首页> 外文期刊>Journal of Analytical & Applied Pyrolysis >Comparing the catalytic performances of mixed molybdenum with cerium and lanthanide oxides supported on HZSM-5 by multiobjective optimization of catalyst compositions using nondominated sorting genetic algorithm
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Comparing the catalytic performances of mixed molybdenum with cerium and lanthanide oxides supported on HZSM-5 by multiobjective optimization of catalyst compositions using nondominated sorting genetic algorithm

机译:通过非支配排序遗传算法多目标优化催化剂组合物,比较HZSM-5负载钼与铈和镧系元素氧化物的催化性能

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Mixed oxides, La_2O_3-MoO_3 and CeO_2-MoO_3, were being used as catalysts for thermal catalytic cracking of naphtha. Effect of catalyst compositions on the yield of light olefins (ethylene and propylene) were systematically examined using central composite design (CCD) coupled with the response surface methodology. Two empirical models for each system, based on these preparation variables for the yields of ethylene and propylene were constructed in two CCD studies. These models, shown as contour diagrams, indicated that the yields of ethylene and propylene gradually increased up to a certain amount of loadings. In fact, the yield of light olefins has been decreased by the high loadings of rare earth elements (La and Ce) and molybdenum. In order to compare the catalytic performance of these two systems, a multiobjective optimization (MOO) for simultaneous maximization of ethylene and propylene was carried out by the elitist nondominated sorting optimization algorithm or NSGA-II. This algorithm resulted in Pareto-optimal solutions and an additional criterion was proposed over the solutions to obtain a final unique optimal solution. It was found that the supported CeO_2-MoO_3 increased the yield of light olefins slightly more than supported La_2O_3-MoO_3 at the optimum point.
机译:混合氧化物La_2O_3-MoO_3和CeO_2-MoO_3被用作石脑油热催化裂化的催化剂。使用中心复合设计(CCD)结合响应表面方法系统地检查了催化剂组成对轻质烯烃(乙烯和丙烯)收率的影响。在两次CCD研究中,基于这些乙烯和丙烯收率的制备变量,为每个系统建立了两个经验模型。这些模型显示为等高线图,表明乙烯和丙烯的收率逐渐增加到一定的负载量。实际上,由于高含量的稀土元素(镧和铈)和钼,轻质烯烃的产率已经降低。为了比较这两个系统的催化性能,通过精英非支配排序优化算法或NSGA-II进行了乙烯和丙烯同时最大化的多目标优化(MOO)。该算法产生了帕累托最优解,并在该解上提出了附加准则,以获得最终唯一的最优解。发现在最佳点,负载的CeO_2-MoO_3增加的轻烯烃产率略高于负载的La_2O_3-MoO_3。

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