Continuous Preferential Crystallization in Two Coupled Crystallizers



Similar documents
ME6130 An introduction to CFD 1-1

Interactive simulation of an ash cloud of the volcano Grímsvötn

Express Introductory Training in ANSYS Fluent Lecture 1 Introduction to the CFD Methodology

Lecture 3 Fluid Dynamics and Balance Equa6ons for Reac6ng Flows

Dynamic Process Modeling. Process Dynamics and Control

Customer Training Material. Lecture 2. Introduction to. Methodology ANSYS FLUENT. ANSYS, Inc. Proprietary 2010 ANSYS, Inc. All rights reserved.

CFD SIMULATION OF SDHW STORAGE TANK WITH AND WITHOUT HEATER

Determination of the heat storage capacity of PCM and PCM objects as a function of temperature

Introduction to CFD Analysis

A systematic approach to optimization of industrial lactose crystallization. University of Wisconsin, Madison 1605 Linden Drive Madison, WI 53706

Computational Fluid Dynamics (CFD) and Multiphase Flow Modelling. Associate Professor Britt M. Halvorsen (Dr. Ing) Amaranath S.

Fluid Dynamic Optimization of Flat Sheet Membrane Modules Movement of Bubbles in Vertical Channels

Chapter 12 IVP Practice Problems

Heat Transfer and Energy

Chapter 28 Fluid Dynamics

Coupling Forced Convection in Air Gaps with Heat and Moisture Transfer inside Constructions

Introduction to CFD Analysis

Phosphate Recovery from Municipal Wastewater through Crystallization of Calcium Phosphate

Differential Balance Equations (DBE)

Effect of Aspect Ratio on Laminar Natural Convection in Partially Heated Enclosure

CFD Model of a Spinning Disk Reactor for Nanoparticle Production

Figure 1 - Unsteady-State Heat Conduction in a One-dimensional Slab

Numerical Model for the Study of the Velocity Dependence Of the Ionisation Growth in Gas Discharge Plasma

Simulation and Nonlinear Analysis of the Stagnant Polymer Layer in a LDPE Tubular Reactor

INTERACTION BETWEEN MOVING VEHICLES AND RAILWAY TRACK AT HIGH SPEED

Lecture 24 - Surface tension, viscous flow, thermodynamics

ADVANCED COMPUTATIONAL TOOLS FOR EDUCATION IN CHEMICAL AND BIOMEDICAL ENGINEERING ANALYSIS

Integration of a fin experiment into the undergraduate heat transfer laboratory

Diffusion and Fluid Flow

Contamination Transport from Wafer to Lens

Differential Relations for Fluid Flow. Acceleration field of a fluid. The differential equation of mass conservation

Ravi Kumar Singh*, K. B. Sahu**, Thakur Debasis Mishra***

Modelling the Drying of Porous Coal Particles in Superheated Steam

RESEARCH PROJECTS. For more information about our research projects please contact us at:

PSTricks. pst-ode. A PSTricks package for solving initial value problems for sets of Ordinary Differential Equations (ODE), v0.7.

CBE 6333, R. Levicky 1 Differential Balance Equations

XI / PHYSICS FLUIDS IN MOTION 11/PA

ACETYLENE AIR DIFFUSION FLAME COMPUTATIONS; COMPARISON OF STATE RELATIONS VERSUS FINITE RATE KINETICS

Statistical Forecasting of High-Way Traffic Jam at a Bottleneck

STEADY STATE MODELING AND SIMULATION OF HYDROCRACKING REACTOR

4. Introduction to Heat & Mass Transfer

FLUID FLOW Introduction General Description

Decaffeination of Raw, Green Coffee Beans Using Supercritical CO 2

Mathematical Modeling and Engineering Problem Solving

Simulation and capacity calculation in real German and European interconnected gas transport systems

The HLLC Riemann Solver

Dr.B.R.AMBEDKAR OPEN UNVERSITY FACULTY OF SCIENCE M.Sc. I year -CHEMISTRY ( ) Course I: Inorganic Chemistry

MODELING, SIMULATION AND DESIGN OF CONTROL CIRCUIT FOR FLEXIBLE ENERGY SYSTEM IN MATLAB&SIMULINK

Collision of a small bubble with a large falling particle

Applications of Organic Solvent Nanofiltration in the Process Development of Active Pharmaceutical Ingredients. Dominic Ormerod

HEAT TRANSFER ANALYSIS IN A 3D SQUARE CHANNEL LAMINAR FLOW WITH USING BAFFLES 1 Vikram Bishnoi

Thème Analytical Chemistry ECUE composant l UE

CHEMICAL ENGINEERING AND CHEMICAL PROCESS TECHNOLOGY - Vol. I - Interphase Mass Transfer - A. Burghardt

TWO-DIMENSIONAL FINITE ELEMENT ANALYSIS OF FORCED CONVECTION FLOW AND HEAT TRANSFER IN A LAMINAR CHANNEL FLOW

A Study on Analysis of Clearwell in Water works by Computational Fluid Dynamics

WJP, PHY381 (2015) Wabash Journal of Physics v4.3, p.1. Cloud Chamber. R.C. Dennis, Tuan Le, M.J. Madsen, and J. Brown

Factors Affecting Precipitation of Calcium Carbonate

Heat Transfer Prof. Dr. Ale Kumar Ghosal Department of Chemical Engineering Indian Institute of Technology, Guwahati

Wind Turbine Power Calculations

Mixing in the process industry: Chemicals Food Pharmaceuticals Paper Polymers Minerals Environmental. Chemical Industry:

Euler-Euler and Euler-Lagrange Modeling of Wood Gasification in Fluidized Beds

Stability of Evaporating Polymer Films. For: Dr. Roger Bonnecaze Surface Phenomena (ChE 385M)

Thermodynamics. Chapter 13 Phase Diagrams. NC State University

Measuring Optical and Thermal Properties of High Temperature Receivers

Model Order Reduction for Linear Convective Thermal Flow

CFD Analysis Of Multi-Phase Flow And Its Measurements

Mobatec in a nutshell

Modelling and Simulation of High Pressure Industrial Autoclave Polyethylene Reactor

A Course in Particle and Crystallization Technology

ME 538: Experiment # 1 Flow measurement and particle generation instruments

Sugar Identification using Polarimetry

Dynamic Models Towards Operator and Engineer Training: Virtual Environment

Properties of a molecule. Absolute configuration, Cahn-Ingold Prelog. Planar, axial, topological chirality and chirality at atoms other than carbon

Application Note. Increasing the activity of monoclonal antibody isoforms by MCSGP. Summary

DIFFUSION IN SOLIDS. Materials often heat treated to improve properties. Atomic diffusion occurs during heat treatment

A LAMINAR FLOW ELEMENT WITH A LINEAR PRESSURE DROP VERSUS VOLUMETRIC FLOW ASME Fluids Engineering Division Summer Meeting

Multiple Optimization Using the JMP Statistical Software Kodak Research Conference May 9, 2005

6 J - vector electric current density (A/m2 )

Kinetics of Phase Transformations: Nucleation & Growth

Chemical Sputtering. von Kohlenstoff durch Wasserstoff. W. Jacob

Drying Parawood with Superheated Steam

Simulation to Analyze Two Models of Agitation System in Quench Process

Monte Carlo Methods in Finance

NUMERICAL ANALYSIS OF THE EFFECTS OF WIND ON BUILDING STRUCTURES

MULTI-POLE MODELING AND INTELLIGENT SIMULATION OF A HYDRAULIC DRIVE WITH THREE-DIRECTIONAL FLOW REGULATING VALVE

GUJARAT TECHNOLOGICAL UNIVERSITY Environmental Science & Technology(35) BE 1st To 8th Semester Exam Scheme & Subject Code

Application Note. Purifying common light-chain bispecific antibodies using MCSGP. Summary

INCORPORATING CFD INTO THE UNDERGRADUATE MECHANICAL ENGINEERING PROGRAMME AT THE UNIVERSITY OF MANITOBA

COMPUTER AIDED NUMERICAL ANALYSIS OF THE CONTINUOUS GRINDING PROCESSES

TWO-PHASE FLOW IN A POROUS MEDIA TEST-CASES PERFORMED WITH TOUGH2

GenOpt (R) Generic Optimization Program User Manual Version 3.0.0β1

AN EFFECT OF GRID QUALITY ON THE RESULTS OF NUMERICAL SIMULATIONS OF THE FLUID FLOW FIELD IN AN AGITATED VESSEL

Transcription:

A publication of 2053 CHEMICAL ENGINEERING TRANSACTIONS VOL. 32, 2013 Chief Editors: Sauro Pierucci, Jiří J. Klemeš Copyright 2013, AIDIC Servizi S.r.l., ISBN 978-88-95608-23-5; ISSN 1974-9791 The Italian Association of Chemical Engineering Online at: www.aidic.it/cet Continuous Preferential Crystallization in Two Coupled Crystallizers Shamsul Qamar a,b, *, Kamila Galan a, Andreas Seidel-Morgenstern a,c a Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany b COMSATS Institute of Information Technology, Park Road Chak Shahzad, Islamabad, Pakistan c Otto von Guericke University Magdeburg, Universitaetsplatz 2, 39106 Magdeburg, Germany shamsul.qamar@comsats.edu.pk This contribution investigates continuous preferential crystallization in two coupled vessels connected via liquid exchange to resolve enantiomers from a racemic mixture. A comparison is drawn between separation in single and two coupled crystallizers. Implementation of periodic and continuous seeding modes is analyzed as well as the influence of exchange flow rate. A high resolution scheme of Koren is applied to solve the models considered. Productivity, purity and mean crystal size are chosen as goal functions to evaluate the product quality and advantages of the coupled process. 1. Introduction Motivation Enantiomeric separation is still a challenging task despite availability of many chiral separation techniques such as enantioselective synthesis, chromatographic methods, enzymatic resolutions, membrane technologies or separation of racemates. The possibility of exhibiting different metabolic effects on a human body either by a pure enantiomer or by a racemic mixture draws attentions of manufactures to the importance of this task. Enantiomers are present in many industrial brunches e.g. pharmaceutical, agrochemical, food, cosmetic. In this contribution continuous preferential crystallization in two coupled crystallizers is investigated. Preferential crystallization and MSMPR Preferential crystallization is successfully applied to conglomerate forming systems where one enantiomer is separated from a racemic mixture of both (reported by Elsner et al., 2005). A representative of this group, L/D-threonine in water whose solubility and kinetics had been studied by Lorenz et al. (2006) and by Sapoundjiev et al. (2006), was chosen for further investigation. The resolution of enantiomers occurs in the metastable zone, where spontaneous, primary nucleation is inhibited kinetically. By inserting seeds of only one enantiomer into the solution, separation driven by the seed surface takes place. In order to conduct preferential crystallization in a continuous manner, a continuous supply of seeds along with racemic feed solution and a continuous removal of the product suspension containing the seeded target enantiomer are required. This is a concept of Mixed-Suspension Mixed-Product Removal (MSMPR) (Randolph and Larson, 1988) which is applied in a single vessel. Modification of this idea could be coupling two MSMPR tanks via liquid phases and thus reducing a counter enantiomer concentration in each tank leading to higher purity. Furthermore liquid phase exchange improves productivity because supersaturation in each vessel is higher. Operating at steady state is a goal of all continuous processes. Time required to reach the steady state may differ due to different kinetics of the model system which change with different process conditions. Finding optimum of the operating parameters may lead to a continuous separation of the target enantiomer at high purity and productivity, and in the coupled case a simultaneous production of both enantiomers in two separated vessels.

2054 2. Mathematical model A population balance model has been established to simulate the dynamic behaviour during continuous preferential crystallization. In each vessel each enantiomer is described by population balance equation (PBM) for the solid phase and by mass balance (MB) in a form of ordinary differential equations (ODE) for the liquid phase. In order to complete the mathematical model algebraic equations for nucleation and crystal growth kinetics together with liquid and sold mass flow rates are implemented. The population balances are given as (c.f. Qamar et al., 2012) F t ( k) ( k) ( G F ) ( k) ( k) seeds out = + F, F,, k { p, c}, { A, B}, x where p stands for preferred enantiomer and c for counter one, while A and B are vessels. The term on the left hand side represents accumulation of crystals of size x. The first term on the right hand side represents convective transport in the direction of the property coordinate x due to size-dependent growth rate. The other terms on the right hand side denote particle number fluxes due to seeding and product removal, respectively. And the initial conditions, based on the assumption that at the beginning the solutions in A and B vessels are crystal free, are given as ( ) { } { } F t = 0, x = 0, k p, c, A, B, whereas primary nucleation generates nuclei of minimum size x min and at the same time the number density function vanishes for crystals of arbitrary size x max (1) (2) B0, () t ( k F (, ), ) t x = xmin = F ( t, x = xmax ) = 0. G (, t x ) 0, min (3) The expressions for nucleation and growth are taken from Mersmann (2001). Each crystallizer is only seeded with preferred enantiomer, thus F seeds, ( x) ( ) ( p ) F = seeds, x for k = p, 0 fork = c. The overall mass of the liquid phase in the system is described by Qamar et al., (2012) (4) dm L, () t ( k) ( k) 2 ( k () () ) ( k) = L, in, L, out, vρs ( ) dt 0 with initial conditions ( ) ( ) m t m t 3 k x G t, x F ( t, x) dx k ( k) ( k) L, L,0, L,0, L,0, L,, { } { } m t = 0 = m = w ρ V k p, c, A, B, where an initial concentration of a racemic solution is included. A high resolution finite volume scheme of Koren is used to solve the model in a length coordinate, while a fourth order Runge-Kutta method is applied for an ODE system in a time coordinate, see Koren (1993) and Qamar et al., (2012). To be able to compare different process variations, goal functions are introduced and defined as: Productivity (5) (6) ms,out, mseeds, = VL, Pr, Purity (7)

2055 m S,out, = ( c) ms,out, + ms,out, Pu, Mean crystal size ( k) 3 ( k) S,out, = vρ S 0 m k x F (t,x)dx, (8) ( p ) μ1, = ( p μ ) 0, x. An explanation of all equations and all kinetic parameters is covered by Qamar et al. (2012). (9) 3. Results 3.1 Single tank and coupled crystallization m =89 g/min m =0.0356 g/min m =23 g/min m =89 g/min m =0.0356 g/min m =23 g/min m =89 g/min m =89 g/min m =0.0356 g/min m =0.0356 g/min m =23 g/min m =23 g/min m =89 g/min m =0.0356 g/min m =23 g/min m =89 g/min m =0.0356 g/min m =23 g/min Figure 1: Simulation results for continuous preferential crystallization with a continuous seeding mode in a single crystallizer (left side) and two coupled ones (right side).

2056 This study focuses on continuous enantioseparation in a single vessel and in two coupled ones where seeds are added continuously. Coupling of two tanks via their mother liquor leads to a concentration increase of the target enantiomer in the liquid phase and lowers the probability of primary nucleation of the counter enantiomer. Thus, productivity, purity and mean crystal size are improved. Moreover, the coupled case yields both enantiomers in an enantiopure form simultaneously (see Figure 1). Results of the coupled case depict values for only one tank because conditions in both tanks should be the same. Due to a higher mass flow rate of seeds, better productivity and purity can be reached, although the mean crystal size gets smaller (because a larger number of seed crystals utilizes supersaturation). 3.2 Different seed crystal distributions Continuous seeding with different seed size distributions during continuous preferential crystallization in two coupled vessels is analyzed in this case. The properties of seeds are very crucial for the process trajectory. Their size, especially their surface, induces separation by crystal growth and secondary nucleation. For this reason the smaller available seeds, the higher productivity and purity. On the other hand bigger seeds will lead to a bigger product size which can be observed on Figure 2. Increasing mass flow rate of seeds enhances productivity and purity. m =89 g/min m =0.0356 g/min m =89 g/min m =0.0356 g/min m =23 g/min m =23 g/min m =89 g/min m =89 g/min m =0.0356 g/min m =0.0356 g/min m =23 g/min m =23 g/min m =89 g/min m =0.0356 g/min m =89 g/min m =0.0356 g/min m =23 g/min m =23 g/min Figure 2: Simulation results for smaller (x mean =288 nm, left side) and bigger (x mean =730 nm right side) seeds for continuous seeding during continuous preferential crystallization in two coupled crystallizers.

2057 3.3 Continuous and periodic seeding Provision of seeds can be realized in a continuous or periodic mode. During periodic addition of seeds t on represents the time when seeds are inserted into the crystallizer and t off is the time when no seeds are provided. By seeding periodically, the mass of invested seeds can be reduced (see Table 1). Increasing t off leads to a lower productivity because the seed investment is lowered. On the other hand the mean crystal size is bigger due to a smaller number of crystals in the solution consuming supersaturation. Table 1: Simulation results for continuous and periodic seeding during continuous preferential crystallization in two coupled vessels. Seeding t on [min] t off [min] g min ( p ) Seeds, Pu [%] m Pr kg 3 min m z C - - 0.0356 9 0.090 0 P 10 5 44 9 0.076 6 P 10 10 0.0189 9 5 0 P 10 20 0.0126 9 0.054 6 ( p ) [ mm] 3.4 Different exchange flow rates Exchange of the liquid phase between two vessels should keep the concentration at a racemic level throughout the process time. The exchange flow rate should be adjusted to improve the performance of the process. This study case investigates different exchange flow rates during continuous preferential crystallization in two coupled tanks with continuous seeding. Increasing exchange flow rate improves productivity and mean crystal size which can be seen from Figure 3. The mean crystal size can only slightly be enhanced because crystal size depends on a residence time inside the crystallizer which in this study is the same. 0 0.09 5 0.07 0 5 0 5 0 10 20 30 40 50 60 70 80 90 100 volumetric exchange flow rate [ml/min] 0 0 10 20 30 40 50 60 70 80 90 100 volumetric exchange flow rate [ml/min] Figure 3: Simulation results for different exchange flow rates during continuous preferential crystallization in two coupled crystallizers. 4. Conclusions Continuous preferential crystallization in two crystallizers connected through exchange pipes was studied. A concept of MSMPR crystallizer was implemented for enantiomeric resolution. Different process strategies were simulated by means of mathematical models. The effect of connecting two crystallizers via the mother liquor exchange was presented. Seeds with different mean crystal size were compared. Both continuous and periodic modes of seeding were analyzed. The influence of exchange flow rate was shown. It was found that coupled process has improved the values of all goal functions. Seeds with small mean crystal sizes have produced a product of better quality. Periodic seeding could reduce the overall investment of seeds and the mean crystal size of the product could be larger. By increasing the exchange flow rate between the coupled crystallizers, productivity is enhanced. These results could be used to find optimal operating conditions to improve the product quality and reduce operational costs. The experimental validation of this work is currently in progress.

2058 References Elsner M.P., Fernández Menéndez D., Alonso Muslera E., Seidel-Morgenstern A., 2005, Experimental study and simplified mathematical description of preferential crystallization. Chirality 17, 183-195. Koren B., 1993, A robust upwind discretization method for advection, diffusion and source terms. C.B. Vreugdenhil and B. Koren, editors, Numerical Methods for Advection-Diffusion Problems, Volume 45 of Notes on Numerical Fluid Mechanics, Vieweg Verlag, Braunschweig, 117-138. Lorenz H., Perlberg A., Sapoundjiev D., Elsner M.P., Seidel-Morgenstern A., 2006, Crystallization of enantiomers. Chemical Engineering and Processing 45(10), 863-873. Mersmann A., 2001, Crystallization Technology Handbook, second edition, Marcel Dekker, New York, USA. Qamar S., Elsner M.P., Hussain I., Seidel-Morgenstern A., 2012, Seeding strategies and residence time characteristics of continuous preferential crystallization. Chemical Engineering Science 71, 5-17. Randolph A.D., Larson M.A., 1988, Theory of Particulate Processes Analysis and techniques of continuous crystallization. Academic Press, second edition, San Diego, USA. Sapoundjiev D., Lorenz H., Seidel-Morgenstern A., 2006, Solubility of chiral threonine species in water/ethanol mixtures. Journal of Chemical and Engineering Data 51(5), 1562-1566.