6784

6326

كارشناسي ارشد

مهندسي شيمي

اصفهان: دانشگاه صنعتي اصفهان، دانشكده مهندسي شيمي

1390

پانزده، 136ص.: مصور، جدول، نمودار

ص.ع.به فارسي و انگليسي

محمد قريشي، علي اكبر دادخواه

مهدي پورمدني

5/4/91

مسعود حق شناس فرد، مهدي كديور

1396/09/14

كتابنامه

مهندسي شيمي

مهندسي شيمي

ID6326

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

Experimental Investigation Modeling and Optimization of Operating Conditions of Supercritical Extraction of EGCG from Green Tea Elham Heidari E heidari@ce iut ac ir Date of submission 28 February 2012 Department of Chemical Engineering Isfahan University of Technology Isfahan 84156 83111 IranDegree M Sc Language FarsiSupervisor Prof Seyyed Mohammad Ghoreishi ghoreshi@cc iut ac irSupervisor Assist Prof Ali Akbar Dadkhah dadkhah@cc iut ac irAbstractRecently scientists have proven the green tea therapeutic effects on various diseases such as breast colon duodenal rectal and pancreas cancer hypertension diabetes Alzheimer s etc by extensive researches Tea iscomposed of various compounds Most of its antioxidant effects are often attributed to epigallocatechingallet EGCG Therefore necessity of EGCG extraction and producing extract of antioxidant is obvious In this study the extraction of EGCG from green tea was investigated by modified supercritical CO2 and Soxhlet extractionwith constant volume of co solvent 1 ml 25 min of static time and 0 674 mm of average particle size Designof experiment carried out with response surface methodology RSM using Mini Tab software The operatingtemperature 40 60 by step 5 C the operating pressure 10 30 by step 5 Mpa the dynamic extraction time 40 120 by step 20min and the flow rate of CO2 0 5 1 7 by step 0 3 ml min have been considered as operatingvariables Response surface analysis verified that the data were adequately fitted to second order polynomialmodel The linear and quadratics terms of temperature pressure CO2 flow rate and dynamic time as well as theinteraction between pressure temperature and dynamic time temperature had significant effects on the proposedmodel of EGCG recovery based on coded variables R2 and modified R2 of the model are 98 40 and 96 99 respectively It was predicted that the optimum extraction conditions within the experimental ranges would bethe extraction pressure of 19 29 MPa temperature of 43 7 $ C flow rate of 1 5 ml min and extraction time of106 min with recovery of 0 462 Moreover in the present study a mathematical modeling for EGCG extractionfrom green tea was performed by modified supercritical carbon dioxide based on the differential mass balance Density and viscosity of dense gases mixture was obtained by Peng Robinsson PR equation of state with thevan der Waals mixing rules and Chung et al respectively Mathematical model parameters are includingeffective pore diffusivity film mass transfer coefficient axial dispersion and distribution coefficient The firstthree parameters were obtained from empirical equations and the distribution coefficient between solid andsolvent has been determined by thermodynamic modeling of solubilities Indicated by obtained results themathematical model is able to predict the experimental data with acceptable accuracy and R2 is 98 The mainprocess conditions which must be determined to maximize the extraction recovery are temperature pressure flow rate of CO2 and dynamic extraction time These were optimized by genetic algorithm The optimaloperating conditions were observed at 41 2 C 19 79 MPa 1 7 ml min and 116 3 min dynamic time toachieve 0 447 recovery There was good agreement between two methods of optimization genetic and RSM Finally neural network modeling was done by three hidden layers with 16 10 and 8 neuron respectively Theresults showed the truly trained network and very good compatibility between the neural networks andexperimental data for EGCG recovery Key WordsEpigallocatechingallet Supercritical extraction Co solvent Response surface methodology Mathematical modeling Genetic algorithm Neural network

محمد قريشي، علي اكبر دادخواه

مهدي پورمدني

مسعود حق شناس فرد، مهدي كديور