甲苯与戊二烯催化合成戊烯基甲苯反应过程的建模及优化

Modeling and optimizing of catalytic reaction for synthesizing pentenyltoluene from toluene with pentadiene

戊烯基甲苯可以由甲苯与戊二烯通过催化合成反应制得,是制备2,6-二甲基萘的重要原料。本文首先利用Matlab 语言对此催化合成反应建立了人工神经网络模型,根据此模型可预测反应条件改变时实验结果;接着利用遗传算法对此模型进行优化,得到优化的反应条件组合;最后在此优化条件组合下进行实验验证。当原料配比4.39,催化剂配比4.43mol%,反应温度82℃,反应时间2.6hr 时,目标产物收率实验值29.87%与优化结果33.93%比较接近。

Pentenyltoluene is an important raw material for preparing 2,6-dimethylnaphalene,which can be synthesized from toluenewith pentadiene on appropriate catalyst.In this paper,first,the catalytic reaetian model of pentenyltoluene has been set up by artificialneural network in Matlab language,which can predict the experiment result when the reaction conditions change.And then,the geneticagorithm has been applied to the catalytic reaction model,so that the best reaction conditions can be obtained.Finally,the best reac-tion conditions have been examined by experiment.On the best reaction conditions that the raw material ratio is 4.39,the catalyst ratiois 4.43 mol%,temperature is 82℃,reaction time is 2.6 hr,the yield of pentenyltoluene is 29.87% which is close to the optimizationvalue 33.93%.