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Preparation, characterization and catalytic performance of Pt supported on porous carbonaceous materials in the oxidation of toluene as a volatile organic compound
Progress in Reaction Kinetics and Mechanism ( IF 0.7 ) Pub Date : 2019-11-29 , DOI: 10.1177/1468678319887931
Niloofar Atashi 1 , Mohammad Hasan Peyrovi 1 , Nastaran Parsafard 2
Affiliation  

Platinum-carbonaceous catalysts were prepared by the wet impregnation method and tested for catalytic oxidation of toluene as a volatile organic compound. The textural properties of the constructed catalysts were considered by X-ray diffraction, X-ray fluorescence, inductively coupled plasma – optical emission spectroscopy, Fourier transform infrared, scanning electron microscope and N2 adsorption–desorption analysis. The catalytic assessments showed that the best activity (>99%) and high stability and selectivity to CO2 (>99%) are related to platinum-supported carbon nanotube. The curves of the conversion and selectivity demonstrate that the performance of catalysts to eliminate the volatile organic compound and turn it into CO2 conforms to the following descending order: platinum-supported carbon nanotube >platinum-supported graphene >platinum-supported activated carbon >platinum-supported carbon nanofibre. The kinetic of toluene oxidation has been evaluated as a function of toluene and oxygen partial pressures in different temperatures. Two kinetic models (Power Law and Mars–van Krevelen mechanisms) were applied to the reaction and compared with the experimental data. Mars–van Krevelen model is more appropriate than the Power Law model for this reaction as Mars–van Krevelen model showed better prediction of the behaviour of the reaction.

中文翻译:

多孔碳质材料负载铂的制备、表征及催化甲苯氧化挥发性有机化合物的性能

通过湿浸渍法制备铂-碳质催化剂并测试甲苯作为挥发性有机化合物的催化氧化。通过X射线衍射、X射线荧光、电感耦合等离子体-发射光谱、傅里叶变换红外、扫描电子显微镜和N2吸附-解吸分析来考虑所构建催化剂的结构特性。催化评估表明,铂负载的碳纳米管具有最佳活性 (>99%) 和对 CO2 的高稳定性和选择性 (>99%)。转化率和选择性曲线表明,催化剂去除挥发性有机化合物并将其转化为CO2的性能符合以下递减顺序:铂负载碳纳米管> 铂负载石墨烯>铂负载活性炭>铂负载碳纳米纤维。甲苯氧化的动力学已被评估为不同温度下甲苯和氧分压的函数。将两种动力学模型(幂律和 Mars-van Krevelen 机制)应用于反应并与实验数据进行比较。Mars-van Krevelen 模型比幂律模型更适合这种反应,因为 Mars-van Krevelen 模型显示了对反应行为的更好预测。将两种动力学模型(幂律和 Mars-van Krevelen 机制)应用于反应并与实验数据进行比较。Mars-van Krevelen 模型比幂律模型更适合这种反应,因为 Mars-van Krevelen 模型显示了对反应行为的更好预测。将两种动力学模型(幂律和 Mars-van Krevelen 机制)应用于反应并与实验数据进行比较。Mars-van Krevelen 模型比幂律模型更适合这种反应,因为 Mars-van Krevelen 模型显示了对反应行为的更好预测。
更新日期:2019-11-29
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