The multipath application of green resources needs to be realised under the carbon neutrality goal. Worldwide, biomass is a resource in urgent need of treatment. In this paper, corn stover biomass (YM) or biochar with different particle sizes (YMF or YMX) was added during the preparation of coal-water slurry to investigate its effect on the performance of coal-water slurry and the micro-mechanism. The results showed that the fixed viscosity concentration of coal-water slurry (CYWS) with YM was only 47.42%, and the flowability was 49.9 mm, which made the slurry performance poor. The fixed viscosity concentration of coal-water slurry (CFWS) blended with YMF and coal-water slurry (CXWS) blended with YMX increased by 10.41% and 14.24%, respectively, compared with CYWS. Meanwhile, CXWS had the lowest thixotropy and yield stress, with a yield stress of only 16.13 Pa, which was 77.31 Pa lower than that of CYWS. This indicates that YMX treated by charring and milling is more favorable to be blended with coal to prepare coal-water slurry. This is due to the enhanced hydrophilicity and electronegativity of YMX. The enhanced hydrophilicity reduces the tendency to form three-dimensional networks in coal-water slurry, while the enhanced electronegativity improves the electrostatic repulsion between particles, which is beneficial to the dispersion of particles. In the subsequent EDLVO analyses, the same idea was proved.

Self-assembly of block copolymers (BCPs) is highly intricate and is adsorbing extensive experimental and simulation efforts to reveal it for maximizing structural order and device performances. The coarse-grained (CG) molecular dynamics (MD) simulation offers a microscopic angle to view the self-assembly of BCPs. Although some molecular details are sacrificed during CG processes, this method exhibits remarkable computational efficiency. In this study, a comprehensive CG model for polystyrene-block-poly(2- vinylpyridine), PS-b-P2VP, one of the most extensively studied BCPs for its high Flory-Huggins interaction parameter, is constructed, with parameters optimized using target values derived from all-atom MD simulations. The CG model precisely coincides with various classical self-assembling morphologies observed in experimental studies, matching the theoretical phase diagrams. Moreover, the conformational asymmetry of the experimental phase diagram is also clearly revealed by our simulation results, and the phase boundaries obtained from simulations are highly consistent with experimental results. The CG model is expected to extend to simulate the self-assembly behaviors of other BCPs in addition to PS-b-P2VP, thus increasing understanding of the microphase separation of BCPs from the molecular level.

The complex dense-phase pneumatic conveying of pulverized coal process was studied using an electrical capacitance tomography (ECT) signal that represented the motion characteristics of gasesolid twophase flow. The fluctuation characteristics of conveying process signals are inseparable from the flow pattern. The denoised ECT signal and noise signal were obtained by db2 wavelet analysis. It was found that all noise signals were white Gaussian noise. Based on the assumption of the equal probability distribution of pulverized coal concentration, this paper proved that the time series distribution of pulverized coal concentration in the pipeline should obey the normal distribution. Furthermore, through the analysis of the distribution characteristics of the power spectral density function of denoised ECT signals of four flow patterns, they were a-dimensional fractal Brownian motion (fBm) signals, and the parameter a was estimated by the detrended fluctuation analysis. Based on the fBm characteristics of denoised ECT signals and white Gaussian noise, this paper proposed a method for calculating the pulverized coal concentration in the dense-phase pneumatic conveying. In addition to the method of concentration estimation with the significance of engineering guidance, this research can help people to further understand essential characteristics of ECT signals in the dense-phase pneumatic conveying.

The preparation of dispersible MFI-type zeolite nanoparticles with open micropores is challenging. Herein, a rapid and effective ultrasound-assisted liquid-phase exfoliation method along with a freezedrying process for redispersion of calcined silicalite-1 (S-1) zeolite nanoparticle aggregates using 3- aminopropanol as an exfoliating agent is demonstrated. The exfoliation of S-1 zeolite nanoparticles is characterized by X-ray diffraction, scanning electron microscopy and DLS particle size analysis. The effects of drying methods of as-synthesized zeolite nanoparticle suspension, zeolite contents in frozen nanoparticle suspension, exfoliating agent concentrations, and zeolite doses in ultrasonic suspension on exfoliation efficiency are systematically investigated. It is found that the S-1 zeolite nanoparticle (~70 nm) achieves a yield up to 95% through a 30 min ultrasonic exfoliation in a 3-aminopropanol solution along with a freeze-drying process. The proposed exfoliation mechanism involves two primary stages: guest molecule insertion followed by water expansion, both substantially enhanced by tip sonication. This work offers a comprehensive understanding of the exfoliation process, provides valuable insights into the dispersion of sintered zeolite nanoparticles.

In this work, a simple two-step electrodeposition was employed to prepare PPy-Cu/GF (PPy, polypyrrole; GF, graphite felt) composite cathodes for the nitrate reduction. Characterized results revealed that the introduction of PPy as an intermediate layer resulted in the transformation of both granular and dendritic Cu in form of Cu⁺/Cu⁰, Cu²⁺ on the electrode surface. The NO₃^--N of 50 mg·L^-1 was almost completely removed (99.01%) using the PPy-Cu/GF cathode under the optimum condition, which is obviously higher than the GF, PPy/GF and Cu/GF electrodes. NO₃^--N removal was slightly affected over the pH scale of 3.0 e11.0, whereas increasing the current density from 10 to 25 mA·cm^-2 boosted the reduction of NO₃^--N. At a Cl concentration of 2000 mg·L1, the removal of NO₃^--N was slightly reduced, while the selectivity for N₂ increased dramatically due to the active chlorine could oxidize NH₄⁺-N to N₂. Meanwhile, PPy-Cu/ GF cathode exhibits an average removal rate of 97.83% within 12 cycles, highlighting its potential for application in actual water bodies. The EPR analysis and the active species trapping experiment confirmed that the nitrate reduction on the PPy-Cu/GF cathode mainly relies on direct reduction mediated by electron transfer, while ^*H influences the reduction of nitrite to ammonia.

Solid solution hinders the extraction of bromine resources from bittern. To separate chlorineebrominebased solid solution in bittern tail solution, the solubilities of the quaternary system KCl-KBr-NaCl-NaBr-H₂O and its ternary subsystem NaBr-KBr-H₂O at 333.15 K were determined by the isothermal dissolution method, and the corresponding phase diagrams were conducted. An improved model was employed to predict the solubilities of the quaternary system KCl-KBr-NaCl-NaBr-H₂O at 333.15 K. The calculated results coincide with the experimental values, implying that the prediction method is feasible. A closed loop crystallization process for the separation of chlorineebromine-based solid solution in bittern tail solution was proposed and NaBr was obtained with a purity of 98.23%.

A biodegradable and green organic compound octadecyl dimethyl benzyl amm-onium chloride (ODBAC) was used as an efficient inhibitor for cold rolled steel (CRS) in phosphoric acid (H₃PO₄). The mechanism of adsorption and film formation of ODBAC on CRS was studied through experimental and theoretical calculations. The weight loss method shows that the inhibition efficiency of ODBAC can reach 92.01% at a concentration of 10 mg·L^-1. The adsorption of ODBAC on the CRS surface conforms to the Langmuir isotherm model, which is a mixed adsorption mainly based on physical adsorption. The X-ray photoelectron spectroscopy (XPS) and contact angle results confirmed the existence of the ODBAC film and steel surface's hydrophobicity has been significantly enhanced. Electrochemical test results reveal that the film's formation mainly inhibits the cathodic corrosion reaction and effectively increases the charge transfer resistance. Quantum chemical calculations have found that N18 in ODBAC and C24 and C25 on the benzene ring are the key active adsorption sites. Molecular dynamics simulation results indicate that ODBAC can sharply reduce the free fraction volume to 8% and inhibit the diffusion of corrosion particles, meaning that the formed ODBAC film makes it difficult for corrosion particles to penetrate, thus improving the corrosion resistance of CRS in H₃PO₄.

The production of medical waste (MW) is a growing concern, particularly in light of the increasing annual generation and the exacerbating effects of the COVID-19 pandemic. Traditional techniques such as incineration and landfilling present significant limitations. In this study, a self-designed 50 kW arc plasma reactor was employed to conduct gasification experiments on nitrile-butadiene rubber (NBR) which served as a model of MW and a mixture of NBR/SiO₂ which served as a model of glass-containing MW, using CO₂ as the working gas. The CO₂ thermal plasma gasification process not only ensures the safe and efficient disposal of MW, but also facilitates its effective conversion into H₂ and CO, achieving a carbon conversion efficiency of 94.52%. The yields of H₂ and CO reached 98.52% and 81.83%, respectively, and the specific energy consumption was as low as 3.55 kW·h·k·g^-1. Furthermore, the addition of SiO₂ was found to inhibit the gasification of NBR and cause damage to the reactor. Therefore, it is recommended that glass waste should be removed prior to the treatment of MW. The CO₂ thermal plasma gasification technology can not only eliminate environmental and health risks posed by MW, but also convert it into syngas for further utilization. This provides a promising approach to the harmless and resource disposal of MW, while also contributing to the comprehensive utilization of greenhouse gases.

Bioelectrochemical regulation has been proved to enhance the traditional anaerobic digestion (AD) of organic wastes. However, few investigations have explored whether it is possible to enhance the production of biomethane from raw corn stover (CS). A single-chamber microbial electrolysis cell (MEC) was incorporated with an AD to form a new system (MEC-AD) with aiming at more efficient bioconversion of CS to biomethane. The performance and microbiological characteristics of MEC-AD was investigated, and compared with conventional AD, which were inoculated with original inoculum (UAD) and electrically domesticated inoculum (EAD), respectively. The results showed that MEC-AD achieved the highest CH₄ yield of 239.13 ml·g^-1 volatile solids (VS), which was 29.28% and 12.44% higher than those of UAD and EAD, respectively. MEC-AD also achieved higher substance conversion rates of 73.24% VS, 91.16% cellulose, and 77.24% hemicellulose, respectively. The community characteristics of microorganisms revealed that the relative abundance and interactions of functional microorganisms in MEC-AD were obviously different from UAD and EAD. In MEC-AD, Electroactive bacteria (Sedimentibacter) with electrotrophic methanogens (Methanosarcina and Methanosaeta) in anodic biofilms established electrotrophic methanogenesis through direct interspecies electron transfer (DIET). The process of methanotrophic methanogenesis was facilitated by the interactions between fermentative acid-producing bacteria (FABs), syntrophic organic acid oxidation bacteria (SOBs), and methylotrophic methanogens (Methyl-HMs) in MEC-AD suspensions. Efficient synergistic interactions between these functional microorganisms improved the performance of MEC-AD in converting CS to produce biomethane. The study could provide an effective means for achieving higher AD biomethane production from raw CS.

This study utilizes a visualization nozzle and spray experimental platform to experimentally investigate the flow focusing/blurring nozzle. It is found that the working mode of the nozzle transitions from flow focusing to flow transition and eventually to flow blurring as the gas flow rate increases or the tube hole distance decreases. Conversely, an increase in liquid flow rate only facilitates the transition from flow focusing to flow transition. Changes in the gas/liquid flow rate or tube hole distance influence the gas shear effect and the gas inertial impact effect inside the nozzle, which in turn alters the working mode. An increase in gas flow rate results in a shift of the droplet size distribution towards smaller particle sizes in the flow blurring mode, whereas an increase in liquid flow rate produces the opposite effect. Notably, the impact of the gas flow rate on these changes is more pronounced than that of the liquid flow rate.

The indiscriminate use and disposal of ciprofloxacin (CIP) have led to its detection in water globally, which pose a huge risk to public health and water environment. Herein, (Zn-Al) LDHs modified 3D reduced graphene oxide nanocomposite ((Zn-Al) LDHs/3D-rGO) was synthesized through a feasible onepot hydrothermal method for CIP removal. The highly distributed (Zn-Al) LDHs flakes on the surface of 3D-rGO endow the resulted (Zn-Al) LDHs/3D-rGO with an excellent adsorption performance for CIP. The adsorption results showed that the adsorption process could be well interpreted by Temkin isothermal model and the pseudo second-order kinetics model. The maximal adsorption capacity of 20.01 mg·g^-1 for CIP could be achieved under the optimal conditions optimized by response surface methodology (RSM). The inhibitory effect of co-existing ions on CIP adsorption were also discussed. The probable adsorption mechanism might be ascribed to p p interactions, hydrogen bonding, electrostatic, and surface complexation. Regeneration tests showed that the obtained 3D porous material also possessed pronounced recyclability. The obtained (Zn-Al) LDHs/3D-rGO holds a great potential for removal of CIP from actual wastewater.

Jet agitation is known as a maintenance-free stirring technique for nuclear wastewater treatment and demonstrates great potential in transport of radioactive particles. Removal processes of horizontal sediment beds driven by impinging jets were experimentally investigated using image capture and processing technique. The beds were composed of heavy fine particles with particle density ranging from 3700 to 12600 kg·m^-3 and particle diameter from 5 to 100 mm. The jet Reynolds number varied between 4300 and 9600. The single-phase large eddy simulation method was used for calculating both jet flow characteristics and wall shear stresses. The effects of jet strength, particle density, particle diameter, and bed thickness on bed mobility in terms of the critical Shields numbers were considered. Specifically, the critical Shields number was found to be intricately related to properties of particles, and independent of jet intensity. A new Shields number curve for stainless-steel particles was found, and a model was proposed to predict the transport rate of thin beds, with R² = 0.96.

The purity of electronic-grade chemicals significantly impacts electronic components. Although crystallization has been used to purify cerium ammonium nitrate (CAN), the impurity removal mechanism underlying different crystallization parameters remains unclear. Traditional analytical methods of inductively coupled plasma mass spectrometry (ICP-MS) have problems in detecting trace Fe accurately, because of the high concentration of Ce and interference of polyatomic ions. Therefore, this study developed a new method integrating the standard addition and internal standard methods and explored the role of the kinetic energy discrimination mode. This new approach effectively overcomes Ce-related matrix interference and fills the gap in ultra-trace impurity detection. Furthermore, the study investigated the effects of cooling rate, seed mass loading and seed size on the removal of Fe impurity. The seed mass loading affects the average crystal size through regulating secondary nucleation and crystal growth. The removal of Fe in CAN is determined by surface adsorption and agglomeration. Under the condition of the cooling rate of 0.2 K·min^-1, and addition of 0.5% (mass) 600-680 mm seeds, the Fe content is the lowest, at only 0.24 mg·L^-1, and the Fe removal rate reaches 92.28%.

Natural gas is widely regarded as an efficient, relatively clean, and economically viable energy source. Its safe operation and continuous supply through pipeline infrastructure has led to its prominence in the energy sector. Methanol plays an important role in the natural gas industry, typically serving as a solvent or hydrate inhibitor. Therefore, the accurate estimation of thermodynamic properties for methane/ methanol binary is extremely important to optimise the operating parameter, maximise the dehydration effect, and reduce the cost. As the Helmholtz energy equation of state is expected to offer high accuracy in predicting the vapour liquid equilibrium of methane/methanol binary, four reducing parameters were derived based on collected experimental data. Additionally, the sensitivities of various reducing parameter combinations were simultaneously investigated. The results demonstrated a strong agreement between predicted fractions and experimental data, with the UMADs (uncertainty-weighted mean absolute deviation) of 3.484 and 0.665 for liquid and vapour phases, respectively. Meanwhile, it is deemed “very likely”, “likely”, and “unlikely” to achieve acceptable prediction for 3-parameter optimisation, 2-parameter optimisation and, 1-parameter optimisation, respectively.

Pressurized oxy-fuel combustion is a next-generation and low-cost carbon capture technology with industrial application potential. This work presents an innovative research explorationdcoupling coal pressurized fluidized bed oxy-fuel combustion technology with energy utilization of poultry manure as a renewable and carbon-neutral fuel, in order to capture CO₂ and solve the problem of poultry manure treatment simultaneously. In this study, a stable co-combustion of coal and chicken manure in a laboratory-scale pressurized fluidized bed under typical oxy-fuel condition (30%O₂/70%CO₂, i.e., Oxy-30) is achieved. The key parameters including the combustion pressure (0.1-0.5 MPa) and chicken-manure proportion (0% to 100%) and their impacts on fundamental combustion efficiency, carbon conversion, nitrogen and sulfur pollutant emissions, and residue ash characteristics have been investigated. The result show that pressurization favors an increase in the CO₂ enrichment concentration and fluidized bed combustion efficiency. During co-combustion under 0.1 and 0.3 MPa, the CO₂ concentration in the flue gas is the highest when the chicken manure blending ratio (M_pm) is 25%. Although the NO emissions fluctuate and even increase as M_pm increases, the co-combustion of coal and chicken manure exhibits a synergistic effect in reducing NO conversion rate (X_NO). The effect of pressurization on reducing NO emission is significant, X_NO at M_pm = 25% decreasing from 15% to 5% as the pressure (P) increases from 0.1 to 0.5 MPa. As P increases from 0.1 to 0.5 MPa and M_pm increases from 0% to 50%, the SO₂ emissions and conversion rates decrease. The self-desulfurization process plays an important role in the reduction of SO₂ emissions during pressurized oxy-fuel co-combustion. The aim of this work is to advance the development and application of pressurized fluidized bed oxy-fuel co-combustion technology and promote a circular bioeconomy and carbon-free waste management for biomass derived from livestock manure.

Liquid-liquid dispersion is often performed in stirred tanks, which are valued for their ease of operation, high droplet generation rate and effective droplet dispersion. Many relevant simulations use the Eulerian-Eulerian method, combining population balance equations with statistical models to forecast droplet breakage. Conversely, the Eulerian-Lagrangian (E-L) method provides precise tracking of individual droplets, which is crucial for simulating dispersion processes. However, E-L simulation faces challenges in integrating droplet breakage effectively. To address this issue, our research introduces a probabilistic approach for droplet breakages. It assumes that a longer time increases the likelihood of breakup; a droplet breaks if the calculated probability exceeds a random value from 0 to 1. Consequently, the simulated breakage frequency becomes independent of the Lagrangian time step. The Sauter mean diameter and droplet size distribution can be accurately predicted by this probabilistic approach. By closely monitoring droplet motion, we reveal the complexity of droplet trajectories and the detailed patterns of circulation in stirred tanks. These insights contribute to a deeper understanding of liquidliquid dispersion dynamics.

In petroleum, mercaptan impurities generate malodorous fumes that pose risks to both human health and the environment, and leading to substandard oil quality. Lye desulfurization is a widely employed technique for eliminating mercaptans from oil. In traditional scrubber towers, lye and oil are poorly mixed, the desulfurization efficiency is low, and the lye consumption is high. To enhance washing efficiency, a droplet micromixer and corresponding fiber coalescence separator were developed. By optimizing the structure and operating parameters, more effective mixing and separation were achieved, and both caustic washing and desulfurization were enhanced. The proposed mixer/separator outperforms the industry standard by reducing the caustic loading by 30% and offers superior economic and engineering performances. The results of this study offer a direction for designing and optimizing a mercaptan removal unit to enhance the scrubbing effectiveness and decrease expenses to achieve more efficient and green production process.

Activated carbon (AC) is considered to be an excellent adsorbent due to its high specific surface area and various functional groups. AC powders are available in sizes ranging from 44 to 150 mm. Its particle size prevent its separation from the soil. Therefore, when AC powder is applied to Cd-contaminated soil, it only reduces the bioavailability of Cd and Cd is not necessarily removed but semi-immobilized. Recovery of adsorbent materials from the soil is therefore a preferred soil remediation method. In order to achieve the separation of Cd from soil and the recovery and reuse of AC, a batch of phenolic resin (PR) -carboxymethyl cellulose (CMC)-activated carbon (AC) composite (PCC-800) with uniform particle diameter (diameter 0.8 mm) and high compressive strength was prepared. PCC-800 composites were made of PR/ CMC/AC calcined at 800 ℃ in a certain ratio. The Barrett Joyner Halender results showed that the PCC- 800 spheres own a mesoporous structure. The compressive strength of PCC-800 pellets was 20.6 N. After first adsorption cycle, total Cd in the soil decreased by 52.18% while bioavailable Cd decreased to 25.68% of the original soil. After three cycles, the recovery rates of PCC-800 were 90.37% and the adsorption regeneration was 72.73%. The PCC-800 immobilized Cd by adsorption, precipitation and complexation reaction. This study demonstrates the potential for developing adsorbents that are both easily separable from soil and highly effective in adsorption.

To solve the serious volume expansion problem of Sb-based anode materials in the alloying/dealloying process, a strategy combining electrospinning and hydrogen reduction is proposed to prepare a series of Sb-based alloys/carbon nanofiber composites (SbM/CNFs, M = Co, Zn, Ni). Inactive elements are innovatively introduced to form Sb based alloys with enhanced stability. The results show that the content of SbCo nanoparticles is high to 69.12% (mass), which are uniformly dispersed in carbon fibers. When evaluated as anode material for SIBs, SbCo/CNFs anode exhibits excellent sodium storage capacity, the initial discharge capacity is 580.0 mA h·g^-1 at 0.1 A g^-1, which can hold 483.5 mA h·g^-1 after 100 cycles. Even the current density increases to 1.0 A g^-1, the specific capacity still maintains at 344.5 mA h·g^-1 after 150 cycles. The improved sodium storage capacity is attributed to the synergistic effect of conductive carbon fibers and SbCo nanoparticles with uniform dispersion, which not only provide excellent electronic conductivity, but also enhance structural stability to reduce volume change.

The efficient and cost-effective implementation of ammonia borane (AB) hydrolysis dehydrogenation for hydrogen storage is crucial. This study investigated the role of solid acid Amberlyst-15 (A-15) for hydrogen evolution from AB hydrolysis. Notably, AB hydrogen evolution rate can reach 194.15 ml·min^-1 at 30℃, with a low apparent activation energy of 8.20 kJ·mol^-1. After five cycles of reuse, the reaction involving A-15 could keep a conversion rate of about 93%. The AB hydrolysis follows quasi first-order kinetics with respect to the AB concentration and quasi zero-order kinetics with respect to the A-15 mass. According to the characterization results of XRD, ATR-FTIR, and in-situ MS, the boric acid was the dominant hydrolyzate, while water as a hydrogen donor in this reaction. Furthermore, based on the reasoning that hydrogen bonds between A-15 and AB (aq) promotes the diffusion of AB, release of H₂ and the cleavage of OdH bond of H₂O, a possible mechanism was proposed.

A MnFe₂O₄@SiO₂@NH₂ coupled with acylated multi-walled carbon nanotubes (AMWCNT_S) was prepared using an easy one-step modification approach and applied for the visible light-assisted removal of ciprofloxacin (CIP). FT-IR, XRD, VSM, Raman spectrum, FE-SEM, BJH/BET, UV-Vis, and band gap analysis were used to characterize nanocomposites. In terms of CIP removal, the nanocomposites outperformed both AMWCNT_S and MnFe₂O₄@SiO₂@NH₂ nanoparticles. At a pH of 7, an initial CIP concentration of 25 mg·L^-1, a reaction time of 40 min, and a catalyst dose of 0.8 g·L^-1, all of the CIP was degraded. The ratios of BOD₅/ COD (5-day biological oxygen demand/chemical oxygen demand) and BOD₅/TOC (5-day biological oxygen demand/total organic carbon) at the beginning of the process were 0.22 and 0.71, respectively, and reached 0.755 and 1.21 at the end of the process, which signposts the conversion of non-biodegradable wastewater into biodegradable wastewater. Scavenger studies disclosed that hydroxyl radicals and holes had the greatest effect on the degradation of CIP. The toxicity of the final effluent was also investigated with E. coli bacteria, and the results showed a very good effect of the process in the field of effluent sterilization. Equilibrium data fully followed first-order kinetics, with a reaction rate constant of 0.109 min^-1. Also, the half-life for the complete degradation of CIP was equal to 6.8 min. The CIP removal efficiency still remained at 9.4% in the five cycles. MnFe₂O₄@SiO₂@NH₂@AMWCNTS gave a pronounced potential for eliminating CIP from aqueous environment.

Freshwater scarcity has emerged as a critical global environmental challenge. Flow-electrode capacitive deionization (FCDI) represents a promising technology for achieving efficient and low-energy seawater desalination. This study presents a novel flow-electrode material, nitrogen-doped porous carbon (NPC), which is derived from biomass and demonstrates both cost-effectiveness and high performance. The NPC material is synthesized from bean shells through high-temperature pre-carbonization followed by activation with KHCO₃, resulting in a rich porous structure, increased specific surface area, and high graphitization degree, which collectively confer superior capacitance performance compared to activated carbon (AC). Desalination experiments indicate that the FCDI performance of the NPC flow-electrode surpasses that of the AC flow-electrode. Specifically, at a voltage of 2.5 V in a 6 g·L^-1 NaCl solution, the NPC system achieves an average salt removal rate (ASRR) of 104.9 mg·cm^-2·min^-1, with a charge efficiency (CE) of 94.0% and an energy consumption (EC) of only 4.4 kJ·g^-1. Furthermore, the NPC-based FCDI system exhibits commendable desalination cycling stability, maintaining relatively stable energy consumption and efficiency after prolonged continuous desalination cycles. This research holds significant implications for the advancement of environmentally friendly, low-cost, high-performance FCDI systems for large-scale applications.

China has abundant resources of high-alumina coal (HAC). However, its application as a raw gasification material is limited owing to high ash-fusion characteristics. For overcoming the limitation, this study employed Xinjiang coal (XJ), having a low ash fusion temperature, to improve the ash fusibility and viscosity of high-alumina Jungar coal (JG). The evolution of Al-containing phases and structures during mixed ash melting were investigated based on XRD, XPS, ²⁷Al NMR, high-temperature stage microscopy (HTSM), and thermodynamic simulations. An increase in the XJ mass ratio resulted in the transformation of gehlenite to anorthite and mullite, producing more amorphous materials at high temperature. These phenomena were manifested at a microscopic imaging as an increase in the number of reaction/melting sites and their area expansion rate, as well as a decrease in ash area shrinkage and melting temperature. Moreover, the introduction of XJ altered the aluminaeoxygen network, reducing the binding to the silicaoxygen network and converting some [AlO₆]^9- to [AlO₄]^5- as the relative concentration of O_2- and O^- increases. Consequently, the decrease in the stability of the aluminate structure improves the AFT and viscosity. Based on these results, a mechanism to improve the ash fusion characteristics of HAC based on coal blending is proposed.

This study introduces an innovative computational framework leveraging the transformer architecture to address a critical challenge in chemical process engineering: predicting and optimizing light olefin yields in industrial methanol-to-olefins (MTO) processes. Our approach integrates advanced machine learning techniques with chemical engineering principles to tackle the complexities of non-stationary, highly volatile production data in large-scale chemical manufacturing. The framework employs the maximal information coefficient (MIC) algorithm to analyze and select the significant variables from MTO process parameters, forming a robust dataset for model development. We implement a transformer-based time series forecasting model, enhanced through positional encoding and hyperparameter optimization, significantly improving predictive accuracy for ethylene and propylene yields. The model's interpretability is augmented by applying SHapley additive exPlanations (SHAP) to quantify and visualize the impact of reaction control variables on olefin yields, providing valuable insights for process optimization. Experimental results demonstrate that our model outperforms traditional statistical and machine learning methods in accuracy and interpretability, effectively handling nonlinear, non-stationary, highvolatility, and long-sequence data challenges in olefin yield prediction. This research contributes to chemical engineering by providing a novel computerized methodology for solving complex production optimization problems in the chemical industry, offering significant potential for enhancing decisionmaking in MTO system production control and fostering the intelligent transformation of manufacturing processes.

One-carbon (C1) compounds, such as CO₂, methane, and methanol, are emerging as promising feedstocks for next-generation biomanufacturing due to their abundance and low cost. In recent years, there has been growing interest in harnessing microorganisms to convert these carbon sources into valuable natural products (NPs), which offers great potential for sustainable development. This review systematically outlines recent advancements in biocatalysts, synthetic biology, and process optimization aimed at improving the feasibility and scalability of producing C1-based NPs. Current challenges and insights into NPs biomanufacturing from C1 compounds are thoroughly examined in the areas of multi-gene editing, metabolic regulation, and synthetic microbial consortium. With ongoing progress in biosynthetic tools and fermentation techniques, C1-based biomanufacturing is becoming a versatile and sustainable platform for generating diverse value-added products.

Hexafluoropropylene oxide (HFPO) is a crucial fluorinated chemical mainly synthesized from hexafluoropropylene (HFP) through the oxidation of oxygen. However, the reaction network and kinetic characteristics are not fully understood yet, resulting in a lack of theoretical basis for synthesis process improvement. Here, the free radical reaction mechanism and complete reaction network involved in the noncatalytic oxidation of HFP to synthesize HFPO was explored by density functional theory. Transition state theory was employed to calculate the intrinsic reaction rate constants for elementary reactions. Based on theoretical reaction rate ratios, reaction pathways were selected, and a simplified reaction network was derived. It was found that byproducts were formed owing to the decomposition of HFPO and subsequent reactions with excessive oxygen while oxygen tended to participate more in the main reaction under oxygen-deficient conditions. The variations in reaction pathways occurring at different HFP/oxygen molar ratios was well elucidated by comparing with experimental data. This research establishes a robust theoretical foundation for optimizing and regulating the synthesis of HFPO.

Kernel-based slow feature analysis (SFA) methods have been successfully applied in the industrial process fault detection field. However, kernel-based SFA methods have high computational complexity as dealing with nonlinearity, leading to delays in detecting time-varying data features. Additionally, the uncertain kernel function and kernel parameters limit the ability of the extracted features to express process characteristics, resulting in poor fault detection performance. To alleviate the above problems, a novel randomized auto-regressive dynamic slow feature analysis (RRDSFA) method is proposed to simultaneously monitor the operating point deviations and process dynamic faults, enabling real-time monitoring of data features in industrial processes. Firstly, the proposed Random Fourier mappingbased method achieves more effective nonlinear transformation, contrasting with the current kernelbased RDSFA algorithm that may lead to significant computational complexity. Secondly, a randomized RDSFA model is developed to extract nonlinear dynamic slow features. Furthermore, a Bayesian inference-based overall fault monitoring model including all RRDSFA sub-models is developed to overcome the randomness of random Fourier mapping. Finally, the superiority and effectiveness of the proposed monitoring method are demonstrated through a numerical case and a simulation of continuous stirred tank reactor.

During the production of natural gas hydrates, micron-sized sand particles coexist with hydrate within the transportation pipeline, posing a significant threat to the safety of pipeline flow. However, the influence of sand particles on hydrate formation mechanisms and rheological properties remains poorly understood. Consequently, using a high-pressure reactor system, the phase equilibrium conditions, hydrate formation characteristics, hydrate concentration, and the slurry viscosity in micron-sized sand system are investigated in this work. Furthermore, the effects of sand particle size, sand concentration, and initial pressure on these properties are analyzed. The results indicate that a high concentration of micron-sized sand particles enhances the formation of methane hydrates. When the volume fraction of sand particles exceeds or equals 3%, the phase equilibrium conditions of the methane hydrate shift to the left relative to that of the pure water system(lower temperature, higher pressure). This shift becomes more pronounced with smaller particle sizes. Besides, under these sand concentration conditions, methane hydrates exhibit secondary or even multiple formation events, though the formation rate decreases. Additionally, the torque increases significantly and fluctuates considerably. The RoscoeBrinkman model yields the most accurate slurry viscosity calculations, and as sand concentration increases, both hydrate concentration and slurry viscosity also increase.