Optimization of process parameters for lipase-catalyzed synthesis of esteramines-based esterquats using wavelet neural network (WNN) in 2-liter bioreactor Hamid Reza Fard Masoumi a, *, Mahiran Basri a, *, Anuar Kassim a , Dzulkefly Kuang Abdullah a , Yadollah Abdollahi b , Siti Salwa Abd Gani a , Malahat Rezaee c a Department of Chemistry, Faculty of Science, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia b Material Synthesis and Characterization Laboratory, Institute of Advanced Technology, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia c Malaysia Institute of Bioscience, Universiti Putra Malaysia, 43400 Serdang, Selangor, Malaysia 1. Introduction Esteramines-based esterquats are potential high-value pro- ducts utilized as surfactants and softening agents. They are remarkably biodegradable and biocompatible due to the fact, their ester bonds are easily hydrolyzed [1–3]. Chemical synthesis is the typical means to esterify triethano- lamine and fatty acids. However, such a kind of synthesis normally needs high temperature, high pressure as well as corrosion- resistant equipment which often result in unwanted by-products. Preparation of the fatty acid substrates, for example, produces quite a few impurities giving a dark-colored product. Following downstream operations such as bleaching and distillation are required to attain purer and lighter-colored products [4]. Since conventionally chemical synthesis has the shortcomings discussed above, researchers have been looking at alternative methods. Enzymatic preparation of fatty esters has drawn great interest for the past twenty years. Because of the bio-catalytic selectivity of enzymes, final products consist of much less isomers and side-products [5]. Moreover, the reaction conditions of an enzymatic synthesis are significantly mild by comparison with the conventional means. Thus, reactor design is rather simple. Also industries drive to reduce the expenses on operation and devices and to improve safety in the work area [6]. In this study, triethanolamine (TEA) and oleic acid (OA) were selected as substrates to design an optimum model reaction which will lead to high conversion rate utilizing lipase from Candida antarctica (Novozym 435) as a biocatalyst in the organic solvent system. All process parameters are selected to perform the optimization by using wavelet neural network (WNN). Therefore, this work aims to locate the optimum reaction conditions for lipase-catalyzed synthesis of esteramines-based esterquats through Response Surface Methodology (RSM) as an experimental design [7–9] and WNN as a statistical tool for optimization. Five independent process variables, including enzyme amount, reaction time, reaction temperature, substrates molar ratio of OA to TEA and agitation speed were studied under the given conditions designed by Design Expert software. 2. Material and methods 2.1. Materials Novozym 435, C. antarctica lipase B immobilized on a macroporous acrylic resin (10,000 propyl laurate units per gram), Journal of Industrial and Engineering Chemistry 20 (2014) 1973–1976 A R T I C L E I N F O Article history: Received 14 June 2013 Accepted 14 September 2013 Available online 21 September 2013 Keywords: Wavelet neural network (WNN) Optimization process parameters Esterquat Enzymatic reaction Lipase-catalyzed synthesis A B S T R A C T 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. ß 2013 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved. * Corresponding authors. Tel.: +60 17 244 0 298; fax: +60 3 8943 2508. E-mail addresses: fardmasoumi@upm.edu.my (H.R. Fard Masoumi), mahiran@upm.edu.my (M. Basri). Contents lists available at ScienceDirect Journal of Industrial and Engineering Chemistry jou r n al h o mep ag e: w ww .elsevier .co m /loc ate/jiec 1226-086X/$ – see front matter ß 2013 The Korean Society of Industrial and Engineering Chemistry. Published by Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.jiec.2013.09.019