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.

During steam reforming, the performance of a catalyst and amount/property of coke are closely related to reaction intermediates reaching surface of a catalyst. Herein, modification of reaction intermediates by placing Mg-Al-hydrotalcite above Ni/KIT-6 catalyst in steam reforming of glycerol was conducted at 300 to 600 °C. The results revealed that the catalytic activity of Ni/KIT-6 in the lower bed was enhanced with either Mg₁-Al₅-hydrotalcite (containing more acidic sites) or Mg₅-Al₁-hydrotalcite (containing more alkaline sites) as upper-layer catalyst. The in situ infrared characterization of steam reforming demonstrated that Mg-Al-hydrotalcite catalyzed the deoxygenation of glycerol, facilitating the reforming of the partially deoxygenated intermediates over Ni/KIT-6. Mg-Al-hydrotalcite as protective catalyst, however, did not protect the Ni/KIT-6 from formation of more coke. Nonetheless, this did not lead to further deactivation of Ni/KIT-6 while Mg₅-Al₁-hydrotalcite even substantially enhanced the catalytic stability, even though the coke was much more significant than that in the use of single Ni/KIT-6 (52.7% vs. 28.6%). The reason beneath this was change of the property of coke from more aliphatic to more aromatic. Mg₅-Al₁-hydrotalcite catalyzed dehydration of glycerol, producing dominantly reaction intermediates bearing C=C, which formed the catalytic coke of with carbon nanotube as the main form with smooth outer walls as well as higher aromaticity, C/H ratio, crystallinity, crystal carbon size, thermal stability, and resistivity toward oxidation on Ni/KIT-6 in the lower bed. In comparison, the abundance of acidic sites on Mg₁-Al₅-hydrotalcite catalyzed the formation of more oxygen-containing species, leading to the formation of carbon nanotubes of rough surface on Ni/KIT-6.

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.

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.

Typically, the hydroxide agents, such as sodium hydroxide and potassium hydroxide, which have corrosive properties, are used in the carbon activation process. In this study, potassium oxalate (K₂C₂O₄), a less toxic and non-corrosive activating reagent, was used to synthesize activated carbon from the solid residue after autohydrolysis treatment. The effect of the autohydrolysis treatment and the ratio of the K₂C₂O₄/solid residue are presented in this study. Moreover, the comparison between the activated carbon from bamboo and biochar from the solid residue are also reported. The resulting activated carbon from the solid residue exhibited a high surface area of up to 1432 m²·g^–1 and a total pore volume of up to 0.88 cm³·g^–1. The autohydrolysis treatment enhanced the microporosity properties compared to those without pretreatment of the activated carbon. The microporosity of the activated carbon from the solid residue was dominated by the pore width at 0.7 nm, which is excellent for CO₂ storage. At 25 °C and 1.013 × 10⁵ Pa, the CO₂ captured reached up to 4.1 mmol·g^–1. On the other hand, the ratio between K₂C₂O₄ and the solid residue has not played a critical role in determining the porosity properties. The ratio of the K₂C₂O₄/solid residue of 2 could help the carbon material reach a highly microporous textural property that produces a high carbon capture capacity. Our finding proved the benefit of using the solid residue from the autohydrolysis treatment as a precursor material and offering a more friendly and sustainable activation carbon process.

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.

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.

Membrane gas separation is considered an energy-saving technique to extract He from natural gas due to no phase change and room temperature operation. However, the membrane performance was strongly limited by the trade-off between permeance and selectivity. Herein, novel 4,4′-(hexafluoroisopropylidene)diphthalic anhydride (6FDA)-2,2′-bis(3-amino-4-hydroxyphenyl)hexafluoropropane (APAF)-5-amino-2-(4-aminobenzene)benzimidazole (BIA) asymmetric membranes with a thickness of 300 nm were successfully prepared by the non-solvent induced phase separation method. The membrane performance was modulated by regulating dope solution compositions (e.g., tetrahydrofuran and polymer concentration). The ideal He/CH₄ selectivity was 124 and the optimized He permeance reached 87 GPU, beyond the current upper bound. He/CH₄ selectivity was 75 and He permeance was 73 GPU for the binary mixture feed containing 0.2 mol % He. The membrane showed good resistance to CO₂ and C₂H₆, which are the typical impurities in natural gas. The 6FDA-APAF-BIA membranes have good stability (> 160 h), which can provide great potential in He extraction from natural gas.

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 fabrication of suitable MFI zeolites to effectively produce para-xylene through the alkylation between toluene and methanol is highly desired. Here, the two-dimensional pillared MFI zeolite was modified by silicalite-1, and its morphology and structure were systematically investigated by tuning the concentration of Si species during the secondary crystallization process. The MFI zeolites were characterized by X-ray diffraction, transmission electron microscopy, pyridine-infrared and N₂ adsorption-desorption isotherms. The characterization results showed that the external Brønsted acid sites of surface passivated P-MFI-x samples have been successfully shielded. Interestingly, the P-MFI-23 showed long lifetime and high selectivity of para-xylene (about 35%) based on the cooperation between opened interlamellar structure and passivated silicalite-1 layer. It was found that the accumulated hard coke in the interior of MFI zeolites not only blocked the channels of zeolites but also covered the acidic sites, resulting in the deactivation of catalyst. Furthermore, the highest selectivity of para-xylene (about 48%) can be achieved for P-MFI-30 under harsh reaction condition, which also exhibited excellent regeneration property in the alkylation reaction between toluene and methanol. The strategy described in present research may open a window for the design of other advanced materials.