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Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network


Citation

Langroodi, Naz Chaibakhsh (2010) Modeling And Optimization Of Lipase-Catalyzed Synthesis Of Adipate Esters Using Response Surface Methodology And Artificial Neural Network. PhD thesis, Universiti Putra Malaysia.

Abstract

Optimized Novozym 435 (Candida antarctica lipase B immobilized on acrylic resin)- catalyzed esterification of adipic acid and various monohydric alcohols was successfully performed. Solvent-based synthesis of adipate esters was carried out in small scale reaction using 30 mL screw-capped vials. The synthetic reaction was optimized by Response Surface Methodology (RSM) based on central composite rotatable design (CCRD) to evaluate the interactive effects of reaction parameters including temperature, time, enzyme amount and alcohol/acid molar ratio. A high percentage yield (>96.0%) using optimum conditions was obtained using a minimum amount of enzyme, which matched well with the predicted values. Artificial Neural Network (ANN) approach was also employed for the estimation of esterification yield in enzymatic synthesis of adipate esters. Various feedforward neural networks were performed using different learning algorithms. The best algorithm was found to be Levenberg–Marquardt (LM) for a network composed of seven hidden nodes with hyperbolic tangent sigmoid transfer function. ANN showed better prediction ability compared to RSM. A high coefficient of determination (R2) (>0.9) and a low mean absolute error (MAE) and root mean squared error (RMSE) for training, validating and testing data implied the good generalization of the developed models for predicting the reaction yield. In order to develop an efficient enzyme catalyzed process, alcohol specificity of enzyme in terms of chain length and structure in the synthesis of adipate esters was determined. Methanol, n-butanol, octanol, dodecanol, octadecanol, isobutanol, sec-butanol and tertbutanol were the alcohols used for this study. The results demonstrated that alcohol chain length and structure were determining factors that affect the optimum condition of the reaction parameters for the enzymatic synthesis of adipate esters. Minimum reaction time for achieving maximum ester yield was obtained for isobutanol. The initial rates of synthesis of adipate esters for primary and secondary alcohols were nearly the same. Kinetic study of the lipase-catalyzed adipate ester synthesis in solvent-based system was carried out as a preliminary step for future industrial scale bioreactor design. The reaction was found to obey the ping-pong bi-bi mechanism with alcohol inhibition. The coefficient of determination (R2) and MAE values between the simulated and experimental initial rates were determined as 0.9904 and 2.4×10-4 which shows a good quality of fit between the simulated and experimental values.In order to make the synthesis process more environmentally friendly and improve the productivity of the reactor to the highest amount, the reaction was performed in a solvent-free system using 0.5-L batch and 4-L continuous stirred tank reactors. Due to low solubility of the substrate and high viscosity of the reaction mixture, a continuous stirred tank reactor was used for continuous production of the ester. A high percentage conversion was achieved (about 96%) using minimum amount of enzyme (2.5%w/w) indicating the high efficiency of solvent free-system for synthesis of adipate ester. Continuous production of adipate ester was successfully performed with an average yield of 92.7% and high operation stability of enzyme for 28 hours, which is indicative of performing a successful process for the ester synthesis.


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Additional Metadata

Item Type: Thesis (PhD)
Subject: Neural networks
Subject: Surfaces (Physics) - Analysis
Subject: Esters
Call Number: FS 2010 22
Chairman Supervisor: Professor Mohd Basyaruddin Abdul Rahman, PhD
Divisions: Faculty of Science
Depositing User: Mohd Nezeri Mohamad
Date Deposited: 11 Jul 2011 08:52
Last Modified: 27 May 2013 07:52
URI: http://psasir.upm.edu.my/id/eprint/12437
Statistic Details: View Download Statistic

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