₂ demonstrated high stability, maintaining CH₄ and CO₂ conversions of 78.0% and 87.2% with H₂/CO ratio of 0.95 at 800 ^◦C. This is attributed to the CaO dopant, which not only stabilized t-ZrO₂ phase but also strengthened metal—support interaction at the Ni₃Fe₁—ZrO₂ interface, increased oxygen vacancy concentration, and improved surface basicity. Notably, these significantly facilitated CH₄ dissociation and CO₂ activation, establishing an effective balance between carbon formation and gasification, thereby improving the coke resistance of the catalyst.

The limited recovery rate of powdered photocatalysts and potential secondary pollution issues have constrained the practical application of photocatalytic technology. Therefore, it is urgent to develop easily recoverable photocatalysts to address harmful algal blooms. In this study, a simple sol-gel method was used to synthesize a recyclable TiO₂/FeTiO₃ composite photocatalyst on ceramic membrane for photocatalytic inactivation of Microcystis aeruginosa. TiO₂/FeTiO₃ photocatalysts exhibit stable algal removal performance under various conditions (natural organic matter content, alkalinity levels et al.), the TiO₂/FeTiO₃-4 photocatalyst with the best performance can achieve 100% photocatalytic inactivation of Microcystis aeruginosa (OD₆₈₀=0.8) within 4 h of light irradiation. TiO₂/FeTiO₃ photocatalysts can not only inactivate Microcystis aeruginosa, but also degrade intracellular and extracellular organic matter. Free radical scavenging experiments prove that holes play a major role in the photocatalytic inactivation of Microcystis aeruginosa, additionally, cyclic stability tests indicate that the photocatalyst is easy to recover and maintains a degradation rate of 97.19% even after three cycles. The process of preparing recyclable photocatalysts on ceramic membranes provides new ideas for the application of photocatalytic technology in pollutant treatment.

Chemical looping hydrogen generation (CLHG) utilizes the cyclic operation of oxygen carriers to independently convert fuel and steam, providing advantages such as low energy demand for decarbonization and a simplified process. However, conventional optimization of CLHG using Aspen Plus generally relies on sequential simulations of individual process parameters, such as reactor temperature, pressure, and feed ratio, which is both time-consuming and inefficient. This study develops an optimization framework that couples Aspen Plus with machine learning algorithms, where the latter serves as a surrogate model to rapidly predict the impact of operational conditions on hydrogen yield and fuel conversion efficiency in CLHG process, thereby avoiding repeated full-scale simulations and accelerating process optimization. The results demonstrate that temperature is the most influential factor, with shapley additive explanations (SHAP) values ranging from - 40 to 30. The feed ratio and pressure have relatively weaker impacts, with SHAP values of - 10 to 10 and near zero, respectively. Verified through literature data, the model achieves an accuracy rate of approximately 93.8%. This method can rapidly and efficiently optimize the chemical looping hydrogen production process and can be extended to the optimization of other chemical looping applications.

The persistent challenge of antibiotic contamination in water necessitates efficient catalytic systems for peroxymonosulfate (PMS)-based advanced oxidation processes. While cobalt-based catalysts derived from ZIF-67 metal-organic frameworks and conventional core-shell structures like SiO₂coatings offered limited physical encapsulation, they failed to prevent intra-particle agglomeration and adequately suppress Co ions leaching. Drawing inspiration from the dual-shell defense mechanism of the nacre structure, which combined physical and chemical mechanisms, this study constructed a Co₃O₄/C@MnSiO₃(CCMS) nacre-mimetic nanostructured catalyst by converting the mesoporous SiO₂on the surface of ZIF-67 into MnSiO₃. The unique architecture effectively suppressed nanoparticle aggregation within individual ZIF-67 through physical encapsulation and bimetallic interaction, dispersed the active sites, reduced Co²⁺leaching, and enhanced catalytic activity. Compared to Co₃O₄/C (CC) and Co₃O₄/C@SiO₂(CCS), the CCMS/PMS system significantly improved tetracycline degradation(1.4 and 2.3 times higher kinetic constants)and maintained 75% removal efficiency after five cycles. This study constructed a nacre-mimetic structure achieving highly efficient and stable catalysis, meanwhile providing novel strategies for optimizing MOF-based catalytic materials.

Geothermal energy is a crucial renewable resource for achieving carbon neutrality. However, its exploitation is hampered by scaling, particularly calcium carbonate (CaCO₃) deposition in wellbores. To address this, a novel composite polymer scale inhibitor was synthesized via the copolymerization of five monomers: acrylic acid, hydroxyethyl methacrylate, sodium allyl sulfonate, citric acid, and monosodium glutamate. This molecular design enables the synergistic integration of multiple functional groups (carboxyl, sulfonic, hydroxyl, ester, and amide). Fourier transform infrared spectroscopy confirmed the successful incorporation of these groups, and thermogravimetric analysis demonstrated excellent thermal stability. Evaluation experiments revealed that the copolymer serves as a highly effective scale inhibitor under simulated high-temperature geothermal conditions (150 ^◦C—200 ^◦C), achieving an inhibition rate exceeding 96% against CaCO₃ scaling. This work presents a promising and sustainable solution for scaling control in challenging geothermal environments.

The design of highly stable and efficient porous materials is crucial for physisorption-based separation of radioactive species (⁹⁹TcO₄^- /ReO₄^- ), serving as an alternative to current concentrate-storagesolidification treatment technologies. Herein, employing a covalent-ionic dual-crosslinking strategy with economical ionic compounds as reactive monomers, a novel cationic organic polymer (TJU-COP-1) was synthesized for the first timeviafacile radical polymerization for ⁹⁹TcO₄^- /ReO₄^- sequestration. TJU-COP-1 demonstrates exceptional adsorption capacity, kinetics and selectivity (K_d) for ⁹⁹TcO₄^- /ReO₄^-(861.87 mg·g^{- 1}, K_d =5.0×10⁵ ml·g^{- 1}), achieving adsorption equilibrium within merely 1 min. Notably, TJU-COP-1 maintains adsorption efficiency as high as 96.25%after five adsorption-desorption cycles. The TJU-COP-1 showed high stability after acid (3 mol·L^{- 1} HNO₃), alkali (3 mol·L^{- 1} NaOH) and radiation (200 kGy ⁶⁰Co γ) treatment. More significantly, TJU-COP-1 demonstrated robust and promising removal performance in complex solution, achieving 98.55% efficiency for ⁹⁹TcO₄^- /ReO₄^- amid high concentrations of competing anions and an excellent 72.11% removal in simulated Hanford LAW waste solution. Combined experimental characterization and density functional theory theoretical validation confirmed that the adsorption mechanism involves a synergistic combination of electrostatic interactions and anion exchange. This study illustrates that TJU-COP-1 has great potential for practical application in the capture of ⁹⁹TcO₄^- /ReO₄^- , and provides a new approach to the design of high-performance adsorbents for the treatment of nuclear wastewater.

The separation and purification of xylene isomers represent a pivotal process in the petrochemical industry. Compared to ortho-xylene and meta-xylene, para-xylene possesses greater application value. Membrane separation technology has shown great potential for application due to its environmental benefits, ease of operation, low energy consumption and excellent selectivity. Notably, attributed to unique pore structures and surface properties, inorganic membrane systems engineered from porous inorganic materials exhibit excellent separation performance for xylene isomers. Through precise molecular discrimination capabilities, this process enables selective recovery of individual isomers, facilitating downstream processing into high-value-added derivatives. This review systematically summarizes recent progress in xylene isomer separation using inorganic membranes. The preparation methods and separation mechanisms of four inorganic membranes were summarized in detail. Furthermore, the two processes involved in the separation of xylene using inorganic membranes were discussed, focusing on solvation diffusion kinetics and the molecular size sieving effect. Subsequently, the challenges currently faced by inorganic membranes were elaborated. Finally, the future development prospects of xylene industrial production were discussed from three perspectives, including membrane material modification strategies, advanced intelligent anti fouling technologies, and comprehensive analysis of mass transfer mechanisms.

During the chloride-route production of titanium, the resulting chlorinated slag and high-salinity waste brine contain multiple metal chlorides and are strongly acidic, hindering the green operation of the titanium industry. In this study, we introduce a three-reagent metered-dosing strategy under real-time pH—oxidation-reduction potential control (NaOH—waste brine—Na₂CO₃) that repurposes the high-salinity residual brine as an alkalinity source while providing stable feedback control over both the dosing trajectory and the end point, thereby enabling the detoxification and resource recovery of chloride titanium slag. Inductively coupled plasma optical emission spectroscopy and X-ray diffraction analyses show that Fe, Al, and Mn precipitate at pH 3—5 with removal efficiencies exceeding 98%. At pH 6.5—7.2, Ca precipitates as carbonates, whereas Mg²⁺ remains in solution and can be subsequently utilized to produce basic magnesium carbonate. Under the optimal volumetric dosing ratio of water-quenched leachate: 30% NaOH: waste brine: 30% Na₂CO₃=75 : 4.5 : 25 : 1.75, with a carbonate-stage reaction time of 20 min, the Ca removal efficiency reached 90.65% and the Mg retention reached 73.1%. The results indicate that Mg²⁺ inhibits CaCO₃ nucleation; during Ca removal, the precipitate exhibits a crystallographic evolution from Ca_1+δMg_{1- δ}(CO₃)₂ to CaMg(CO₃)₂ and then to MgCO₃. Excessive Mg²⁺ concentrations or elevated pH trigger non-selective coprecipitation, thereby reducing Mg retention. Compared with current approaches for handling chloride titanium residues, this method simultaneously recovers value from both solids and brine while mitigating environmental risks, offering a practical and low-cost solution.

Methyl diphenylmethane dicarbamate (MDC) was synthesized by condensation of methyl phenylcarbamate (MPC) using trioxane as methylenation reagents over sulfonic acid resin catalyst. The effect of Brønsted's acid amount on the condensation reaction was investigated, and the optimal sulfonic acid resin (NKC-9) with an acid amount of 4.57 was determined. 2-MDC, featuring a methylene-bridged biphenyl structure, achieved 91.6% selectivity and 83.2% yield after response surface methodology optimization. In situ FTIR spectroscopy was employed to monitor the condensation process. The spectroscopic results unequivocally demonstrate that trioxane undergoes catalytic depolymerization to formaldehyde over NKC-9 resin, which subsequently reacts with MPC to form MDC. After sulfuric acid regeneration, NKC-9 maintains its catalytic performance after 4 cycles.

In the process of chemical production and mechanical manufacturing, powder usually appears as an associated organism. However, powder might explode while exposed to ignition sources, static electricity, and high-speed collisions, which result in the release of immense energy and extremely destructive consequences. Powder explosions account for 21% of explosion accidents; therefore, it is of great significance to analyse the explosion mechanism of different types of powder, build the explosion model, and finally put forward a feasible method of forestalling explosion. This study provides a comprehensive review and perspectives for synergistic explosion mechanism of combustible gas and different types of powder, such as polyolefin powder, and coal powder. The synergistic explosion parameters of powder and combustible gas were summarised and a explosion simulation model was constructed. In addition, this paper focuses on the analysis and study of gas-liquid-solid products after the explosion to capture the powder explosion mechanism. Finally, the scheme and suggestion for dust explosion suppression are provided. This article explores the mechanism of powder explosion fundamentally and puts forward higher safety recommendations as well as explosion suppression measures, which provide a theoretical and guiding basis for modern industrialisation and mechanically safer chemical production.

A novel phase change absorbent, diethylamine ethanol (DEEA)/2-(2-aminoethylamino)ethanol (AEEA)/H₂O-Al₂O₃ (γ), which can be abbreviated as DAH-Al₂O₃ (γ), was developed based on nanoparticle enhancement. The γ-Al₂O₃ nanoparticles had excellent dispersibility in the absorbent and could enhance the CO₂ loading of the absorbent more than other nanoparticles. The γ-Al₂O₃ nanoparticles slightly affected the phase separation ratio of the absorbent, but could reduce the viscosity of the CO₂rich phase and shorten the phase separation time. The nanoparticle migration in the two phases was explored, and γ-Al₂O₃ tended to migrate from the CO₂-rich to the CO₂-lean phase as CO₂ loading increased. Compared to the DAH absorbent, the DAH-Al₂O₃ absorbent had a 17.67% higher absorption rate and a 24.39% higher desorption rate. Over five cycles, the phase separation behavior of the absorbent with nanoparticles remained stable. Similarly, the γ-Al₂O₃ nanoparticles retained excellent dispersibility in the absorbent. The regeneration energy of the absorbent was 2.46 GJ·t^{- 1} CO₂, with 37.72% lower than the monoethanolamine absorbent. The strategy for the phase change absorbent with nanoparticle enhancement was feasible, providing a potential pathway for industrial carbon capture.