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Optimization of process parameters for lipase-catalyzed synthesis of esteramines-based esterquats using wavelet neural network (WNN) in 2-liter bioreactor

机译:利用小波神经网络(WNN)在2升生物反应器中脂肪酶催化合成基于酯胺的酯季铵盐的工艺参数的优化

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摘要

A wavelet neural network (WNN) based on the genetic algorithm (GA) was used in conjunction with an experimental design to optimize the enzymatic reaction conditions for the preparation of esteramines-based esterquats. A set of experiments was designed by central composite design to process modeling and statistically evaluate the findings. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio and agitation speed were studied under the given conditions designed by Design Expert software. All these show that the WNN has great potential ability in prediction of reaction conversion in lipase-catalyzed synthesis of products.
机译:基于遗传算法(GA)的小波神经网络(WNN)与实验设计结合使用,以优化用于制备基于酯胺的酯季铵盐的酶促反应条件。通过中央复合设计设计了一组实验,以进行建模并统计评估结果。在Design Expert软件设计的给定条件下,研究了五个独立的工艺变量,包括酶量,反应时间,反应温度,底物摩尔比和搅拌速度。所有这些表明,WNN在脂肪酶催化的产物合成中具有预测反应转化的巨大潜力。

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