Optimal operation of simulated moving bed and varicol processes for bio separation

OPTIMAL OPERATION OF SIMULATED MOVING BED AND VARICOL PROCESSES FOR BIO-SEPARATION FALDY WONGSO NATIONAL UNIVERSITY OF SINGAPORE 2003 OPTIMAL OPERATION OF SIMULATED MOVING BED AND VARICOL PROCESSES FOR BIO-SEPARATION FALDY WONGSO (B Tech., University of Gadjah Mada, Indonesia) A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF CHEMICAL & ENVIRONMENTAL ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2003 To my beloved parents Acknowledgement ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ Acknowledgement I would like to use this opportunity to salute my supervisor Prof Ajay Kumar Ray for allocating his valuable time through incessant guidance, brilliant idea and outstanding patience during my years of candidature in the National University of Singapore It is right to express my deepest gratefulness for everything we have done together I acknowledge the boundless thought and interest of Prof Hidajat throughout my study and also for sourcing the interesting chiral compounds as the scope of this work I would also like to thank Prof Andrezj Krasalawski (Lappeenranta University of Technology, Finland) for his sober assistance and advice prior and during the ESCAPE13 symposium, Prof Iftekhar Abubakar Karimi and Prof Gade Pandu Rangaiah for the implied trust in my appointment as graduate tutor My special thanks to Prof Santosh Kumar Gupta for the NSGA jumping genes algorithm which is a superb tool in carrying out our work It is a great honor to have Prof Lakshminarayanan Samavedham’s resourceful presence and input at my PG seminar Thanks are also due to Prof Marc Garland for the fruitful feedback on this thesis I want to express my gratitude to Mr Boey and Mr Mao Ning for the access to the workstation and Mr Toh for the Microsoft Visual Fortran software, Mr Chun See Chong for his assistance during my PG seminar, Mr Yeo Eng Hee and Mr Zhang Xinhuai from the SVU team for their excellent support in the execution of my simulation program I always appreciate the National University of Singapore for the Research Scholarship which made this work possible I will not forget the sincerity of my senior, Dr Effendi Widjaja who has encouraged me to pursue my master degree in NUS I’m thankful to Dr Zhang Ziyang for his cooperative assistance and comment in all my doubts Million thanks to all my labmates and friends: Yu Weifang, Kanheya Mehrotra, Hari Prasad Janakiram Subramani, Chen Saoping, Kurup Anjushri Sreedhar, Eng Yongyong, Zhang Yan, Naveen Agrawal, Lee Yen Mei, and Paritam Kumar Dutta for the advices, jokes and time we spent together I also thank my flatmate, Handoko for sharing his experience on Microsoft Visual Basic program Foremost, my deepest gratitude goes to my beloved parents and all family members whose understanding, support and love have always inspired me this time round i Table of Contents ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ Table of Contents Acknowledgments…………………………………………………………………………i Table of Contents……………………………………………………………………… ii Summary… ……………………………………………………………………………viii Nomenclature…………………………………………………………………………… x List of Figures………………………………………………………………………… xiii List of Tables………………………………………………………………… ………xvii Introduction………………………………………….……………………………1 Literature Review……………………………………………………………… 2.1.Review on Stereochemistry……………………………………………………7 2.1.1 An Overview on Chirality… ……… ………………………… 2.1.2 Trends in Chiral Chemistry…………………………………… 10 2.1.2.1 Trends in Pharmaceutical Industry………………………11 2.1.2.2 Trends in Fine Chemical Industry……………………….15 2.2.Chromatographic Separation…………………………………………………21 2.2.1 Elution Chromatography…………………………………………21 2.2.2 Continuous Crosscurrent Chromatography………………………24 2.2.3 Continuous Countercurrent Chromatography……………… …27 2.2.3.1 True Moving Bed Chromatography……………… … 28 2.2.3.2 Simulated Moving Bed Chromatography….……………32 ii Table of Contents ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 2.3.Application of SMB Technology……………………………….…………….35 2.3.1 Petrochemical Industry…………………………….…………… 36 2.3.2 Food and Flavor Industry……………………………………… 38 2.3.3 Pharmaceutical and Fine Chemical Industry….………………….41 2.3.4 Protein Separation……………………………………….……… 45 2.4.Optimization of Simulated Moving Bed.……………….…………………….47 2.4.1 Optimization Algorithm………………………………….……… 48 2.4.2 Optimization Work on SMB…………………………….……… 50 2.4.2.1 Single Objective Optimization…….……………….…….51 2.4.2.2 Multi Objective Optimization……….……….………… 55 2.5.Update on Moving Bed Technology…………………….……….………… 55 2.5.1 Reactive SMB………………………………….…….…… …….56 2.5.2 Ternary and Pseudo-SMB……………………….….…………….58 2.5.3 Supercritical Fluid-SMB Chromatography……… …………… 62 2.5.4 Varicol Process…………………………………… …………….66 2.5.5 SMB Process Control…………………………………….…… 69 Simulated Moving Bed and Varicol Process……………………………………… 72 3.1 Schematic Diagram of SMB and Varicol Process………………………… 72 Optimal Operation of Moving Bed Process for Chiral Drug Separation…………77 4.1 Background of Enantio-Separation ………………………………………….77 4.2 Numerical Simulation of SMB and Varicol Process…………… ………….79 iii Table of Contents ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 4.3 Calculation of Theoretical Number of Plate…………………………………82 4.4 Model Validation…………………………………………………………….85 4.5 Sensitivity Study…………………………………………………………… 88 4.5.1 The Effect of Switching Time…………………………………… 88 4.5.2 The Effect of Feed Flow Rate…… ……………………………….91 4.5.3 The Effect of Raffinate Flow Rate…………………………………92 4.5.4 The Effect of Desorbent Flow Rate………… ……………………94 4.6 Single Objective Optimization……………………………………… …….96 4.6.1 Case Single Objective Optimization: Maximization of throughput 97 4.6.2 Case Single Objective Optimization: Minimization of desorbent consumption …………………………………………………… 100 4.7 Multi-Objectives Optimization…………………………………………… 105 4.7.1 Case Two Objectives Optimization: Maximization of raffinate and extract productivity……………………………… … ……… 107 4.7.2 Case Two Objectives Optimization: Maximization of raffinate purity and productivity… 109 4.7.3 Case Two Objectives Optimization: Maximization of extract purity and productivity…… ….…………… ………………………112 4.7.4 Case Two Objectives Optimization: Maximization of throughput and minimization of desorbent consumption………….…… …115 4.7.5 Case Three Objectives Optimization: Maximization of raffinate and extract productivity and minimization of solid requirement 118 iv Table of Contents ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 4.7.6 Case Three Objectives Optimization: Maximization of raffinate and extract productivity and minimization of desorbent consumption……………………………………… ……………….…… 120 4.8 Pure Separation Regime for Binary Separation… ……………………… 122 4.9 The Effect of Sub-interval and Partial Feed Operation… 127 Optimization Study of Continuous Chromatographic Separation of a Chiral Intermediate………………………………………………………………………….134 5.1 The Application of 1,1’-bi-2-naphtol……………………………….………134 5.2 Mathematical Model of SMB and Varicol Process ………………………137 5.3 Model Validation………………………………………………………… 141 5.4 Sensitivity Analysis ………………………………………………………145 5.4.1 The Effect of Switching Time……………………………………146 5.4.2 The Effect of Feed Flow Rate……………………… …….……147 5.4.3 The Effect of Raffinate Flow Rate………………………….…….148 5.4.4 The Effect of Desorbent Flow Rate………………………………149 5.4.5 The Effect of Column Number……………………………….… 150 5.5 Optimization Study………….……………………………………… ……153 5.5.1 Single Objective Optimization……………………………………154 5.5.1.1 Case Single Objective Optimization: Maximize feed flow rate….…………………….………………………… …154 5.5.1.2 Case Single Objective Optimization: Minimize desorbent flow rate.………………….……………….…………….156 v Table of Contents ¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯¯ 5.5.2 Multi Objective Optimization…………………………………….158 5.5.2.1 Case Multi Objective Optimization: Maximize raffinate and extract purity……………………………………… 160 5.5.2.2 Case Multi Objective Optimization: Maximize raffinate and extract productivity…………………………………163 5.5.2.3 Case Multi Objective Optimization: Maximize raffinate purity and productivity………………………………….165 5.5.2.4 Case Multi Objective Optimization: Maximize extract purity and productivity…… ………………………………168 5.5.2.5 Case Multi Objective Optimization: Maximize feed and minimize desorbent rate………………………………….170 5.5.2.6 Case Multi Objective Optimization: Maximize raffinate and extract productivity and minimize desorbent rate… 173 5.5.2.7 Case Multi Objective Optimization: Maximize raffinate and extract productivity and minimize column length… 175 5.6 Complete Separation Region……………………………………………….177 5.7 The Effect of Flow Rate in Zone (Q1) on Countercurrent Separation……181 Conclusion and Recommendation…………………….……………………………185 6.1 Optimal Operation of SMB and Varicol Processes for Chiral Drug Separation …………………………………………………………………………… 185 6.2 Optimization Study of Continuous Chromatographic Separation of a Chiral Intermediate in SMB and Varicol System………………………………….187 vi for component B  t (φ )  dC B( N,k) 1 − ε   t (φ )  dq B( N,k) C B( N,k)−1 = C B( N,k) +  +     ε   J  dt  J  dt ……….(A.4) and q B ,k = H B C B ,k + NK B C B ,k + K A C A, k + K B C B , k ……….(A.5) Then taking the derivative of eq.(A.5), dq B( N,k) dt = HB dC B( N,k) dt + NK B   dC B( N,k) dC A( N,k)    + KA  −  K B  dt dt    (N ) dt + NK C B B ,k  (N) (N ) (N )  + K B C B ,k )  (1 + K A C A,k + K B C B ,k )      dC B( N,k) (1 + K A C A( N,k) ……….(A.6) Substituting this derivative to eq.(A.4),  J  (N)  dC B( N,k) 1 − ε    dC A( N,k) dC B( N,k) 1 − ε   NK B C B( N,k) K B NK B C B( N,k) K A NK B (N ) + − −   C B ,k −1 − C B ,k = H B +   (N) (N )  dt (1 + K A C A( N,k) + K B C B( N,k) ) (1 + K A C A( N,k) + K B C B( N,k) )  dt  ε    ε   (1 + K A C A,k + K B C B ,k )  dt  t 0(φ )  [ ] ……….(A.7) 214 Rearranging, dC B( N,k) dt  J  (N )  dC A( N,k) NK B C B( N,k) K A 1 − ε   (N ) C C − +   B ,k −1 B ,k  ε   (1 + K C ( N ) + K C ( N ) )  dt    t 0(φ )  A A, k B B ,k =  1− ε  NK B (1 + K A C A( N,k) )  1− ε  H + +   B    (N ) (N)   ε  (1 + K A C A,k + K B C B ,k )    ε  [ ] ……….(A.8) Similarly for component A, we first take the derivative of eq.(A.3) as follows: dq A( N,k) dt = HA dC A( N,k) dt + NK A   dC B( N,k) dC A( N,k)     + KA −  KB  dt dt  (N )   dt + NK C A A, k  (N) (N ) (N )  + K B C B ,k ) (1 + K A C A,k + K B C B ,k )       dC A( N,k) (1 + K A C A( N,k) ……….(A.9) Substituting this derivative to eq.(A.2), we obtain  J  ( N) dCA(N,k) ( N)   CA,k −1 −CA,k = dt t0(φ)  [ ]  dCA(N,k) NKACA(N,k) KA NKA 1−ε  + H A + (1+ K C(N) + K C(N) ) − (1+ K C(N) + K C(N) )2  dt  ε   A A,k B B,k A A,k B B,k  dCB(N,k) NKACA(N,k) KB 1−ε  − ( N) ( N)    ε (1+ KACA,k + KBCB,k )  dt ……….(A.10) 215 Rearranging, dC A( N,k) dt  J  − ε   1 + ε  t (φ )       (N ) NK B (1 + K A C A( N,k) )  ( N ) NK A C A( N,k) K B HB +  C A,k −1 − C A( N,k) +  J   C B ,k −1 − C B( N,k) (N) (N)  (N) (N )   (1 + K A C A,k + K B C B ,k )    t 0(φ )   (1 + K A C A,k + K B C B ,k )  =  1− ε    NK A (1 + K B C B( N,k) )   − ε  NK B (1 + K A C A( N,k) )   NK A C A( N,k) K B NK B C B( N,k) K A HA +  1 + HB +  −  1 +    ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) N N N N N N N N ε  ε  (1 + K A C A,k + K B C B ,k )   (1 + K A C A,k + K B C B ,k )   (1 + K A C A,k + K B C B ,k )   (1 + K A C A,k + K B C B ,k )   [ ] [ ] ……….(A.11) Boundary Condition, At the eluent port, C (N ) i , first = N) (Q1 − QE )Ci(,last Q1 ……….(A.12) At the feed port, ) C i(,Nfirst = Q2 C i(,Nlast) + QF C i(,NF ) Q3 ……….(A.13) Else, ) N) C i(,Nfirst = C i(,last ……….(A.14) 216 APPENDIX B Calculation of CSP usage & void fraction in SB-553261 separation Table B.1 Experimental Data on Productivity and Desorbent Consumption Productivity (kgprod/kgCSP/day) 0.604 6-column SMB 1/2/2/1 6-column VARICOL 0.664 /// 5-column VARICOL 0.725 /// 4-column VARICOL 0.906 //