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The Friedel-Crafts reactions are very important reactions which are widely used in the production of fine chemicals, intermediates, and petrochemicals. Typical catalysts for the Friedel-Crafts reactions are available in the liquid phase. The usage of over-stoichiometric amounts of these acids generates several problems such as corrosion, separation, and waste disposal. Therefore, to develop environmentally benign processes, active and green solid acid catalysts are required. Ionexchanged clays1),2) are highly efficient catalysts and zeolites show unique shape selectivity in spite of the low activity imposed by the diffusivity limit. Among the H-type zeolites, β zeolite has properties as an anticoking catalyst3). Other mesoporous materials such as SBA-14) and transition metal oxides are other known types of catalysts5),6). The high-throughput screening (HTS) approach is useful to estimate the catalytic properties of new materials. We previously developed the HTS method using test tubes and a dry bath to optimize the catalyst composition of oxides for benzylation of anisole by benzyl alcohol7),8). The ohmic heating was then replaced by rapid microwave heating to accelerate the screening, which showed that Fe or Sn containing montmorillonite have high activity9). Then the development of successive catalyst screening revealed that phosphotungstate (HPA) shows higher activity. In the present study, we describe the screening of support and additives for HPA catalyst for benzylation of anisole by benzyl alcohol using the HTS method with test tubes and data mining tools. Catalytic phenomena are generally very complicated because many non-linear parameters are involved. Therefore, the catalytic activity or selectivity of a new catalyst is quite difficult to predict based on previous experimental results. We have been using RBFN10)~17) to investigate the relationship between the activity and physicochemical properties of elements which are used as additives to catalysts. These properties should affect the catalytic properties such as surface area, metal dispersion, electronic state, morphology, thermal stability, affinity to supports, and others, and these catalytic properties then determine the catalytic activities. Therefore, the properties of elements should be correlated to the catalytic performance, although through quite complicated non-linear relationships. Catalysts were prepared using elements with known properties, and the parameters of a RBFN were tuned using the physicochemical properties and the catalytic performance. The tuning process is usually called “training” because of the association with the learning process of the human brain. The important point is that the variety of training elements are selected according to the orthogonal concept. For example, all elements can be clustered by the k-means clustering method, and some elements can be selected as the representative of each 114 Journal of the Japan Petroleum Institute, 54, (2), 114-118 (2011)

Screening of Supports and Additives for Heteropoly Acid Catalysts for Friedel-Crafts Reaction by High-throughput Screening and Data Mining