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The hydrogenation of CO 2 or CO to single organic product has received widespread attentions. Here we show a highly efficient and selective catalyst, Mo 3 S 4 @ions-ZSM-5, with molybdenum sulfide clusters ([Mo 3 S 4 ] n+ ) confined in zeolitic cages of ZSM-5 molecular sieve for the reactions. Using continuous fixed bed reactor, for CO 2 hydrogenation to methanol, the catalyst Mo 3 S 4 @NaZSM-5 shows methanol selectivity larger than 98% at 10.2% of carbon dioxide conversion at 180 °C and maintains the catalytic performance without any degeneration during continuous reaction of 1000 h. For CO hydrogenation, the catalyst Mo 3 S 4 @HZSM-5 exhibits a selectivity to C 2 and C 3 hydrocarbons stably larger than 98% in organics at 260 °C. The structure of the catalysts and the mechanism of CO x hydrogenation over the catalysts are fully characterized experimentally and theorectically. Based on the results, we envision that the Mo 3 S 4 @ions-ZSM-5 catalysts display the importance of active clusters surrounded by permeable materials as mesocatalysts for discovery of new reactions. A series of materials containing Mo-S clusters confined in zeolitic cages of ZSM-5 are reported and shown to be efficient for CO 2 or CO hydrogenation with >98% selectivity to methanol, stable over 1000 h, or C 2 and C 3 hydrocarbons, stable over 100 h.

Modelling catalytic fixed bed reactors with a small tube-to-particle diameter ratio requires a detailed description of the interactions between fluid flow, intra-particle transport, and the chemical reaction(s) within the catalyst. Particle-resolved computational fluid dynamics (PRCFD) simulations are the most promising approach to predict the behaviour of these reactors accurately, since they take into account the local packed bed structure explicitly. In this work, a conjugated heat and mass transfer model for use in PRCFD simulations is presented in order to couple the fluid flow through the fixed bed with transport and reaction in the porous catalyst, while guaranteeing the no-slip boundary condition at the fluid-solid interface. For this purpose, the solutions of the solid and fluid domain are computed separately and are coupled by calculation and updating the boundary condition at the particle surface. Owing to the consideration of secondary gradients, the developed transfer model is also valid for unstructured calculation meshes containing non-orthogonal cells at the fluid-solid interface. Such meshes are often used to resolve complex geometries, such as a packed bed, in a computationally efficient manner. The coupling approach is validated using cases for which an analytical solution or literature correlations derived from experimental data are available. The simulation results of a short catalytic packed bed with rings catalysing the partial oxidation of n-butane to maleic anhydride exemplify the potential of PRCFD involving reactions to analyse the catalyst performance in great detail.

Alkene feedstocks are used to produce polymers with a market expected to reach 128.4 million metric tons by 2027. Butadiene is one of the impurities poisoning alkene polymerization catalysts and is usually removed by thermocatalytic selective hydrogenation. Excessive use of H 2 , poor alkene selectivity and high operating temperature (e.g. up to 350 °C) remain the most significant drawbacks of the thermocatalytic process, calling for innovative alternatives. Here we report a room-temperature (25~30 °C) electrochemistry-assisted selective hydrogenation process in a gas-fed fixed bed reactor, using water as the hydrogen source. Using a palladium membrane as the catalyst, this process offers a robust catalytic performance for selective butadiene hydrogenation, with alkene selectivity staying around 92% at a butadiene conversion above 97% for over 360 h of time on stream. The overall energy consumption of this process is 0.003 Wh/mL butadiene , which is thousands of times lower than that of the thermocatalytic route. This study proposes an alternative electrochemical technology for industrial hydrogenation without the need for elevated temperature and hydrogen gas. Industrial thermocatalytic hydrogenation requires excessive H 2 gas and high temperature operation. Here, the authors report a room-temperature electrochemistry-assisted hydrogenation process using a palladium membrane as the catalyst and water as the hydrogen source, eliminating the need for H 2 gas.

The purpose of this study is to explore a new low-cost and high-efficiency biochar adsorption material. The residual sludge as solid waste and fresh bamboo with fast growth and high yield were used as raw materials, modified by the KOH chemical activation method, and pyrolyzed in a tubular furnace with nitrogen atmosphere to obtain sludge biomass bamboo charcoal. In the performance test, the H 2 S gas adsorption experiment in a fixed bed reactor and the heavy metal adsorption experiment in soil were designed. Using different proportions of biochar, the preparation process of biochar was optimized by adjusting the raw material ratio and activation conditions. The results showed that when dealing with H2S gas, the appropriate amount of sludge can improve the adsorption effect, while the increase of bamboo component will reduce the adsorption rate. In the soil Cr(VI) restoration experiment, it was found that the best restoration effect was achieved after adding 10% biochar and applying it for 28 days, and the restoration rate reached 63.5%.

Indonesia has an abundance of various types of agricultural products. One of the abundance of agricultural products in Indonesia is cassava, but the skin is rarely used, so it can be a source of waste. Cassava peels can be used as a source of bioenergy in the form of biogas. This research was conducted by mixing the ratio of domestic waste mixing IPAL Cemara PDAM Tirtanadi and water by including cassava peels. In the slurry, cassava peels added about 8-9 % This study aims to determine the amount of biogas produced from bioreactors with and without silica gel as media. The ratio of domestic waste from IPAL Cemara PDAM Tirtanadi and water 1: 0, 1: 0.5, 1: 0.4 1: 0.3. The retention time during 23 days. The parameters tested from this study were COD, TSS, and VS. From the results of the research, it was found biogas from bioreactor ratio of 1: 0. In the bioreactor with silica gel media biogas was found on the 19th day with a pressure of 499.8 Pa, however in bioreactor without silica gel media, biogas was found at 294 Pa.

Biodiesel from waste oil is produced using heterogeneous catalyzed transesterification in a fixed bed reactor (FBR). Potassium iodide/calcium oxide/alumina (KI/CaO/Al2O3) catalyst was prepared through the processes of calcination and impregnation. The novel catalyst was analyzed with X‐ray diffraction (XRD), scanning electron microscopy (SEM), and energy dispersive X‐ray spectrometer (EDX). The design of experiment (DoE) method resulted in a total of 20 experimental runs. The significance of 3 reaction parameters, namely catalyst bed height, methanol to waste oil molar ratio, and residence time, and their combined impact on biodiesel yield is investigated. Both the artificial neural network (ANN) based on artificial intelligence (AI) and the Box‐Behnken design (BBD) based on response surface methodology (RSM) were utilized in order to optimize the process conditions and maximize the biodiesel production. A quadratic regression model was developed to predict biodiesel yield, with a correlation coefficient (R) value of 0.9994 for ANN model and a coefficient of determination (R2) value of 0.9986 for BBD model. The maximum amount of biodiesel that can be produced is 98.88 % when catalyst bed height is 7.87 cm, molar ratio of methanol to waste oil is 17.47 : 1, and residence time is 3.12 h. The results of this study indicate that ANN and BBD models can effectively be used to optimize and synthesize the highest %yield of biodiesel in a FBR. The production of biodiesel involves the transesterification of waste oil in a fixed bed reactor using a catalyst composed of potassium iodide, calcium oxide, and alumina. Predicting and validating optimal conditions for biodiesel production is accomplished using artificial neural network (ANN) and response surface methodology (RSM). The ANN and RSM are effective tools for statistical modeling of biofuel manufacturing processes.

This paper deals with the adsorption of an anionic dye, Eriochrome Black T (EBT), from aqueous solutions onto sawdust, which is a natural, eco-friendly, widespread, and a low-cost bio sorbent. The aim of the work is to append values to the wood industry waste. Thus, sawdust was used as adsorbent in both batch reactor (BR) and fixed bed column (FBC), and various operating parameters influencing the adsorption process were investigated. The kinetic and the equilibrium adsorption results were found to agree with, respectively, the prediction of the pseudo-second-order equation and the Langmuir model. This latter allowed also the determination of the maximum EBT dye adsorbed amount, which was found to be about 40.96 mg EBT per gram of sawdust at pH = 4, corresponding to % dye removal of about 80%. In addition, the influence of various parameters on the dye adsorption, such as the adsorbent dose, the aqueous phase pH, and the initial dye concentration, was also examined. In batch experiments, The EBT adsorbed amount was found to increase either by increasing the amount of sawdust or by decreasing the aqueous phase pH, whereas, in the fixed bed column, the EBT retention was found to increase by decreasing the flow rate of the dye through the column. The overall data indicate that the EBT adsorption is mainly governed by the electrostatic interactions occurring between the adsorbent material and the dye.

Acid-modified red mud supported by peanut shells (MRP) catalysts were prepared for the catalytic wet persulfate oxidation (CWPO) process of dyes wastewater (containing methyl orange (MO), NH3-N, and Cr6+) in batch and continuous fixed bed reactors. Importantly, the influence of NH3-N and Cr6+ on the catalytic performance of the MRP catalyst was primarily studied. In the CWPO process, the reactors had a remarkable degradation efficiency (72–97%) of MO in the dyes wastewater. In the batch reactor, with the increase of NH3-N concentration (5–20 mg L−1), the degradation efficiency of MO was maintained at 93%. When NH3-N, Cr6+, and MO coexist, the degradation of MO had slight inhibition with 87.24%, which indicated that MO concentration was still controlled by MRP under the coexistence system, and the order of the removal effect of MRP on the three pollutants in the reactors was as follows: MO > NH3-N > Cr6+. Furthermore, in the fixed reactor, with the increasing of NH3-N or Cr6+ concentration, the MO degradation removal decreased to about 84%. The results showed that the degradation effect of MO in a fixed bed is still considerable. Then, the SEM and FTIR results indicated that SO4·−, ·OH, and O2−· generated in the CWPO process and Fe2+ and oxygen-containing functional groups on MRP played a major role on the degradation of pollutants. This study showed that this novel MRP is a promising catalyst with promising applications in composite dyes wastewater.

MnO 2 based photothermal catalysis has been demonstrated to be a promising technology to eliminate pollutants in air. However, the relationship between catalytic activity and MnO 2 crystal phase has not been revealed. Herein, we hydrothermally synthesized four MnO 2 catalysts, α-MnO 2 , β-MnO 2 , γ-MnO 2 and δ-MnO 2 , and systematically studied their structural properties and photothermal conversion behavior. The α-MnO 2 was proved to simultaneously possess large specific surface area (54.28 m 2  g −1 ), developed < 10 nm pores, and high low-valence manganese (Mn 2+  + Mn 3+ ) content, as well as the robust photothermal conversion ability. The photothermally catalytic behavior was evaluated through degrading gaseous formaldehyde in both batch and fixed bed experiments. As we expected, the α-MnO 2 showed the best activity for formaldehyde removal and the highest CO 2 yield under xenon light illumination. In the meantime, the α-MnO 2 had good stability of photothermal catalysis that was verified by the repeated cycling tests in the batch reactor and the durable test in the fixed bed reactor. Through detecting the intermediates and reactive oxygen species, a plausible mechanism of photothermal catalysis was proposed to illustrate the degradation route of formaldehyde on MnO 2 . Graphical Abstract The mechanism of photothermal catalysis degradation for formaldehyde over α-MnO 2

For the first time, the catalytic oxidation of Kraft lignin over a solid heterogeneous catalyst was studied in a continuous lab‐scale trickle‐bed reactor. This catalytic process is able to depolymerize Kraft lignin and produce phenolic compounds of interest such as vanillin. The impact of operating conditions such as temperature, residence time, contact time, catalyst loading and lignin concentration was evaluated. The formation of vanillin, the main phenolic compound detected in reaction products, was favored at medium temperature (200 °C), short contact time (<1gcat.min.gfeed−1), high catalyst loading (32 g) and low lignin concentration (5 g.L−1). The vanillin productivity is 30 times higher in a continuous fixed bed reactor than in a batch reactor. The catalytic hydrothermal oxidation of Kraft lignin was carried out in a continuous fixed bed triphasic reactor with a copper‐based solid catalyst. The production of phenolic compounds was observed, vanillin being the main phenolic compound. A parametric study was performed to determine the optimum operating conditions: medium temperature (200 °C), short contact time, short residence time and high fluid space velocity lead to the best productivity of vanillin and other derivatives.