Chinese Journal of Chemical Engineering最新文献

Direct-Z-scheme g-C₃N₄/Ti₃C₂/TiO₂ photocatalyst with giant internal electric field was prepared by one-step aqueous sonication self-assembly method using g-C₃N₄ and MXene of Ti₃C₂ as the source materials. The chemical composition and structure of the catalysts was characterized by FT-IR, XRD, SEM, TEM, and XPS. The XPS characterization indicated that Ti₃C₂ was partially oxidized to TiO₂ during the composite process. As a result, an efficient direct-Z-scheme heterojunction structure consisting of the g-C₃N₄ and TiO₂ with Ti₃C₂ as an electron bridge was constructed. The photocatalytic performance of the prepared catalysts was evaluated by degrading the rhodamine B (RhB) wastewater. Compared with the single g-C₃N₄, the g-C₃N₄/Ti₃C₂/TiO₂ composite photocatalyst exhibited efficient and stable photocatalytic degradation ability, with a degradation efficiency as high as 99.2% for RhB under optimal conditions (2% Ti₃C₂, pH = 3). The high degradation performance of g-C₃N₄/Ti₃C₂/TiO₂ for RhB was attributed to the combination of Ti₃C₂, TiO₂, and g-C₃N₄ components, forming a direct-Z-scheme heterojunction with a high-speed electron transport channel structure. The role of Z-scheme heterojunctions in electron transport is verified by photoelectrochemical characterization, along with photoluminescence (PL). Our research provides a simple method to design photocatalysts by constructing direct-Z-scheme electron transport channels for highly efficient treatment of dye wastewater.

Modern industrial processes are typically characterized by large-scale and intricate internal relationships. Therefore, the distributed modeling process monitoring method is effective. A novel distributed monitoring scheme utilizing the Kantorovich distance-multiblock variational autoencoder (KD-MBVAE) is introduced. Firstly, given the high consistency of relevant variables within each sub-block during the change process, the variables exhibiting analogous statistical features are grouped into identical segments according to the optimal quality transfer theory. Subsequently, the variational autoencoder (VAE) model was separately established, and corresponding T² statistics were calculated. To improve fault sensitivity further, a novel statistic, derived from Kantorovich distance, is introduced by analyzing model residuals from the perspective of probability distribution. The thresholds of both statistics were determined by kernel density estimation. Finally, monitoring results for both types of statistics within all blocks are amalgamated using Bayesian inference. Additionally, a novel approach for fault diagnosis is introduced. The feasibility and efficiency of the introduced scheme are verified through two cases.

Nickel is a strategic resource in social life and defense technology, playing an essential role in many fields, such as alloys and batteries. With the decrease in nickel sulfide, it is of great significance to extract nickel from laterite. The limonitic laterite is a kind of rich nickel-cobalt-scandium resource. At present, there are few reviews on the extraction of limonitic laterite. This study reviews the hydrometallurgical processes for limonitic laterite ores and the methods of recovering valuable elements. The mineralogical characteristics are analyzed, and the typical mineral compositions are summarized. The main hydrometallurgical processes are compared and discussed, including reduction roasting-ammonia leaching, sulfuric acid pressure leaching, nitric acid pressure leaching, and the atmospheric nitric acid leaching (DNi process). The methods of recovering nickel, cobalt, scandium, and iron are emphatically outlined. Finally, reasonable suggestions are proposed for comprehensive utilization. This study can provide a reference for industrial development and diversified applications.

The research on the thermal property of the hydrate has recently made great progress, including the understanding of hydrate thermal conductivity and effective thermal conductivity (ETC) of hydrate-bearing sediment. The thermal conductivity of hydrate is of great significance for the hydrate-related field, such as the natural gas hydrate exploitation and prevention of the hydrate plugging in oil or gas pipelines. In order to obtain a comprehensive understanding of the research progress of the hydrate thermal conductivity and the ETC of hydrate-bearing sediment, the literature on the studies of the thermal conductivity of hydrate and the ETC of hydrate-bearing sediment were summarized and reviewed in this study. Firstly, experimental studies of the reported measured values and the temperature dependence of the thermal conductivity of hydrate were discussed and reviewed. Secondly, the studies of the experimental measurements of the ETC of hydrate-bearing sediment and the effects of temperature, porosity, hydrate saturation, water saturation, thermal conductivity of porous medium, phase change, and other factors on the ETC of hydrate-bearing sediment were discussed and reviewed. Thirdly, the research progress of modeling on the ETC of the hydrate-bearing sediment was reviewed. The thermal conductivity determines the heat transfer capacity of the hydrate reservoir and directly affects the hydrate exploitation efficiency. Future efforts need to be devoted to obtain experimental data of the ETC of hydrate reservoirs and establish models to accurately predict the ETC of hydrate-bearing sediment.

The sulfate radical-based photocatalytic process is supposed to be the most promising way to degrade organic pollutants. However, the development of a suitable and efficient photocatalyst is very challenging. The 40LaFeO₃-CuFe₂O₄ (40LFO-CFO) nanocomposite was constructed and its catalytic performance was studied using Rhodamine B (RhB) as the target pollutant. 40LFO-CFO exhibited excellent RhB degradation by the persulfate (PS)-assisted photocatalytic process compared to the pristine LFO and CFO. The degradation rate constant for RhB by 40LFO-CFO in the Vis/PS system was 2.22 h⁻¹ which is 3.04 times and 5.05 times higher than the pristine LFO (0.73 h⁻¹) and CFO (0.44 h⁻¹), respectively. Furthermore, the trapping experiments and EPR spectra proved that h⁺ plays a leading role in the bleaching of RhB for the 40LFO-CFO/PS/Vis system. The enhanced photocatalytic oxidation activity of 40LFO-CFO could be attributed to the unique charge carriers flow in 40LFO-CFO due to the Z-scheme and the cooperation effect between photocatalysis and PS activation. The recycle tests confessed the stability of 40LFO-CFO. Additionally, the intermediates and products of RhB are detected by liquid chromatography-mass spectrometry (LC-MS), and the photocatalytic degradation routes of RhB for the 40LFO-CFO/Vis/PS system were proposed. Moreover, the 40LFO-CFO nanocomposite has a superior catalytic performance for other organics, suggesting that it is a promising heterocatalyst because of its high catalytic activity and stability for the PS-assisted photocatalytic process.

Isosorbide is a novel bio-based material derived as a secondary dehydration product of sorbitol. This work focuses on the kinetics of sulfuric acid-catalyzed dehydration of sorbitol under conditions of nonconstant volume. Herein, the effects of stirring rate, catalyst dosage, reaction temperature, and reaction time on the dehydration reaction of sorbitol were investigated. The yield of isosorbide up to 77.13% was obtained after 1.5 h of reaction time under conditions of 2 kPa, 1.0% (mass) catalyst dosage, and 413.15 K. Based on the sorbitol dehydration reaction mechanism and a simplified reaction network, a kinetic model was developed in this work. A good agreement was accomplished between kinetic modeling and experiments between 393.15 and 423.15 K. The fitting results indicate that side reactions with higher activation energies are more affected by reaction temperatures, and the main side reaction that influences the selectivity of isosorbide is the oligomerization reaction among the primary dehydration products of sorbitol. The model fitting of the catalyst amounts effect shows that the effective concentration of sulfuric acid would be reduced with the increase of dosage due to the molecular agglomeration effect. Hopefully, the kinetic experiments and modeling results obtained in this work will be helpful to the design and optimization of the industrial sorbitol dehydration process.

The simulated moving bed (SMB) chromatographic separation is a continuous compound separation process based on the differences in adsorption capacity exhibited by distinct constituents of a mixture on the fluid phase and stationary phase. The prediction of axial concentration profiles along the beds in a unit is crucial for the operating optimization of SMB. Though the correlation shared by operating variables of SMB has an enormous impact on the operational state of the device, these correlations have been long overlooked, especially by the data-driven models. This study proposes an operating variable-based graph convolutional network (OV-GCN) to enclose the underrepresented correlations and precisely predict axial concentration profiles prediction in SMB. The OV-GCN estimates operating variables with the Spearman correlation coefficient and incorporates them in the adjacency matrix of a graph convolutional network for information propagation and feature extraction. Compared with Random Forest, K-Nearest Neighbors, Support Vector Regression, and Backpropagation Neural Network, the values of the three performance evaluation metrics, namely MAE, RMSE, and R², indicate that OV-GCN has better prediction accuracy in predicting five essential aromatic compounds' axial concentration profiles of an SMB for separating p-xylene (PX). In addition, the OV-GCN method demonstrates a remarkable ability to provide high-precision and fast predictions in three industrial case studies. With the goal of simultaneously maximizing PX purity and yield, we employ the non-dominated sorting genetic algorithm-II optimization method to perform multi-objective optimization of the PX purity and yield. The outcome suggests a promising approach to extracting and representing correlations among operating variables in data-driven process modeling.

Hydroxylation of inert benzene through the activation of the C_sp2-H bond is a representative reaction about the transformation of C–H bonds to C–O bonds, which has far-reaching guiding significance but remains a challenging scientific problem. To overcome this problem, a series of VO_x-Ga₂O₃/SiO₂–Al₂O₃ were prepared to achieve an efficient and economical hydroxylation path of benzene to phenol. The results showed that the phenol yield was 72.89% (selectivity > 98.1%) under the optimum conditions. The reason is that the C–H bond in the benzene ring is activated by heterolysis over a VO_x-Ga₂O₃/SiO₂–Al₂O₃ catalyst. Meanwhile, the introduction of aluminum (Al) and gallium (Ga) made a qualitative change in the catalyst, enhancing the electron motion and spin motion of vanadium species, resulting in the increase of V⁴⁺/V⁵⁺ ratio. In addition, the catalyst can provide an optimal acidic environment and a three-dimensional cross-linked surface structure that facilitates product diffusion.