Optimisation of olefin epoxidation catalysts with the application of high-throughput and genetic algorithms assisted by artificial neural networks (softcomputing techniques)

被引:74
作者
Corma, A
Serra, JM
Serna, P
Valero, S
Argente, E
Botti, V
机构
[1] Univ Politecn Valencia, Inst Tecnol Quim, E-46022 Valencia, Spain
[2] Univ Politecn Valencia, Dept Sistemas Informat & Computac, E-46022 Valencia, Spain
关键词
genetic algorithm; neural networks; high-throughput; epoxidation; titanium; MCM-41; MCM-48;
D O I
10.1016/j.jcat.2004.11.024
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
An olefin epoxidation Ti catalyst has been optimised by means of high-throughput experimentation involving materials synthesis, postsynthesis treatments, and catalytic testing. Softcomputing techniques for advanced experimental design have been used. The variables explored in the hydrothermal synthesis of Ti-silicate-based catalysts were: concentration of OH-, titanium, and surfactant. The probe reaction employed for the optimisation was the solvent-free epoxidation of cyclohexene, with tert-butylhydroperoxide as oxidant. The different catalyst groups detected by clustering analysis were studied by XRD and UV diffuse reflectance. Ti-mesoporous MCM-41 and MCM-48 molecular sieves were among the most active catalysts. The best performing catalysts were tested for epoxidation of different linear olefins. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:513 / 524
页数:12
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