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

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Abstract

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. © 2013 The Korean Society of Industrial and Engineering Chemistry.

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Fard Masoumi, H. R., Basri, M., Kassim, A., Abdullah, D. K., Abdollahi, Y., Gani, S. S. A., & Rezaee, M. (2014). Optimization of process parameters for lipase-catalyzed synthesis of esteramines-based esterquats using wavelet neural network (WNN) in 2-liter bioreactor. Journal of Industrial and Engineering Chemistry, 20(4), 1973–1976. https://doi.org/10.1016/j.jiec.2013.09.019

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