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Abstract
para-Xylene is widely used in chemical industry. It can be synthesized by alkylation of toluene with methanol using zeolite ZSM-5 as catalyst. The proportion of para-xylene, among its other isomers and other reaction byproducts, depends on the reaction conditions. As this process still remains largely empirical, we attempted to build a theoretical model able to predict the para-xylene yield under specific reaction conditions. We have consequently collected data regarding this reaction from the literature and exploited the potency of a particular artificial neural network (ANN), the counter-propagation ANN based on the Kohonen technique. The results show that such an approach is suitable to establish a predictive model of the yield in para-xylene on the basis of reaction parameters. The quality of the model could be further improved by considering a larger valuable data set, e.g. including experiments characterized by a low yield in para-xylene.
Original language | English |
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Pages (from-to) | 557-572 |
Number of pages | 16 |
Journal | Computers and Chemistry |
Volume | 26 |
Issue number | 6 |
DOIs | |
Publication status | Published - 1 Nov 2002 |
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Dive into the research topics of 'Application of a Kohonen Neural Network to the Analysis of Data Regarding the Alkylation of Toluene with Methanol Catalyzed by ZSM-5 Type Zeolites'. Together they form a unique fingerprint.Projects
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High Performance Computing Technology Platform
Benoît Champagne (Manager)
Technological Platform High Performance ComputingFacility/equipment: Technological Platform