The Mechanisms and Control of Impurities in Continuous Crystallization

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The Mechanisms and Control of Impurities in Continuous Crystallization: A Review Christine Darmali, Shahnaz Mansouri, Nima Yazdanpanah, and Meng Wai Woo Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/acs.iecr.8b04560 • Publication Date (Web): 13 Dec 2018 Downloaded from http://pubs.acs.org on December 13, 2018

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Industrial & Engineering Chemistry Research

The Mechanisms and Control of Impurities in Continuous Crystallization: A Review Christine Darmali,a Shahnaz Mansouri,a Nima Yazdanpanah,b and Meng W. Woo*,a a

Department of Chemical Engineering, Monash University, Clayton, Victoria 3800, Australia

b

Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States

Abstract Crystallization has been applied to a broad range of industries such as bulk and fine chemicals, pharmaceutical and food industries. It is important to strategically control the in-situ purification process during crystallization to meet the regulatory and functional specifications of the crystals. While the control of the crystallization-purification process has been widely discussed for batch crystallizers, there has been little focus with the literature on controlling purification for continuous crystallizers. Continuous crystallization is a more intensified approach to crystallization, with lower capital footprint and potentially offering more consistent quality control. This review paper provides an in-depth discussion of the strategies and scientific understanding in controlling the crystallization-purification process in continuous crystallization. In particular, it describes how scientific understanding in the purification process generated so far for batch crystallization, can be translated to continuous crystallization.

Contents 1.

Introduction .......................................................................................................................................... 2

2.

Mechanism in the inclusion of impurities in crystals............................................................................ 4 2.1

3.

Adsorption of impurity onto the crystal ....................................................................................... 4

2.1.1

Thermodynamic adsorption of impurity ............................................................................... 4

2.1.2

Kinetic adsorption of impurity onto the crystal .................................................................... 5

2.1.3

The effect of adsorption impurity on the overall rate of crystal growth .............................. 7

2.2

Solvent Inclusion of impurity into the crystal ............................................................................... 8

2.3

Effective Distribution Coefficients .............................................................................................. 10

2.4

Crystallization of enantiomers .................................................................................................... 11

Continuous Crystallization Types and its Application for Purification ................................................ 12 3.1

Mixed Product Mixed Suspension Removal (MSMPR) ............................................................... 12

3.2

Tubular Crystallizer ..................................................................................................................... 13

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3.3 4.

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Fluidized Bed Crystallizer ............................................................................................................ 16

Control Strategies for Purification in Continuous Crystallization ....................................................... 17 4.1

Process Analytical Technologies (PAT-based) measurement control ......................................... 17

4.2

Predictive based operation of the continuous crystallization process ....................................... 18

5.

Conclusions ......................................................................................................................................... 21

6.

Nomenclature ..................................................................................................................................... 21

7.

Author Information ............................................................................................................................. 22

8.

Acknowledgement .............................................................................................................................. 22

9.

References .......................................................................................................................................... 22

1. Introduction Crystallization is employed to produce an extensive range of materials from primary products, by-products and intermediates in a broad range of industries including food, bulk and fine chemical and pharmaceutical industries.1, 2 Almost 70% of all solid materials produced from the chemical industries involves a form of crystallization process.3 The physicochemical properties (stability and bioavailability) of the final product depend on the crystal characteristics.4-6 As a consequence, many interests have been focused on having a desirable direct control over the crystallization process to attain high and reproducible quality and bioavailability, such as purity, size, shape and polymorphic form in high yield.7, 8 Purity and particle properties such as polymorph and shape of the product obtained from crystallization are the most concerning aspect for determining the quality to meet the regulatory requirements. The presence of an impurity within the crystal can be critical, as it may be potentially harmful to human beings.1 In general, a small amount of impurities is still presence during crystallization as a result from an inefficiency of the upstream process such as a liquid-liquid separator.9, 10 Furthermore, crystallization also affects the efficiency of the downstream processes (e.g. washing, filtration, drying, packaging and formulations of drugs).6, 11 Milling and granulation are usually implemented after the crystallizer which aims to improve crystals properties in the case of out-of-specifications of the desired products.12 Therefore, understanding of the operating conditions that correspond to the product quality with the desired morphology is fundamental during crystallization process development.2, 13, 14 15 In practice, it is difficult to obtain crystals with only pure target compound in the growth medium. The solvent used for crystal growth medium and any other compounds that are intentionally added or inherently presence in the growth medium is considered as an impurity. Examples of such impurities are anions, metallic cations, polyelectrolytes, surfactants, tailor-made additives, solvents, by-products from a reaction, catalyst residuals, polymorphs, or counter-enantiomer.16 The presence of impurities in growth media has been shown to change the growth habit of crystals through their effects on different growth rates on each crystal face, where it may either enhance or retard of the growth process of crystals.17, 18 Impurities which inhibit the crystal growth are known as poison or inhibitors. On contrary, additive and surfactant are terms which are used for impurities which promote the crystal growth rate.18


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Many studies investigated the mechanism of impurities incorporated into crystals in crystallization and found two general mechanisms applied: (1) the adsorption of impurities into the crystal lattice or onto the crystal surface19,and (2) solvent inclusion in the crystals14, 20, 21. The former mechanism can be thermodynamically or kinetically controlled depending on the type and concentration of the impurities, and the conditions in which the crystallization process was taken. A detailed description of these mechanisms will be given in the subsequent sections of this review paper. At the moment, most of the investigation on these mechanisms and how to control them has been widely reported for the batch crystallization process. The traditional batch crystallization process has been dominant within industry as the design criteria, as it has been well established and extensive studied for the past decades.12 The crystallization process is controlled by manipulating the supersaturation of the mother liquor through reactive, evaporative, antisolvent and cooling approaches, which can be applied depending on the needs of the process.22, 23 A key characteristic in the batch crystallization process is that the path of the crystallization process can be well defined. In addition, due to the long operating time of the batch process, the crystallization process is normally operated until it reaches the equilibrium state of the mother liquor. Controlling the path of the crystallization process has been widely investigated and how it manipulates the yield and the purity of the crystals produced. Although this approach may appear relatively simple, its controls can be highly complex which can lead to problems in achieving consistent product specifications from batch-to-batch (e.g. size distribution, correct polymorphic form and morphology).5, 12, 24, 25 Furthermore, due to constraints in mass and heat transfer, scaling up in the batch process is another hurdle as it requires relatively high capital investment and space.5, 26 In contrast, continuous crystallization has garnered great interests in both industry and academia in recent years as it has the potential to overcome the drawbacks of batch processes. It offers the advantages of producing a consistent product specification, whereas, product variations incur on a batch process.11 Furthermore, many problems associated with scaling up can be minimized as the same production rate can be generated for a small scale of the continuous process compared its batch counterpart.11 From the benefit of small scale equipment, it provides flexible controls over the process and lower financially investiment27. However, some limitations of this technology does exist, such as potential line clogging. 5, 28 . These advantages has encouraged industries to shift towards continuous processes. A key characteristic difference between continuous and batch crystallization processes is the path of continuous crystallization has not been well-defined. The process is normally characterized only by the inlet condition and the outlet condition of the mother liquor. In many instances, outlet condition may not be in equilibrium with the mother liquor, due to the short residence time within the continuous process. Therefore, the control of a continuous crystallization process and subsequently the purity of the crystals will be significantly different when compared to a batch process. This review paper will focus and give a consolidated view on how the purification of crystals can be controlled in continuous crystallization processes. As discussed earlier, most of the past reviews available in the literature focused on the control of crystal purity for batch processes. Presently, current work on continuous crystallization focuses on the crystalline particle formation and yield; yet little work has been centred on controlling the impurities presented. This report will bridge the gap between the purity control 3|Page ACS Paragon Plus Environment


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in the batch process with the continuous approach to the crystallization. The review paper will firstly provide an overview of the mechanism in which impurity is retained in the crystallization process. The impurity mechanisms are discussed to provide a better understanding of the mechanisms which might contribute to affecting the purity in the continuous crystallization. Different types of continuous crystallizers will be then discussed and a summary of the reports on the control of impurity for each type of crystallizers are included. The final part of this brief review is an introduction to a few generic approaches in crystallization control which can be applied across different forms of continuous crystallizers.

2. Mechanism in the inclusion of impurities in crystals 2.1 Adsorption of impurity onto the crystal 2.1.1 Thermodynamic adsorption of impurity Impurities can be adsorbed into the lattice or onto specific faces of growing crystals. The adsorption mechanism can be characterized by two components: impurities which adsorb thermodynamically into the crystal, or impurities adsorb kinetically into the crystal.29 The amount of impurity adsorbed thermodynamically is normally driven by the formation of intermolecular bonding to form the least free enthalpy energy corresponding to the equilibrium condition between the mother liquor, host compound and impurity.20 Different molecular structure, size, and weight between the host and impurity compounds will form different free enthalpy energy in the crystal lattice.30 For instance, the crystallization of paracetamol in the presence of 4-nitrophenol has changed the crystal morphology due to its lower energy formed between the host and impurity particle in the crystal lattice.31 Furthermore, the molecular size of the impurity can affect the interaction mechanisms with the crystal surface. For impurity which has a molecular size similar to or larger than the target compound, the impurity molecule will substitute the target molecule.20 However, the larger impurity might disturb or defect the crystal lattice orientation. Whereas, the smaller impurity molecules can insert in between the target molecules in the crystal lattice. This was observed in the crystallization of fructose in the presence of difructose dianhydrides as an impurity.32 Difructose dianhydride has a similar molecular structure as a fructose with two fructose moieties. The impurities were incorporated into the crystal lattice due to the similar molecular structure which hindrance the growth of the fructose solute on the crystal surface and hence, it reduced the overall yield. The incorporation of an impurity into the host component lattice can be determined quantitatively by a distribution coefficient. Distribution coefficient has two types which are equilibrium and effective distribution coefficient.33 These two terms can be used depending on the crystallization process. The equilibrium distribution coefficient of an impurity in a solute is a thermodynamical function of the solution and solid phase. It is defined as the ratio between the impurity concentration to the host compound concentration in the solid phase and in the liquid phase. The following equation defines the equilibrium distribution coefficient34:


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K eq

C (C i ) c solid = (1) C (C i ) c liquid

Where, Keq is the equilibrium distribution coefficient, Ci is the concentration of impurity and Cc is the concentration of the crystallizing compound. The equilibrium distribution coefficient is usually determined from experimental work. This information is then used to model the crystallization process and to further determine how various combinations of process conditions affect the purification process on purity. One main possible application of this approach is to guide the selection of an appropriate solvent or additives to minimize the impurity content.

2.1.2 Kinetic adsorption of impurity onto the crystal In an actual crystallization process, on top of the rate of impurity adsorbed thermodynamically, the total rate or the amount of crystal adsorbed at each point in the crystallization pathway is also contributed by kinetically driven impurity adsorption. The incorporation of impurities into the lattice by the formation of partial or complete solid solutions cannot be influenced by the process conditions as it is thermodynamically driven. In this respect, this is the limit of the purification effect attainable. In order to minimize the impurity in crystals, a key aspect in controlling kinetically controlled impurity adsorption is to identify operating parameter which favours the latter. Conditions during the crystallization process, driven by the supersaturation within the mother liquor, the relative concentration of impurity, the rate of agitation, and cooling rate, may drive the precipitation on the crystal growth unit as well as the impurity components kinetically. Therefore, crystal growth rate can be described as the competition between the impurity adsorption and the growth unit deposition process.35 For instance, if the crystallization process occurs at a very slow rate, at quasi-equilibrium, there will be a different degree of impurity in the crystals at different points of the pathway corresponding to the equilibrium conditions at each point. The degree of mixing can influence on the rate of kinetically driven impurity adsorption through the adsorption of solute to the crystal surface and the desorption of impurity from the interface.20 Its effect on purification in continuous crystallization has a similar concept to the batch process. The influence of mixing depends on both the crystal size and mixing intensity. With sufficient mixing, there will be fewer impurities incorporated into the crystal. It results from the formation of a thinner boundary layer at the crystal-mother liquor interface and the impurity concentration is lower in the thinner boundary layer on the growing face of the crystals.36 Therefore, the rejection rate of impurity is higher and less impurity will entrap in the growing crystal lattice. Whereas insufficient mixing leads to higher concentration of impurities at the crystal-solution interface, due to lack of mass transfer, while increasing the boundary layer. This will cause the rejection of impurity from the interface to be slower and hence, promotes the adsorption of an impurity into the growing crystal face.20 This effect was observed in the separation of enantiomers studied by Gervais and colleagues.37 They showed that the crystals formed by alternating layers between the target enantiomer and counter enantiomer (impurity) without stirring. They found that by providing gentle stirring of the solution, the impurities present within the crystal greatly reduced. 5|Page ACS Paragon Plus Environment


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In addition, mixing does not have a significant effect on purity for small crystals compared to larger crystals. This is because the hydrodynamic boundary layer is thinner around smaller crystals leading to less impurity within the boundary layer.20 However, in some cases, fine particles can incur higher impurity concentration than larger crystals, due to their higher surface area for crystallization, which promotes the adsorption of impurities onto the surface of the crystals38 Gerald and co-workers observed this phenomenon during the continuous crystallization of sodium bicarbonate in the presence of calciumbased additives.38 This fundamental consideration has a significant implication to continuous crystallization as high supersaturation is usually required for continuous crystallization to induce secondary nucleation which leads to the formation of fine particles and hence, promotes the adsorption of impurity on the crystal growth. In common continuous crystallization techniques, the mixing of mother liquor is generated differently depending on the type of crystallizer. For mixed suspension mixed product removal (MSMPR), a typical stirrer type mixing is employed similar to a batch crystallizer, hence, the same consideration in the control of mixing with respect to purification can be applied. The effect of mixing in a tubular, oscillating baffled or fluidized bed crystallizer may offer different mixing and mass transport characteristics when compared to a MSMPR crystallizer. They are currently minimal reports systematically evaluating how the mixing characteristics of these different type of crystallizers compare with respect to the purification process. Furthermore, it is also expected that in continuous processes, the accumulation of impurity over time in the isolated system will be less when compared to batch processes, as the fresh feed is constantly supplied into the crystallizer, while withdrawing the impurities from the system. Another major factor that greatly affects the impurity absorption is the concentration of the impurity. This factor will be discussed in further detail in the following sections. 2.1.2.1 Adsorption at a low impurity concentration At low impurity concentration, the impurity may be adsorbed and disrupt the growth layers at three specific locations of the crystal face: (1) at a kink, (2) steps or (3) on a ledge face between steps (Figure 1).40 At low impurity concentration, the kinetically driven contribution is dominant while the thermodynamically driven adsorption has a negligible role. When kinks are assumed as the preferred adsorption sites, following the Bliznakov kinetic model, a part of the adsorption sites is occupied by the impurity particles, while the remaining sites are unoccupied.18, 39 The coverage site may be described by the usual adsorption isotherm, such as Langmuir and Temkin isotherm, where the coverage of adsorption site increases with an increase in the impurity concentration.18 Consequently, the growth rate of the crystal decreases monotonically with increasing impurity concentration and eventually plateaues.18 In general, the intermolecular bonding energy between the foreign particles and the solute compound is lower, compared to the bonding between both solute compounds. It will lead to the adsorption of the impurity and hindrance the adsorption of the target compound into the crystal lattice. As a result, it causes a change in the crystal lattice energy, disrupting perfect orientation of crystals and hence, modification in the crystal morphology. On the other hand, adsorption site at a surface represents a steric barrier to diffusion of growth units along the step and to their entry into the kinks. This can be described by the Cabrera and Vermilyea model, 6|Page ACS Paragon Plus Environment

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in which the impurities are assumed to be immobile, adsorbed on ledges ahead of steps, where they form a two-dimensional (2-D) lattice.41 The step can move at a reduced rate only if the distance between two adsorbed impurities along the step is d >2rc (where rc is the radius of a critically sized nucleus) as the particles can squeeze in between the gaps; otherwise, they are stopped (dead zone). The mechanism has been verified in many experiments, mainly with organic impurities and tailor-made additives, for example, in the growth of C36H74 from petroleum ether42, in the growth of (101) faces of ADP under low supersaturation43, and in the growth of (001) face of paracetamol44. 2.1.2.2 Adsorption at a high impurity concentration When the concentration of an impurity in the bulk is high, the crystal surface is the preferable adsorption site.39 The growth rate of crystals will be impeded due to inaccessibility of solute compound onto the surface caused by the formation of a homogeneous two-dimensional layer of the adsorbing impurity.18, 45 This adsorption is thermodynamically driven. The formation of adsorption layer is favourable in systems involving impurities of large size (i.e. long chain compounds, surfactants and copolymers) because the interaction between a large inhibiting species and an adsorption site is expected to be relatively weak and the impurity concentration required for inhibiting the movement of ledges is high.18, 46 This was suggested by Sipyagin and Chernov, who discovered that the layer formation might be distributed by the addition of alcohol, which increased the growth rate.42, 47 Adsorption at high impurity concentration could also lead to a formation of surface macro-clusters for supersaturation above the critical values.18 It leads to non-uniform adsorption of impurities on the growing face where some part of the crystal face follows a regular growth mechanism involving twodimensional nucleation or dislocations with or without adsorption, while the growth of other parts are entirely blocked by impurities.42 Surfaces growing with the participation of three-dimensional impurity clusters may exhibit hillocks on them.18, 47 Thus, irregular growth is essentially due to non-uniform adsorption of the impurity on the growing surface.

2.1.3 The effect of adsorption impurity on the overall rate of crystal growth Understanding the effect of adsorption impurity on the overall rate of crystal growth will directly affect the required residence time for crystallization. In batch crystallization, the residence time available for crystal growth can be relatively easy to adjust, a longer crystallization time will mainly translate to a longer batch time and vice versa. For continuous crystallization, control of the residence time is more limited and may be more complex. This will be covered in Section 3 of this work. The effect of impurity on the crystal growth rate is difficult to predict as the thermodynamic and kinetic model are opposed to each other18 as shown in the experiment of Pb(NO3)2 grown in the presence of methyl blue39. In general, as thermodynamically driven impurity adsorption is usually achieved by the incorporation of an impurity into the target compound lattice, it will result in changing the perfect orientation of crystals and disruption of the lattice energy.20 The reduction in the surface energy due to thermodynamically driven impurity adsorption will typically lead to enhance crystal growth rate. At low supersaturation, the growth rate of (100) and (111) face increased at low impurity concentration (the socalled catalytic effect) was attributed to the thermodynamic factor and low density of kinks.39 The adsorption was influenced by the edge free energies on the growth layers.46 However, the growth rate decreased with a rise in impurity concentration at which kinetic factors was dominant as studied by Borsos 7|Page ACS Paragon Plus Environment


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and co-workers in the crystallization of KDP in water.48 This was caused by the desorption of impurity from the crystal-solution boundary was not fast enough so that the impurities became kinetically incorporated into the crystal lattice by interrupting the crystal growth and disturbing the lattice energy on the surface, leading to the formation of more impure product and consequently in yield reduction.20 This phenomenon is often observed in the case of both surface-active additives composed of large molecules and ionic salts.18 On the other hand, at a significantly high supersaturation, a regular decrease in growth rate is observed for small molecular of impurities in which kinetic factor takes over the thermodynamic.14, 18, 47, 49 As the thermodynamic term is fixed for every crystallization system with consistent solute, solvent and impurity, the purification process can only be tailored through the kinetic model by selecting suitable parameters.20 Hence, the mechanisms of impurities incorporated into crystals kinetically are studied to generate a robust purification process to produce pure crystals in industrial crystallization.

2.2 Solvent Inclusion of impurity into the crystal On top of the adsorption of impurity solutes, purification can also be affected when solvent (the bulk of the mother liquor) is incorporated into the growing interfaces as solvent inclusion. The solvent can be incorporated as an impurity via three mechanisms: (1) thermodynamic and kinetic adsorption on either crystal lattice or surface, (2) liquid inclusion into the growing crystal in three-dimensional defects, and (3) solvent entrapment in between crystals.14, 20, 21, 50 The mechanism of solvent being adsorbed thermodynamically and kinetically into the crystal lattice is similar to the adsorption mechanism described in the previous section.20, 51 In view that continuous crystallization is normally undertaken at high initial supersaturation conditions, solvent inclusions are most likely to occur in the process due to the kinetically driven component of the mechanism. The growth rate of the crystal will decrease when reducing the supersaturation as the impurities will occupy the available sites in the crystals gradually.14, 36 There is a possibility for the solvent to adhere on the surface of the crystal in the final products due to the incompleteness of the washing and filtration process. This will lead the solvent molecule to adhere on the crystal surface in which many parameters can have an effect on it, such as the wash ratio in washing, the pressure difference in deliquoring, surface roughness, crystal size, or crystal structure.50, 52, 53 The solvent on the crystals can be found in the void space within the crystal. This could be observed in the crystallization of carbamazepine where the crystals had a low-density packing structure contained large voids, which caused the presence of a solvent in the pores.54-56 Furthermore, crystal size will also affect the washing and filtration performance in the downstream process. In particular, small crystals collected in the product could make the washing and filtration process more challenging, as it has a much greater combined surface area and contains relatively narrow pores in between particles in which solvent can be entrapped.50, 57 This structure will impede the flow of filtrate through the cake, and hence, there is a higher possibility for the solvent to deposit on the surface. One study for the crystallization of bisphenol A gave a product with a purity of 99.5% and the authors discovered that the main source of impurities was from the mother liquor adhering on the crystal surfaces. The crystallization process was then designed to reduce the number of fine particles and to increase the average crystal size, it allowed for the improved 8|Page ACS Paragon Plus Environment

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separation of the crystal product from the mother liquor, giving the material of 99.8% of purity.53 A similar study was also observed in the crystallization of ice and sodium sulfate decahydrate in the presence of phenol as impurity where the washing cycle actually affected the purity of the crystals.58 The author found that the purity of the product increased from 97% to approximately 100% after applying three washing cycles to the crystals. The study found that phenol was not incorporated into the crystal lattice and the impurity could be removed through efficient washing when it was adhered to the crystal surface. The solvent inclusions into the growing crystal in three-dimensional defects can occur due to instabilities growth of the crystals and fast-growing crystals.14 Crystals may reject the impurity during growth, which leads to a higher impurity content, as the impurity accumulate in the crystal-solution interface than in the mother liquor itself. It will cause instability on the crystals boundary which resulting in a dendritic formation where the solvent pocket is entrained in the crystals due to the growth of side branches or direct impingement of dendrites.14, 59 Furthermore, fast growth crystals have a higher likelihood to induce solvent inclusion.14 This phenomena was studied in the fenofibrate at relatively smaller size crystals, at which the two-dimensionally homogeneous layer inclusion will form when the crystals exceed a critical size. This phenomenon was observed in the sodium chloride crystallization60 and hexamine crystallization61. This was also evidenced that a higher content of solvent inclusion was observed when a high initial supersaturation was applied in the crystallization of cyclotromethylene trinitramine from a rapid crystal growth.62 In the subsequent study, Kim and co-workers proposed a method to attain a moderate crystal growth to minimize the solvent inclusion process.63 This was achieved by providing internal seeding to suppress excessive nucleation and temperature cycling to remove the fines particles. It managed to attain a slightly lower solvent inclusion in the crystals when compared to the linear cooling crystallization process. In addition, this was also proved through the simulation developed by Myerson and Kirwan, which they saw a relationship between the solution trapping in the crystallization system.59 It was found that the solution trapping increased with increasing crystal growth rate, while there was a decrease in the absolute value of either negative or positive interfacial temperature gradient. Furthermore, solvent inclusion can be considered when the solvent is entrapped in between crystals through the agglomeration and attritions of crystals.21, 57, 64 Agglomeration usually happened when fine crystals are a presence in the system. The space in between the agglomerated fine crystals is the zone for the solvent entrapment. The aggregated crystals will continue growing by reconstructing the interface between nuclei and hence, solvent inclusions will reduce as increasing in the crystal size in the crystallizer. This phenomenon was observed in the potassium dihydrogen phosphate (KDP) crystallization.21 Agglomeration can also be triggered in the formations of small crystals during the post-crystallization process such as filtration. Nguyen and co-workers investigated that the application of ultrasound had minimized the impurity incorporation into the crystal surface through the cavitation bubble, yet, it led to breakage on the crystals and hence, small crystals were generated.52 The small crystals had a tendency to agglomerate during the continuous filtration where the mother liquor was retained in between the crystals. In addition, the attrition of nuclei can significantly promote the growth rate of the certain crystallographic face at which the nuclei attaches and hence, promotes solvent inclusions. The ratio of the solvent inclusion to water increases as the crystal size is increased, because of collisions of crystals with other crystals, impeller and the crystallizer wall.57 This was also observed in the sodium chloride (KCl) crystallization.64 9|Page ACS Paragon Plus Environment


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2.3 Effective Distribution Coefficients Regardless of the discrepancy attained from the equilibrium distribution coefficients, it can be applied to a non-equilibrium condition, which is named as the effective distribution coefficients. The effective distribution coefficient can be utilized to account for operating conditions such as the cooling rate, agitation rate, local relative impurity concentration, solvent inclusion and crystal growth rate.33 Yazdanpanah and co-workers studied the purity effect of falling film crystallizer and found that the ideal purity of crystals determined through equilibrium distribution coefficient was higher than the experimental result.36 ?. A similar study was done by Li and co-workers in the continuous crystallization of cyclosporine by using a mixed suspension mixed product removal (MSMPR) crystallizer.65 In that study, the effective distribution coefficient was attributed to the solvent composition and properties, mixing and temperature. As aforementioned, the impurities are incorporated into the crystals through the thermodynamic and kinetic adsorption of impurities in the crystal growth and inclusion of solvent.66 The adsorption of the impurities into the crystals or crystal layers will depend on the crystallizer characteristics and the operating conditions. The impurities content at the interface may significantly increase due to high mass transfer and hence, it will have a tendency to attract the impurities. These factors will affect the effective distribution coefficient. By considering the impurities mechanism discussed previously, Yazdanpanah and co-workers had modelled the effective distribution coefficient in the falling film crystallizer which accounting for the combination of the equilibrium distribution coefficient, impurities from solvent inclusion and entrapment of impurities due to crystal growth as shown in Equation 2.33 K eff = K eq,t + Ci,t

msolinc,t + KG ms,t

(2)

Where, Keq is the equilibrium distribution coefficient of the local concentration of impurities at a given time, msolinc,t is the mass of solvent inclusion at a given time, ms,t is the mass of deposited solids in the crystal layer at a given time, Ci,t is the local concentration of impurities at a given time, and KG represents the entrapment of impurities due to crystal growth. From the effective distribution coefficient model discussed above, it can be used to determine the factors which are most influencing the final products’ purity related to the process conditions.6 It was determined that the impurity can be affected thermodynamically, kinetic entrapment of impurities in the growth front and impurities from solvent inclusion. The thermodynamic model is constant for one crystallization system where the solute, solvent and impurities are consistent, and hence cannot be manipulated to control the purity. This term is a function of the relative impurity concentration at the crystal-solution interface where it might contain different concentrations from the bulk. This phenomenon is due to the formation of the boundary layer at the crystal interface where the thickness of boundary layer plays an important role to determine the amount of the impurity which will be adsorbed into the crystal lattice.36 For instance, a thinner boundary layer will contain less impurity molecules into the crystal-solution interface and hence, less impurity will be adsorbed into the growing crystal lattice and vice versa. Meanwhile, the effective distribution coefficient can be minimized and hence, reducing the impurities in the crystals by minimizing the kinetic entrapment of impurities in the growth front and impurities from 10 | P a g e ACS Paragon Plus Environment

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solvent inclusion. The solvent inclusion can be formed due to unstable growth on the crystal from localized supersaturation across the crystal interface and fast growth crystals and also, entrapped in between the aggregated crystals.14, 21, 36, 52 Whereas, the impurities incorporated kinetically can be minimized through determining the operating conditions to produce a thinner boundary layer in the solid-liquid interface.33 Consequently, few suggestions are proposed to minimize the impurity in the crystals. Firstly, the growth rate is directly related to the supersaturation, it has to be maintained at a moderate level to ensure that the primary nucleation is suppressed and the crystals have enough to grow.20 This phenomenon was found during the crystallization of acetaminophen with metacetamol as the impurity. The highest purity achieved when the process was operated at a lower supersaturation ratio where the crystal growth was slower. This phenomenon was also observed in the crystallization of ascorbic acid in the presence of oxalic acid and 2-furaldehyde as impurities where the impurity inclusion increased as the cooling rate increased which resulted in increasing the supersaturation.50 This was due to the fast growth generating at a higher cooling rate which enhances the incorporation of impurities on the crystal surface. Seeding can be utilized to prevent undesired nucleation. A sufficient mixing has to be applied to reduce the incorporation of an impurity into crystals by reducing the mass transfer boundary layer thickness and reject impurities from the crystal surface. Therefore, by ‘cooperating’ these solutions, it can lower the effective distribution coefficient and hence, reducing the impact of impurity on crystals.

2.4 Crystallization of enantiomers In the discussion above, the focus was on the impurity as a different compound molecularly. There is a presence of complexity when the impurity has the same compound but with a different structure such as enantiomers. This is because both target enantiomer and counter enantiomer are kinetically favoured to spontaneous nucleation in the solution. Such thermodynamics based consideration in impurity control has been reported and applied for the continuous crystallization of enantiomers using the ternary solubility phase diagram as shown in Figure 2.67 Phase diagram provides an information on the stable and metastable zone of a compound in order to achieve the desired product quality during crystallization design processes.68 The aims of the enantioselective crystallization process are to grow crystals of one enantiomer while maintains the counter enantiomer in the liquid solution, to selectively extract crystals of a certain desired size.69 There had been many studies on the separation of a racemic compound through preferential crystallization.70-74 One example of a racemic compound solution phase diagram (Figure 2) is shown to provide a clearer discussion on the application of this mechanistic consideration in continuous crystallization. The non-shaded regions are regions in which the composition will remain in the liquid form. Depending on the specification and operation of the continuous crystallizer, the metastable region in which to operate the continuous crystallizer can be determined. As a case in point, Mangold and coworkers studied the continuous fluidized bed crystallizer for the racemic compound, with an interest to obtain high purity R enantiomer, and determined the metastable region bounded by the rectangular box within the non-shaded area.75 The determined metastable region then becomes the guide for the operation in the continuous crystallization. It is noteworthy that the narrower the metastable zone, the more challenging it is to control the purity of the crystals.

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3. Continuous Crystallization Types and its Application for Purification 3.1 Mixed Product Mixed Suspension Removal (MSMPR) MSMPR crystallizer is a typical continuous crystallizer that is frequently found in the industry.77 Its simplicity to convert the existing batch to continuous capacity is one of the benefits.5, 8, 11, 13 It has a similar concept with continuous stirred tank reactor (CSTR) as shown in Figure 3. The feed is fed into the crystallizer continuously, whereas, the product is either withdrawn continuously or intermittently.78 It is fitted with a mixer to maintain the slurry in suspension while the supersaturation solution is formed in the crystallizer at which nucleation and growth of crystals occurred. It is preferred for substances with slow-growing kinetics as longer residence time is permitted. It is able to produce narrow crystal size distribution (CSD), high yield and purity11, 79, as well as stable polymorph80, 81. Moreover, it is also suitable for purification processes such as in preferential crystallization to separate enantiomer from racemate system70, 74 and chiral separation71. The final product properties are usually controlled by the parameters such as temperature, residence time and a number of stages in the MSMPR crystallizer. Due to its relatively simple analysis in MSMPR, it has encouraged the study in determining and studying the crystallization kinetics for various systems. 8, 11, 13, 21, 77, 78, 82-85 MSMPR can be operated in either a single stage or multiple stages in series. The parameters acquired from a single stage is often taken as the basis to predict the crystal size distribution for the multistage MSMPR.77, 83, 86-89 However, the yield obtained in a single MSMPR stage is usually lower than the equivalent batch yield.90 One approach is by increasing the number of stages, it can operate close to the batch equilibrium conditions by allowing longer residence time for the crystals to reach equilibrium.79 However, this might be limited due to the constraint on space, capital, and operating cost of the processes.91 In addition, recycling the solvent back into the crystallizer could effectively enhance the yield.11, 79 It allows longer residence time for the solvent to ‘be retained’ in the crystallizer compared to the crystals. However, the impurity concentration present in the solution will increase unless impurity is being removed by some other techniques. This was studied by Ferguson and co-workers by integrating the process with membrane filtration of the recycled mother liquor.92 The integrated membrane module helps to reduce accumulation of impurities over time.93 Furthermore, the crystal purity can be enhanced by incorporating the complexing agent where this process is utilized when the host and impurity compounds have a similar structure or size.94 The complexing agents have a larger molecular weight and will adsorb the impurity to form the impurity complexation. The impurity complexation which has a larger molecular weight and dimensions will be filtered in the nanofiltration membrane during recycling the mother liquor to enhance the yield. A multistage MSMPR in series is preferable as it affords more degrees of freedom for design such as flexibility in selecting operating temperature to promote growth, availability of extensive cooling surfaces and efficient in energy consumptions.79 Few studies had done on multistage MSMPR in series to optimize the process for achieving the desired product requirements. Zhang and co-workers studied the stage at which the antisolvent was added and showed a significant influence on the final crystal properties, while the yield and purity maintained identical in cascade MSMPR.13 For a system with low crystallization rates, the MSMPR could be controlled in the multistage form by allowing the majority of the nucleation to be conducted in the first stage and crystals growth subsequently.11 It resulted in a larger crystal size and 12 | P a g e ACS Paragon Plus Environment

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narrower crystal size distribution of cyclosporine. Pena and Nagy proposed a novel concept of process intensification which enhanced processing efficiency while maintaining the biopharmaceutical properties in a cascade MSMPR in series.24 The first stage was allocated for nucleation and growth mechanism to obtain desired properties. Whilst, the second stage was tailored for crystals agglomeration to enhance the downstream efficiency. In addition, some studies that cascade MSMPR in series for preferential crystallization offers the greatest promise for creating a truly continuous crystallization process for purification application, allowing constant addition of racemic feedstock with the concomitant recovery of separate individual enantiomers in each respective crystallizer.73 Chaaban and colleagues proposed cascade MSMPR in series at which seeded using opposite enantiomers and with free-crystals liquid exchanged in between crystallizers which caused the concentration of opposite enantiomers to maintain low.70 When the impurity concentration is low, a thin crystal-solution interface will be formed and the impurity adsorption will be suppressed. The authors successfully obtained pure individual enantiomer in each crystallizer but resulting in low yield due to the slow growth kinetics of the system. Besides, a novel study on coupling cascade MSMPR by coupling a free-crystals liquid exchanged between crystallizers with a heated suspension mill was proposed by Vetter and co-workers for preferential crystallization.74 The heated suspension mills was aimed to continuously provide in-situ seeding of the desired enantiomer crystals by breaking parent particles and to dissolve nuclei of the undesired enantiomer at elevated temperature in the corresponding crystallizer. This process was suitable for systems with a narrow metastable zone of the counter enantiomer as the desired enantiomer seed will suppress the nucleation of the opposite enantiomer in the crystallizer. Moreover, the use of mother liquor recycles was added to enhance yield.

3.2 Tubular Crystallizer Tubular crystallizer consists of a long pipe geometry. As the feed material flows through the tubular structure, the solution is progressively cooled in a controlled manner at the wall. In some configurations, antisolvent to the feed material may also be incorporated into the system. It is suitable for fast kinetic substances such as antisolvent, reactive or cooling with fast growth kinetic crystallization process for the process to reach completion without considering the pressure drop constraint in the tube.4, 78, 95 It is known that a plug flow behaviour is required to provide a better control of the crystal size and crystal size distribution (CSD). A high velocity is often required at the initial injection to generate a plug flow behaviour along the tube in the absence of mixer in which it provides a homogeneous mixing. However, it can proceed under conditions of partial segregation, which will result in a wider CSD and possibility of encrustation on the wall without a mixer.4 For instance, in an antisolvent crystallization especially performs at high supersaturation, insufficient mixing in the crystallizer can significantly affect the properties of the product such as crystal size distribution, purity and morphology.96-98 Consequently, few designs had been proposed to obtain a plug flow behaviour to ensure homogeneous mixing, as well as, to generate fine crystals and narrow crystal size distribution4, 99, i.e. by installing a mixer, slug-flow behaviour along the tube, or oscillatory baffled crystallizer. Alvarez and Myerson had installed a Kenics type static mixer along the tube to eliminate the localized uncontrolled supersaturation and induce a more uniform profile velocity (Figure 4).4 Moreover, crystal size could be controlled by introducing antisolvent at multiple points along the tube. Whereas, the slug-flow behaviour with alternating slugs 13 | P a g e ACS Paragon Plus Environment


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between liquid and gas is utilized to form a stable self-circulating slug to provide a homogenous mixing and can be optimized through controlling the slug aspect ratio.100-103 The oscillatory baffled crystallizer generates a homogenous mixing through a pulsed flow through baffles in the pipe by a piston movement. 104, 105 Hohmann and co-workers utilized the coiled flow inverted (CFI) to design a crystallization process of L-analine to achieve a narrow residence time distribution in the tube through minimizing the axial dispersion and operated close to an ideal plug flow behaviour.105 However, agglomeration of crystals occurred when a longer residence time was required by reducing the flow rate as the larger crystals moved slower and tended to deposit on the inner wall. Moreover, it led to unstable operation and subsequently logging within 2 hours of the start-up operation. Tubular crystallizer is prone to the risk of crust formations or fouling deposition on the tubing wall, which will ultimately lead to the clogging of the crystallizer.106 Majumder and Nagy had modelled the encrust layer formation by coupling with the population balance model. Through this model, the mitigation strategy by injecting pure solvent through the crystallizer was recommended to dissolve the encrust layer. Seeding is another alternative to minimize the deposition in the inner wall of the tubular crystallizer. Eder and co-workers found that seeding and operated at a sufficiently high flow velocity led to a robust operation for up to 15 min compared to an unseeded operation which leads to blockage in the tube.106 The seed suspension was prepared in a batch process with the mean particle size of 100 µm was supplied to the tubular section for growth. However, a minimum amount of seed must be added into the tubular crystallizer to prevent any undesired nucleation which could cause a blockage. Consequently, many studies focused the research on generating seed continuously in a separate device before the tubular growth section to control the primary nucleation and on determining the operating conditions to attain a desirable crystal size distribution in the latter tubular section. Wong and co-workers proposed a method for continuous seed generation via continuous contact secondary nucleation where the parent crystals were fixed on the rotating shaft to form seed crystals.107 A further investigation on continuous seeding was carried out through studying the effect of micromixing to induce the primary nucleation. The micromixing happens when the two streams of either between hot and cold solution or between the solute and anti-solvent are merged in dual impinging jet108-110, coaxial100, 111 , radial100, 112 micromixers or Roughton-type vortex mixer95. Jiang and co-workers combined the use of the slug-flow behaviour to minimize the axial dispersion and the primary nucleation was induced by a rapid cooling of a saturated solution in the tubular heat exchanger or by mixing of two saturated solutions of different temperatures in various micromixers.100 It was demonstrated that the seed crystals of uniform crystal size distribution were produced and a large uniform crystal of L-asparagine monohydrate was attained in less than 5 min. This design was suitable for protein such as lysozyme enzyme where the shear forces could inhibit the crystal growth rate. However, the nucleation rate depended on the liquid flow rate and there was a potential of clogging when operating at low velocity.100, 101, 106 Woo and co-workers had conducted a mathematical model from the population balance equation to tailor the seeds’ crystal size distribution from the impinging jet velocity.109 It showed that varying the velocity of the impinging jets with time and the time in which the seed was added into the vessel for growing resulted in different crystal size distributions of the product. A more detailed model was integrated to provide a better understanding on the effect of mixing on crystallization kinetics by coupling computational fluid dynamic (CFD) code with a micromixing model and population balance model.112, 113 This was done by coupling a 14 | P a g e ACS Paragon Plus Environment

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computational fluid dynamics (CFD) code with a multi-environment probability density function (PDF) model. Ultrasound has also been utilized to generate in-situ seeding in the tubular crystallizer to generate a narrow size distribution of the final products by controlling the seed size distribution. It provides an additional degree of freedom by varying the sonicator power on top of controlling the liquid flow rate. Eden and co-workers combined the slug-flow behaviour with slurry and air to generate an individual stable slug to enhance the homogenous mixing and applying direct ultrasonication to induce the primary nucleation.102 Furthermore, the size of the seed can be controlled through fines removal by dissolution from rapid heating before it enters a segmented gas-slurry flow to allow the crystals to grow in the crystallizer. Improvised studies from Eder and co-workers; and Jiang and colleagues used in-direct sonication to control the primary nucleation at a certain section of the tube to narrow the crystal size distribution and hence, the fines dissolution equipment was not required to dissolve certain sizes of the particles.101 It managed to operate for approximately 8.5 min without inducing an excessive secondary nucleation. Slugs of water were used before and after the slugs containing the slurry to allow the pressure drops from the inlets to the outlets to be nearly consistent and hence, it allowed a flexibility in controlling the residence time. In a recent study, Gao and co-workers combined MSMPR and tubular crystallizer system to generate a uniform average size of L-glutamic acid crystals.114 The MSMPR was utilized to control the production of in-situ fine seeds generation with an appropriate control of the parameters at vigorous mixing speed to accelerate the nucleation process and the seed generation is continuously supplied into a three tubular crystallizer in series to promote further growth of the crystals. As supersaturation is usually achieved rapidly in continuous crystallization to promote primary nucleation, it results in an inevitable generation of fine particles. It was noted that the crystal size distribution attained was a consequence of manipulating the nucleation and growth rate. Therefore, few strategies have been suggested by controlling the kinetics. One of those was through controlling the growth and dissolution rates by separating the crystallizer into several segments at which it operates at different temperatures.115, 116 However, it is effective only if the size is dependent on the growth and dissolution kinetics. Another approach proposed in the literature was by applying different injections of antisolvent along the spatial coordinate of the tubular crystallizer.4, 99, 117 Similar to the MSMPR crystallizer, recycling the solid crystal can enhance yield and assist in controlling the shape of the CSD by changing the extraction position along the axis of the tubular crystallizer.118 Neugebauer and Khinast proposed a way to control the crystal size distribution by separating the nucleation and growth zone by modifying the previously stated methods.119 The different mechanism was controlled by different temperature adjustment in the water bath for each tube section. The continuous oscillatory baffled crystallizers (COBC) is a variant of the tubular crystallizer which allows the crystallizing solution through a series of periodically spaced orifice baffles with oscillatory motion as seen in Figure 5 and 6.22, 120 The mixing in a COBC is provided by the generation and cessation of eddies when flow interacts between baffles, and is thus decoupled from net flow driven turbulence.12 It gives homogeneous mixing between the baffles and hence, a plug flow behaviour can be established along the column.12, 22, 121, 122 Of particular attraction, the ability to extend the mean residence time, under plug flow conditions, at a similar mixing intensity, is advantageous to slow processes such as crystallization where 15 | P a g e ACS Paragon Plus Environment


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longer residence times are needed for the induction of nucleation and the subsequent growth of crystals, in addition to a uniform mixing environment facilitating uniform crystal growth.123 Several studies to obtain the crystallization kinetics by using COBC was investigated.124, 125 Moreover, it can be also applied for controlling polymorph.126, 127 Briggs and co-workers designed and operated a COBC to deliver control over the polymorphic form of L-glutamic acid through cooling crystallization process.126 It was found that at lower supersaturation (range of 2-3), a thermodynamically stable β-polymorph was maintained for at least 10 h. However, at a higher supersaturation, it induced the formation of metastable α-polymorph, and resulting in the mixed phase in the final product. The system was robust when a continuous seeding of the β-polymorph was provided. Furthermore, Siddique and co-workers had studied the crystallization of lactose by continuous sonification to generate the α-polymorph nuclei.127 Despite the low yield achieved, the stable α-polymorph was obtained within four hours compared to the batch system which required 13-20 hours. At the moment, there has been no report on the control of crystal purity in the continuous tubular crystallizer system. As discussed in this section, most of the focus hitherto is on controlling the yield and crystal size distributions of crystals produced from the process. This is because the tubular crystallizer system tends to promote the incorporation of impurities as fast kinetics happen which limits its application for purification purpose. The incorporation of impurities is expected to be caused by solvent inclusion and kinetically driven impurity adsorption. It is envisaged that once the area of research is more established to allow more residence time in the crystallizer, it will lay the foundation for a more detailed investigation into the control of impurity in the process.

3.3 Fluidized Bed Crystallizer Fluidized bed crystallizer is typically constructed with a cylinder on cone geometry. Figure 7 illustrates a design of the continuous crystallizer operated for the purification of enantiomers. The operation of the continuous fluidized bed crystallizer is such that a common feed tank containing both enantiomers are feed into separate fluidized bed chambers. Each chamber is seeded with the enantiomer and the counterenantiomer so that different enantiomers are preferentially crystallized in different fluidized beds. Crystals within a certain range are continuously removed from the system and fine crystals are circulated within the continuous system. Product removal occurs via outlet placed at specific positions in the conical sections of the crystallizers to obtain desirable crystal sizes which is one of the advantages. The large particle will sink to the bottom of the bed, it will pass through the sonification process to break them into fine particles and feed them back into the bottom of the crystallizer.129 The CSD as well as the purity of the crystals from this process reached steady states with purity exceeding 97%.128 The high purity was obtained through nucleation of the counter enantiomer was very low due to constant upward flow dragging the nuclei formed out of the crystallizer.7, 128 In essence, this form of the continuous fluidized bed crystallizer has a very similar concept with the two stages MSMPR crystallizers in series. The primary difference is that mixing effect and suspension of the crystals are affected via different mechanism: fluidization versus stirrer agitation. The fluidized bed crystallizer has a broad application ranges from wastewater treatment130-132 to crystallization of inorganic salts from aqueous solutions133, 134. Moreover, its application in pharmaceutical industries is common especially for preferential crystallization of various organic fine chemicals.7, 135, 136 An advantage of constant supersaturation ensures a robust control, where a stable crystal growth and production of 16 | P a g e ACS Paragon Plus Environment

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uniform product crystal size can be attained. On the influence of mixing on crystal precipitation processes—application of the segregated feed model128, 137 Lakerveld and co-workers observed that the secondary nucleation was suppressed in a broad supersaturation range in fluidized bed when compared to a stirred batch crystallizer.137 Yazdanpanah and co-workers explored the purification of acetaminophen with metacetamol as an impurity in the fluidized bed crystallizer.66 The purity of the crystal depended on the supersaturation ratio and crystal growth rate. The highest purity was obtained at lower supersaturation ratio when the crystal growth was slower. In addition, fluidized bed crystallizer allows longer residence time and particles are less prone to attrition and breakage and mixing does not significantly cause the impurity incorporation compared to MSMPR.66, 138 The need for an increased reactor vessel volume and pumping power to ensure stable crystal fluidization are the limitation of the fluidized bed crystallizer. This can lead to higher initial capital costs. Furthermore, the lack of understanding the behind mechanism for scaling up results in difficulty for designing pilotplant. Studies on the effect of seeding on the CSD138, modelling69, 129 and scale-up139, 140 have been investigated. In view of the added complexity of fluidization, the scaling up a process of fluidized bed crystallizer is usually accompanied by the Computational Fluid Dynamics (CFD) modelling.69, 129

4. Control Strategies for Purification in Continuous Crystallization Regardless of the type of continuous crystallizer used, the control over the crystallization process is essential to maintain the product quality at high yield, to suppress the disturbances during the process and to optimize the process performance. The product quality is defined as crystal size distribution, the shape of the desired product and the purity of the product. The control strategies for the general applications of continuous crystallization had been reviewed in details by Wang and co-workers.91 This paper will emphasize more on an overview of the control strategies for the purification application only such as in the presence of impurity, preferential crystallization and polymorph controlling. There are two types of control systems which are direct use of Process Analytical Technologies (PAT-based) measurement controls and Population Balance Equation (PBE) model-based controls.

4.1

Process Analytical Technologies (PAT-based) measurement control

Direct control strategies use the direct measurement obtained from the process analytical technologies (PAT). It is widely used due to its simplicity and the understanding of the crystallization mechanisms behind it are not necessary. Furthermore, consistent properties of the product can be obtained by the application of a model-free feedback controller, it has been applied in the control of crystal size distribution141, 142, crystal shape143, and polymorph144-148. Yang and colleagues used Focused Beam Reflectance Measurement (FBRM) to attain the number of crystals population and had proved to achieve a quick start-up, effectively suppressed the disturbance and excellent control of CSD in both single- and multi-stage MSMPR crystallizer.141 Furthermore, a novel control system had implemented milling at upstream (to control the primary kinetics and seed crystals) and downstream (to control the secondary nucleation kinetics).142 The control of purity from PAT tools in the continuous crystallization has not been well investigated, but there have been many literatures reported in the batch process application. Its implication of the PAT tools in a continuous process is similar to the batch process for the application of the in-line measurement 17 | P a g e ACS Paragon Plus Environment


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of the crystals whereas the control approaches might be different in continuous process as it follows a different crystallization pathway. Few papers had studied on improving the purity of the active polymorphic crystals and narrowing the crystal size distribution with the PAT tools, such as FBRM -to observe the crystallization dynamics indirectly through the number of counts such as the nucleation, growth, agglomeration and aggregation of the crystals; and attenuated total reflectance ultraviolet/visible (ATR-UV/vis) spectroscopy - to measure the solute concentration in the system.144-148 This could be achieved on the basis of the supersaturation or temperature control. Simone and co-workers studied the effect of those two approaches in the crystallization of vitamin B12.148 It was found that the supersaturation control could provide a narrower crystal size distribution while temperature control could promote higher purity of the crystals. The temperature cycles have an effect of rejecting impurities from the crystal lattice because it could dissolve the fine particles and the impurity (unwanted polymorph) on the surface in the heating phase and the growth of crystals were accelerated during cooling period.145, 147, 148 In the following studies, Bakar and co-workers applied a feedback supersaturation control with dissolution cycles to improve the quality of the sulfathiazole crystals in form II depending on the solvent selection.145 In the later study, Simone and co-workers with an additional Raman spectroscopy installed for in-situ measurement to detect the formation of the polymorphic mixture.144 It successfully allowed a pure and stable growth of the desired polymorph by eliminating the undesired polymorph through applying temperature cycle. Process Analytical Technologies (PAT) control has not been applied for the crystallization-purification purpose especially for the different molecular impurity compound presence in the crystals. It is because there is no current instrument available to do a direct in-line measurement of the impurity content in the crystals. However, if the effect of the certain impurity compound on the crystal is known and the expected shape is known, it might be possible to measure the geometry of the crystals to provide an ‘indirect measure’ of impurity and apply this feedback to the controller to obtain the desired crystal shape. The geometry of the crystal can be obtained from imaging analyser which is commonly used. However, the result might not be accurate as the overlapping and agglomeration of crystals can either underestimate or overestimate the crystal size.147

4.2 Predictive based operation of the continuous crystallization process Although experimental results have been used to demonstrate the overall system performance for a range of crystallization solution systems. It is still important to develop a mathematical model, especially on the effect of impurities, for optimization of the crystallizer and to predict the performance of the new crystallization systems.33 In recent years, few studies had focused on developing the kinetics and model analysis for the continuous preferential crystallization.74, 149-151 A mathematical model which describes the crystallization process is known as population balance equation (PBE) model. It is usually employed to estimate the nucleation and growth kinetics through the parameter estimation from the experimental crystal size distribution.8, 12, 82, 152, 153 As a result, it has been used for the design of continuous crystallizers117, 154 , modelling155 to attain a better understanding on the parameters affecting the kinetics 106, 156, 157 , the optimization on crystal purity11, 13, 33, 65, 158, yield11, 158 and crystal size distribution103, 112, 116.


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However, in some systems, the PBE model cannot describe the system or predict the crystal size distribution very well due to the assumptions contributed in it.14 The variables such as breakage, aggregation, growth rate dispersion (GRD), size-dependent growth (SDG) and shape are often affecting the accuracy. For instance, the growth rate was found to be size dependent for small crystals in the organic fine compound83 and potassium sulfate84. The models concerning factors such as aggregation and breakage, which are common occurrences in practice, has been studied.159-163 Moreover, distribution coefficient, a mathematical model which describes the impurity effects quantitatively can also be substituted into the PBE model. A mathematical model which incorporated the impurities effect in the population balance was studied, yet it is still limited to the application of batch crystallization process.164-166 The studies were mainly focused on the additional presence of impurities in the system. Vetter and colleagues presented a population balance model of the crystallization of ibuprofen in the presence of pluronic F127 as an additive.164 The crystallization process was then monitored with PAT tools such as FBRM and ATR-FTIR spectroscopy where the kinetic parameters attained from experiment was fitted into the PBE model prediction using an estimation method of standard nonlinear optimization techniques. It showed that the growth rate decreased due to the adsorption of additive molecules on the crystal surface and hinder the deposition of the solute molecules on the crystal surface. Another study was investigated by Abbou Oucherif and co-workers that an additive of hydroxypropylmethyl cellulose (HPMC) which acts as impurity in the felodipine crystallization.166 The experimental crystallization kinetics results were fitted into the predictive PBE model and it simulated that the additive could inhibit the crystallization process at a very low impurity concentration (0.2 µg mL-1). Alamdari and co-workers developed a mathematical model to predict the effect of the impurity (4-tert-butylphenol) on the crystallization kinetics of bisphenol-A crystals.167 The modelled was the combination of the population balance and the deactivation model which was usually applied in the deactivation of catalyst. It was presumed that the crystals growth has the same mechanism as the deactivation of catalyst where the crystal growth would happen due to a surface reaction on the crystal faces and the secondary nucleation was induced through the breakage of the crystal surface. The model successfully illustrated the impurity effects and showed that traces of impurity would reduce the growth and nucleation rates and increased the agglomeration rate. It was observed that the impurity was adsorbed into the crystal surface and hindrance the growth of the solute particles to the surface. Since there is not many literature reported a quantitative approach to determine the impurity content in the crystals into the population balance model, the effect of the impurities on morphology is a prefer approach to design or optimize the crystallization process. A morphological modelling of the crystallization process usually utilize the multi-dimensional population balance model to study the effect of growth on different faces of the crystals.147 Borsos and colleagues developed a mathematical model to describe the effect of multiple impurities on potassium dihydrogen phosphate (KDP) crystal properties such as particle size and shape.48 Its model utilized the population balance model which included the primary nucleation and growth of each crystal face kinetics and the incorporation of competitive adsorption by Langmuir isotherms. Majumder and Nagy studied the modelling and simulation aspects for predictions of crystal shape distribution in the presence of crystal growth modifiers (CGMs).168 The effect of CGM on crystal shape was modelled using morphological population balance model (PBM) in combination with Kubota19 | P a g e ACS Paragon Plus Environment


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Mullin’s model for the pinning mechanism on the crystal growth.169 Subsequently, a simple feedback control configuration was implemented by manipulating the CGM concentration profile in the crystallizer to control the crystal shape distribution. The simulation results confirmed that very small amounts of impurities in the crystal lattice had a significant effect on the crystal shape. The model showed that the higher initial impurity concentration, the faster it would adsorb into the crystal lattice leading to more impurities incorporated. Furthermore, Zhu and co-workers developed a two-dimensional population balance model with the Kubota-Mullin adsorption model to study the effect of impurities on crystal growth rate in different directions at controlled supersaturation.170 It was simulated that the impurities were strongly inhibited the growth of crystal in L direction, whilst it increased the average width of the crystals in W direction which lead to decrease in the average aspect ratio from 1.9 to 1.2. Another sub-model which can be incorporated into the larger population balance framework for the purification-crystallization control is the Monte Carlo prediction models to determine the shape of the crystals. It is known that the presence of impurity in the crystallization process can affect the shape of the crystals depending on the kinetic growth rate of each crystal face.1, 14, 18, 171 Control on crystal shape distribution was first established in the batch crystallizer used to produce tetragonal hen-egg-white (HEW) lysozyme crystals by using kinetic Monte Carlo (kMC) simulation.172 It included crystal nucleation, growth and shear-induced aggregation to control the evolution of the crystal shape distribution. Subsequently, the method of moments was applied to a population balance model to derive a reduced-order moment model which described the crystal volume distribution. In conjunction with mass and energy balances for the continuous phase, the moment model was used to design a model predictive control (MPC) strategy which drove the crystal shape distribution to a desired set-point value through manipulation of the crystallizer jacket temperature. As a result, it was able to produce crystal aggregates with a desired shape distribution and changed in the average crystal shape due to aggregation process. In addition, Kwon and co-workers used the same methodology to model the crystal nucleation, growth and dissolution through a fines trap in a continuous crystallization process.143 The model could appropriately suppress disturbances, while attaining the desired crystal shape distribution. This concept was successfully applied in the plug flow crystallizer (PFC) by implementing a feed-forward control (FFC) strategy to deal with feed flow disturbances that often occurred during the process.116 Crystals with desired size and shape distribution were produced in the presence of significant undesired effects on the inflow solute concentration and size distribution of seed crystals. A predictive mathematical model to control the formation of desired polymorph is also investigated. One studied by Hermanto and co-workers, a non-linear model predictive control from PBE model was developed for the crystallization of L-glutamic acid from the α-form to the stable β-form crystals.173, 174 It was investigated that the process was more robust by optimizing the concentration profile to maximize the stable polymorph yield compared to controlling the temperature, but it required a very long batch time. Woo and co-worker who explored an integrated model by combining computational fluid dynamics (CFD) code (to observe the mixing effect) with micromixing effect through probability density function (PDF) model (to simulate the fluctuation of the species concentration on the subgrip scale) and PBE model (to simulate the CSD).110 It successfully showed that the CSD could be controlled through adjusting the velocity without much effect on the polymorph ratio of L-histidine in the impinging jet crystallizer.


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All these studies to develop a mathematical model do not consider the mechanism of the solvent inclusion. It has a strong influence on the continuous crystallization as it promotes fast growth crystals at high initial supersaturation level. Consequently, it is significant to include the effective distribution coefficient to determine the amount of impurities in the crystals so that it can help to simulate to the minimum amount of impurity to achieve the desired crystal shape in the future works.

5. Conclusions This review provided a bridge between the understanding of impurity control hitherto mainly developed from batch crystallization and the understanding of the design/control of continuous crystallization. The key to translating this understanding to the continuous mode of crystallization is in the strategic control of the initial supersaturation of the mother liquor. Such a control will be dependent on the mechanism of impurity inclusion inherent in the crystallization system (material and process equipment). This understanding will form the premise for more robust control of the functionality, shape and size of the crystals produced via the continuous crystallization process. There is a significant gap at the moment in the in-line measurement of impurities which will be critical to close the control loop in the purification control in continuous crystallization. Incorporation of the effective distribution coefficient concept into the existing population balance models will potentially expand the capability of the numerical framework to guide the design and operation of the continuous crystallization-purification process.

6. Nomenclature Symbol 𝑑 𝑟 𝐾 𝐶 𝑚

Description The distance between adsorption impurities Radius of the nucleus Distribution coefficient Concentration of impurities Mass

two

Unit m m kg/kg kg

Subscripts Symbol 𝑐 𝑒𝑞 𝑖 𝑐 𝑠𝑜𝑙𝑖𝑑 𝑙𝑖𝑞𝑢𝑖𝑑 𝑒𝑓𝑓 𝑡 𝑠𝑜𝑙𝑖𝑛𝑐 𝑠

Description Critical size nucleus Equilibrium Impurities Crystallize compound Solid phase Liquid phase Effective Time Solvent inclusion Solid, solute 21 | P a g e ACS Paragon Plus Environment


𝐺

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Growth

7. Author Information Corresponding Author *E-mail: [email protected] ORCID iD Christine Darmali: 0000-0002-1457-6938 Nima Yazdanpanah: 0000-0001-7400-1266 Notes The authors declare no competing financial interest

8. Acknowledgement The first authors acknowledges the scholarship support from the Monash Institute of Graduate Research.

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Abstract Graphic



Figure 1 Illustration of adsorption sites of impurities particle at kinks, steps, and surface terrace on the F face of a crystal.

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Figure 2 The ternary solubility phase diagram of the racemic compound. Reproduced from Lu. Y76 and Rougeot. C and Hein, J. E.73.



Figure 3 Schematic Diagram of Continuous Cascade MSMPR Crystallizer.

Figure 4 Schematic Diagram of Tubular Crystallizer with Kenics Type Static Mixer Installed. Reproduced from Alvarez & Myerson (2010). 4

Figure 5 Solution Mixing on the Interaction with the Equally Spaced Baffles. Redrawn from McGlone, et al. (2015).22


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Figure 6 Schematic of a Continuous Oscillatory Baffled Crystallizer Setup. Redrawn from McGlone, et al. (2015).22

Figure 7 Schematic Diagram of Fluidized Bed Crystallizers. Reproduced from Binev and co-workers. 128


The Mechanisms and Control of Impurities in Continuous Crystallization

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