Frontiers of Chemical Science and Engineering最新文献

Methane cracking is considered a bridge technology between gray and green hydrogen production processes. In this work an experimental study of methane cracking in molten tin is performed. The tests were conducted in a quartz reactor (i.d. = 1.5 cm, L = 20 cm) with capillary injection, varying temperature (950–1070 °C), inlet methane flow rate (30–60 mL·min⁻¹) and tin height (0–20 cm). The influence of the residence time in the tin and in the headspace on methane conversion and on carbon morphology was investigated. The conversions obtained in tin and in the empty reactor were measured and compared with results of detailed kinetic simulations (CRECK). Furthermore, an expression of a global kinetic constant for methane conversion in tin was also derived. The highest conversion (65% at Q₀ = 30 mL·min⁻¹ and t = 1070 °C) is obtained for homogeneous gas phase reaction due to the long residence time (70 s), the presence of tin leads to a sharp decrease of residence time (1 s), obtaining a conversion of 35% at 1070 °C, thus meaning that tin owns a role in the reaction. Carbon characterization (scanning electron microscopy, Raman) reported a change in carbon toward sheet-like structures and an increase of the carbon structural order in the presence of molten tin media.

Bifunctional metal/zeolite materials are some of the most suitable catalysts for the direct hydroalkylation of benzene to cyclohexylbenzene. The overall catalytic performance of this reaction is strongly influenced by the hydrogenation, which is dependent on the metal sizes. Thus, systematically investigating the metal size effects in the hydroalkylation of benzene is essential. In this work, we successfully synthesized Ru and Pd nanoparticles on Sinopec Composition Materials No.1 zeolite with various metal sizes. We demonstrated the size-dependent catalytic activity of zeolite-supported Ru and Pd catalysts in the hydroalkylation of benzene, which can be attributed to the size-induced hydrogen spillover capability differences. Our work presents new insights into the hydroalkylation reaction and may open up a new avenue for the smart design of advanced metal/zeolite bi-functional catalysts.

The aluminum-water system is a promising propellant due to high energy and low signal characteristics, and the gel form is easier to store and utilize. In this work, hydrogels of water and aluminum particles were prepared using the low-molecular-weight gellant agarose. The various physical properties of gel systems, including the water loss rate, phase transition temperature, and centrifugal stability at different gellant and aluminum contents, were examined. Rheological properties were assessed through shear thinning tests, thixotropy tests, strain sweep analysis, and frequency sweep experiments. The microstructure of the gel was obtained through scanning electron microscopy images. The results show that the aluminum-hydrogel network structure is composed of micron-scale aluminum and agarose nanosheets, and the unique micro-nanostructure endows the gel with excellent mechanical strength and thermal stability, which improve with increasing gellant and aluminum contents. Notably, the gel with 2% agarose and 20% aluminum had the best performance; the storage modulus reached 90647 Pa, which was within the linear viscoelastic region, and the maximum withstand pressure was 111.2 kPa, which was 118.8% greater than that of the pure hydrogel. Additionally, the gel demonstrates remarkable shear thinning behavior and can undergo gel-sol transformation upon shearing or heating to exceeding 114 °C.

The enzymatic redox reactions in natural photosynthesis rely much on the participation of cofactors, with reduced nicotinamide adenine dinucleotide/nicotinamide adenine dinucleotide phosphate (NADH/NADPH) or their oxidized form (NAD⁺/NADP⁺) as an important redox power. The photocatalytic regeneration of expensive and unstable NADH/NADPH in vitro is an important process in enzymatic reduction and has attracted much research attention. Though different types of photocatalysts have been developed for photocatalytic NADH/NADPH regeneration, the efficiency is still relatively low. To elucidate the key factors affecting the performance of photocatalytic NADH/NADPH regeneration is helpful to rationally design the photocatalyst and improve the photocatalytic efficiency. In this paper, we overview the recent progress in photocatalytic NADH/NADPH regeneration with the focus on the strategies to improve the visible light adsorption, the charge separation and migration efficiency, as well as the surface reaction, which jointly determine the overall photocatalytic regeneration efficiency. The potential development of photocatalytic NADH/NADPH regeneration and photocatalytic-enzymatic-coupling system is prospected finally.

A functional hybrid nano-hydroxyapatite (carboxymethyl cellulose-phytic acid-n-HA, CMC-PA-n-HA) was prepared by adding CMC and PA. The results of Fourier transformation infrared spectra, X-ray diffraction, thermal gravimetric analysis and dispersion experiments indicated that the addition of CMC and PA affected the morphology, crystallinity and crystal size of hybrid n-HA, and CMC endowed hybrid n-HA with excellent dispersion. Scanning electron microscope results showed that CMC-PA-n-HA nanoparticle could be uniformly dispersed in chitosan (CS) matrix to obtain composite membrane by casting technology, so that the highest tensile strength of CMC-PA-n-HA/CS composite membrane was 69.64% and 144.45% higher than that of CS membrane and n-HA/CS composite membrane, respectively. Contact angle test showed that CMC-PA-n-HA effectively improved hydrophilicity of the CS membrane. The simulated body fluid immersion results indicated that the CMC-PA-n-HA/CS composite membrane not only exhibited good degradability but also promoted bone-like apatite deposition. The cell proliferation experiments proved that the introduction of PA made the composite membrane have better cell adhesion and proliferation ability. Antibacterial tests demonstrated that PA could effectively improve the antibacterial properties of the composite membrane, which is expected to be applied as guide bone tissue regeneration membrane.

Methanol-to-olefins, as a promising non-oil pathway for the synthesis of light olefins, has been successfully industrialized. The accurate prediction of process variables can yield significant benefits for advanced process control and optimization. The challenge of this task is underscored by the failure of traditional methods in capturing the complex characteristics of industrial processes, such as high nonlinearities, dynamics, and data distribution shift caused by diverse operating conditions. In this paper, we propose a novel hybrid spatial-temporal deep learning prediction model to address these issues. Firstly, a unique data normalization technique called reversible instance normalization is employed to solve the problem of different data distributions. Subsequently, convolutional neural network integrated with the self-attention mechanism are utilized to extract the temporal patterns. Meanwhile, a multi-graph convolutional network is leveraged to model the spatial interactions. Afterward, the extracted temporal and spatial features are fused as input into a fully connected neural network to complete the prediction. Finally, the outputs are denormalized to obtain the ultimate results. The monitoring results of the dynamic trends of process variables in an actual industrial methanol-to-olefins process demonstrate that our model not only achieves superior prediction performance but also can reveal complex spatial-temporal relationships using the learned attention matrices and adjacency matrices, making the model more interpretable. Lastly, this model is deployed onto an end-to-end Industrial Internet Platform, which achieves effective practical results.

Reducing the production costs of clean energy carriers such as hydrogen through scalable water electrolysis is a potential solution for advancing the hydrogen economy. Among the various material candidates, our group demonstrated transition-metal-based materials with tunable electronic characteristics, various phases, and earth-abundance. Herein, electrochemical water oxidation using Cu₂Se-V₂O₅ as a non-precious metallic electrocatalyst via a hydrothermal approach is reported. The water-splitting performance of all the fabricated electrocatalysts was evaluated after direct growth on a stainless-steel substrate. The electrochemically tuned Cu₂Se-V₂O₅ catalyst exhibited a reduced overpotential of 128 mV and provided a reduced Tafel slope of 57 mV·dec⁻¹ to meet the maximum current density of 250 mA·cm⁻². The optimized strategy for interfacial coupling of the fabricated Cu₂Se-V₂O₅ catalyst resulted in a porous structure with accessible active sites, which enabled adsorption of the intermediates and afforded an effective charge transfer rate for promoting the oxygen evolution reaction. Furthermore, the combined effect of the catalyst components provided long-term stability for over 110 h in an alkaline solution, which makes the catalyst promising for large-scale practical applications. The aforementioned advantages of the composite catalyst overcome the limitations of low conductivity, agglomeration, and poor stability of the pure catalysts (Cu₂Se and V₂O₅).

The nitridation reaction of calcium carbide and N₂ at high temperatures is the key step in the production of lime-nitrogen. However, the challenges faced by this process, such as high energy consumption and poor product quality, are mainly attributed to the lack of profound understanding of the reaction. This study aimed to improve this process by investigating the non-isothermal kinetics and reaction characteristics of calcium carbide nitridation reaction at different heating rates (10, 15, 20, and 30 °C·min⁻¹) using thermogravimetric analysis. The kinetic equation for the nitridation reaction of additive-free calcium carbide sample was obtained by combining model-free methods and model-fitting method. The effect of different calcium-based additives (CaCl₂ and CaF₂) on the reaction was also investigated. The results showed that the calcium-based additives significantly reduced reaction temperature and activation energy E_a by about 40% with CaF₂ and by 55%–60% with CaCl₂. The reaction model f(α) was also changed from contracting volume (R3) to 3-D diffusion models with D3 for CaCl₂ and D4 for CaF₂. This study provides valuable information on the mechanism and kinetics of calcium carbide nitridation reaction and new insights into the improvement of the lime-nitrogen process using calcium-based additives.

We report results from computational modeling of the relative stability of germanosilicate SCM-15 structure due to different distribution of germanium heteroatoms in the double four-member rings (D4Rs) of the framework and the orientation of the structure directing agent (SDA) molecules in the as-synthesized zeolite. The calculated relative energies of the bare zeolite framework suggest that structures with germanium ions clustered in the same D4Rs, e.g., with large number of Ge–O–Ge contacts, are the most stable. The simulations of various orientations of the SDA in the pores of the germanosilicate zeolite show different stability order—the most stable models are the structures with germanium spread among all D4Rs. Thus, for SCM-15 the stabilization due to the presence of the SDA and their orientation, is thermodynamic factor directing both the formation of specific framework type and Ge distribution in the framework during the synthesis. The relative stability of bare structures with different germanium distribution is of minor importance. This differs from SCM-14 germanosilicate, reported earlier, for which the stability order is preserved in presence of SDA. Thus, even for zeolites with the same chemical composition and SDA, the characteristics of their framework lead to different energetic preference for germanium distribution.

Organic matter-induced mineralization is a green and versatile method for synthesizing hybrid nanostructured materials, where the material properties are mainly influenced by the species of natural biomolecules, linear synthetic polymer, or small molecules, limiting their diversity. Herein, we adopted dendrimer poly(amidoamine) (PAMAM) as the inducer to synthesize organosilica-PAMAM network (OSPN) capsules for mannose isomerase (MIase) encapsulation based on a hard-templating method. The structure of OSPN capsules can be precisely regulated by adjusting the molecular weight and concentration of PAMAM, thereby demonstrating a substantial impact on the kinetic behavior of the MIase@OSPN system. The MIase@OSPN system was used for catalytic production of mannose from D-fructose. A mannose yield of 22.24% was obtained, which is higher than that of MIase in organosilica network capsules and similar to that of the free enzyme. The overall catalytic efficiency (k_cat/K_m) of the MIase@OSPN system for the substrate D-fructose was up to 0.556 s⁻¹·mmol⁻¹·L. Meanwhile, the MIase@OSPN system showed excellent stability and recyclability, maintaining more than 50% of the yield even after 12 cycles.