Catalytic behavior in CH4 decomposition of catalysts derived from red mud: Impact of residual Na2O

Catalyst samples for CH₄ decomposition were prepared from red mud (RM) by an acid-leaching neutralization precipitation approach. Water-washing the resultant precipitates multiple times, followed by drying at 105 °C and calcination at 500 °C, resulted in a threshold of residual Na₂O, equivalent to 96% Na₂O removal. Drying the precipitate at a higher temperature of 200 °C, followed by repeated water washing, provided a deeper Na₂O removal of 99% and made the resultant samples more active for the targeted reaction. Subsequently, four catalyst samples with a simulated red mud composition and NaOH contents from 0 to 0.3 wt% were prepared and the catalytic test results revealed that the Na₂O remaining in the RM-derived catalysts did not only inhibit their activation in CH₄ but also lower their maximal activities for CH₄ decomposition. Finally, two catalysts with the same simulated red mud composition and their Na impregnated respectively on Fe₂O₃ and a mixture support of Al₂O₃-SiO₂-TiO₂ were prepared and tested to explore the effect of Na distribution on the activation behavior of RM-derived catalysts for CH₄ decomposition. The activity testing results showed that it was the Na residual dispersed on iron oxides in the RM-derived samples to significantly inhibit the activation of CH₄ decomposition.     

Plasma-assisted CO2 reforming of methane over Ni-based catalysts: Promoting role of Ag and Sn secondary metals

Carbon dioxide (CO₂) and methane (CH₄) are the primary greenhouse gases (GHGs) that drive global climate change. CO₂ reforming of CH₄ or dry reforming of CH₄ (DRM) is used for the simultaneous conversion of CO₂ and CH₄ into syngas and higher hydrocarbons. In this study, DRM was investigated using Ag–Ni/Al₂O₃ packing and Sn–Ni/Al₂O₃ packing in a parallel plate dielectric barrier discharge (DBD) reactor. The performance of the DBD reactor was significantly enhanced when applying Ag–Ni/Al₂O₃ and Sn–Ni/Al₂O₃ due to the relatively high electrical conductivity of Ag and Sn as well as their anti-coke performances. Using Ag–Ni/Al₂O₃ consisting of 1.5 wt% Ag and 5 wt% Ni/Al₂O₃ as the catalyst in the DBD reactor, 19% CH₄ conversion, 21% CO₂ conversion, 60% H₂ selectivity, 81% CO selectivity, energy efficiency of 7.9% and 0.74% (by mole) coke formation were achieved. In addition, using Sn–Ni/Al₂O₃, consisting of 0.5 wt% Sn and 5 wt% Ni/Al₂O₃, 15% CH₄ conversion, 19% CO₂ conversion, 64% H₂ selectivity, 70% CO selectivity, energy efficiency of 6.0%, and 2.1% (by mole) coke formation were achieved. Sn enhanced the reactant conversions and energy efficiency, and resulted in a reduction in coke formation; these results are comparable to that achieved when using the noble metal Ag. The decrease in the formation of coke could be correlated to the increase in the CO selectivity of the catalyst. Good dispersion of the secondary metals on Ni was found to be an important factor for the observed increases in the catalyst surface area and catalytic activities. Furthermore, the stability of the catalytic reactions was investigated for 1800 min over the 0.5 wt% Ag-5 wt% Ni/Al₂O₃ and 0.5 wt% Sn-5 wt% Ni/Al₂O₃ catalysts. The results showed an increase in the reactant conversions with an increase in the reaction time.     

Effect of aluminium acetyl acetonate on the hydrogen and nitrogen permeation of carbon molecular sieves membranes

With a growing interest in hydrogen as energy carrier, the efficient purification of hydrogen from gaseous mixtures is very important. This paper addresses the separation of hydrogen using Carbon Molecular Sieves Membranes (CMSM), which show an attractive combination of high permeability, selectivity and stability. Supported CMSM containing various amounts of aluminium have been prepared from novolac and aluminium acetyl acetonate (Al(acac)₃) as carbon and alumina precursors. The thickness of the CMSM layers depend on the content of Al(acac)₃ in the dipping solution, which also has influence in the pore size and pore size distribution of the membranes. The permeation properties of the membranes against the Al content in the membrane follows a volcano shape, where the membrane containing 4 wt (%) of Al(acac)₃ has the best properties and was stable during 720 h for hydrogen at 150 °C and 6 bar pressure difference. All the CMSM have permeation properties well above the Robeson Upper limit.     

Mathematical Modeling of Drying Processes of Selected Fruits and Vegetables

This study investigates the behavior of fruit and vegetable samples during drying. The experimental data are fitted to several different thin-layer drying models. Regression analysis is used to determine model parameters, while statistical indicators serve to evaluate the goodness of fit. The power function model gives the best fit for all examined samples. Based on this model, different drying and heat storage technologies can be combined to ensure that the required residual moisture content of an agricultural product is reached. It is demonstrated on the case of a specific Togolese processing plant that under favorable conditions, fossil fuel consumption can be decreased by 33 %.     

Effect of wind condition on unintended hydrogen release in a hydrogen refueling station

Ambient condition, especially the wind condition, is an important factor to determine the behavior of hydrogen diffusion during hydrogen release. However, only few studies aim at the quantitative study of the hydrogen diffusion in a wind-exist condition. And very little researches aiming at the variable wind condition have been done. In this paper, the hydrogen diffusion in different wind condition which including the constant wind velocity and the variable wind velocity is investigated numerically. When considering the variable wind velocity, the UDF (user defined function) is compiled. Characteristics of the FGC (flammable gas cloud) and the HMF (hydrogen mass fraction) are analyzed in different wind condition and comparisons are made with the no-wind condition. Results indicate that the constant wind velocity and the variable wind velocity have totally different effect for the determination of hydrogen diffusion. Comparisons between the constant wind velocity and the variable wind velocity indicate that the variable wind velocity may cause a more dangerous situation since there has a larger FGC volume. More importantly, the wind condition has a non-negligible effect when considering the HMF along the radial direction. As the wind velocity increases, the distribution of the HMF along the radial direction is not Gaussian anymore when the distance between the release hole and the observation line exceeds to a critical value. This work can be a supplement of the research on the hydrogen release and diffusion and a valuable reference for the researchers.     

A novel design for humidifying an open-cathode proton exchange membrane fuel cell using anode purge

The low performance of open-cathode proton-exchange-membrane fuel cells (OCPEMFCs) is attributed to the low-humidity ambient air supplied to the cathode using electric fans. To improve the OCPEMFC performance, this paper proposes a novel humidification method by collecting water purged from the anode and supplying it to the open cathode. The OCPEMFC performance is evaluated at various humidifier distances from the cathode inlet, and it is compared with that where no humidifier is used when the OCPEMFC operates under three different current levels of 1, 5, and 8 A. The results show that the novel design improves the stack power, and optimal performance is achieved at a humidifier distance of 2 cm. The energy efficiency achieves an improvement between 1.4% and 1.8% when a humidifier is used.     

Description of the thermodynamic properties and fluid-phase behavior of aqueous solutions of linear,branched, and cyclic amines

The SAFT-γ Mie group-contribution equation of state is used to represent the fluid-phase behavior of aqueous solutions of a variety of linear, branched, and cyclic amines. New group interactions are developed in order to model the mixtures of interest, including the like and unlike interactions between alkyl primary, secondary, and tertiary amine groups (NH₂, NH, N), cyclic secondary and tertiary amine groups (cNH, cN), and cyclic methine-amine groups (cCHNH, cCHN) with water (H₂O). The group-interaction parameters are estimated from appropriate experimental thermodynamic data for pure amines and selected mixtures. By taking advantage of the group-contribution nature of the method, one can describe the fluid-phase behavior of mixtures of molecules comprising those groups over broad ranges of temperature, pressure, and composition. A number of aqueous solutions of amines are studied including linear, branched aliphatic, and cyclic amines. Liquid–liquid equilibria (LLE) bounded by lower critical solution temperatures (LCSTs) have been reported experimentally and are reproduced here with the SAFT-γ Mie approach. The main feature of the approach is the ability not only to represent accurately the experimental data employed in the parameter estimation, but also to predict the vapor–liquid, liquid–liquid, and vapor–liquid–liquid equilibria, and LCSTs with the same set of parameters. Pure compound and binary phase diagrams of diverse types of amines and their aqueous solutions are assessed in order to demonstrate the main features of the thermodynamic and fluid-phase behavior.     

Identifying catalyst layer compositions of proton exchange membrane fuel cells through machine-learning-based approach

Membrane electrode assembly (MEA) is considered a key component of a proton exchange membrane fuel cell (PEMFC). However, developing a new MEA to meet desired properties, such as operation under low-humidity conditions without a humidifier, is a time- and cost-consuming process. This study employs a machine-learning-based approach using K-nearest neighbor (KNN) and neural networks (NN) in the MEA development process by identifying a suitable catalyst layer (CL) recipe in MEA. Minimum redundancy maximum relevance and principal component analysis were implemented to specify the most important predictor and reduce the data dimension. The number of predictors was found to play an essential role in the accuracy of the KNN and NN models although the predictors have self-correlations. The KNN model with a K of 7 was found to minimize the model loss with a loss of 11.9%. The NN model constructed by three corresponding hidden layers with nine, eight, and nine nodes can achieve the lowest error of 0.1293 for the Pt catalyst and 0.031 for PVA as a good additive blending in the CL of the MEA. However, even if the error is low, the prediction of PVA seems to be inaccurate, regardless of the model structure. Therefore, the KNN model is more appropriate for CL recipe prediction.     

Optimized Biocatalytic Synthesis of 2-Selenopyrimidine Nucleosides by Transglycosylation**

Selenium-modified nucleosides are powerful tools to study the structure and function of nucleic acids and their protein interactions. The widespread application of 2-selenopyrimidine nucleosides is currently limited by low yields in established synthetic routes. Herein, we describe the optimization of the synthesis of 2-Se-uridine and 2-Se-thymidine derivatives by thermostable nucleoside phosphorylases in transglycosylation reactions using natural uridine or thymidine as sugar donors. Reactions were performed at 60 or 80 °C and at pH 9 under hypoxic conditions to improve the solubility and stability of the 2-Se-nucleobases in aqueous media. To optimize the conversion, the reaction equilibria in analytical transglycosylation reactions were studied. The equilibrium constants of phosphorolysis of the 2-Se-pyrimidines were between 5 and 10, and therefore differ by an order of magnitude from the equilibrium constants of any other known case. Hence, the thermodynamic properties of the target nucleosides are inherently unfavorable, and this complicates their synthesis significantly. A tenfold excess of sugar donor was needed to achieve 40−48 % conversion to the target nucleoside. Scale-up of the optimized conditions provided four Se-containing nucleosides in 6–40 % isolated yield, which compares favorably to established chemical routes.     

Brönsted方程动力学模型研究ZSM-5催化乙烯齐聚及芳构化活性和酸强度分布之间的定量关系

乙烯催化齐聚和芳构化是烯烃高值化和合成液体燃料的关键过程，采用NH₃-TPD谱图分析计算方法得到的探针分子脱附活化能作为催化剂的酸位点强度分布的参数，结合线性自由能理论在Br?nsted方程中引入酸强度对反应的影响因子γ作为动力学方程参数关联探针分子脱附活化能与反应活化能，明确固体酸酸强度的基准在催化动力学方程中的物理意义。建立同为MFI拓扑结构 Si /Al摩尔比为12.5、19、25、60、70的ZSM-5分子筛催化剂上不同酸强度位和乙烯齐聚及芳构化中氢转移、齐聚、芳构化各单元步骤以及对应的烷烃、低碳烯烃和芳烃产物分布的定量关系。根据拟合得到动力学参数γ可以发现不同强度的酸位点对乙烯齐聚及芳构化具有不同的作用系数。氨脱附活化能(DAE)为90 kJ·mol^-1的酸位点是氢转移反应的主要活性位点，而对于乙烯齐聚反应中主要的活性酸位点为DAE 90 kJ·mol^-1和124 kJ·mol^-1，DAE为150 kJ·mol^-1的酸位点是芳构化反应的主要活性位点。