Crystallization of Monohydrate Citric Acid. 1. In Situ Monitoring through

Oct 3, 2007 - Continuous monitoring of the overall solid concentration during the crystallization process was developed using in situ Raman spectrosco...
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Crystallization of Monohydrate Citric Acid. 1. In Situ Monitoring through the Joint Use of Raman Spectroscopy and Image Analysis Caillet,†

Alexandre Gilles Fevotte*,†

Alain

Rivoire,†,‡

Jean-Marc

Galvan,‡

Franc¸ ois

Puel,†

and

CRYSTAL GROWTH & DESIGN 2007 VOL. 7, NO. 10 2080-2087

UniVersite´ Lyon 1, LAGEP, UMR CNRS 5007, UniVersite´ Lyon 1, Baˆ t. 308G, 43 bld. du 11 noVembre 1918, 69622 Villeurbanne Cedex, France, and CPE Lyon, Domaine scientifique de La Doua, 43 bld. du 11 noVembre 1918, BP 2077, 69616 Villeurbanne Cedex, France ReceiVed August 21, 2006; ReVised Manuscript ReceiVed NoVember 21, 2006

ABSTRACT: Seeded batch crystallizations of monohydrate citric acid were performed under isothermal conditions (15 °C). Continuous monitoring of the overall solid concentration during the crystallization process was developed using in situ Raman spectroscopy. Quantitative estimation of the crystal size distribution (CSD) was made possible thanks to in situ image acquisition: off-line CSD measurements were further computed from the recorded pictures. The growth rate of monohydrate citric acid was estimated from solid concentration. Through in situ particle size visualization and quantitative analysis of the pictures, activated surface secondary nucleation was also shown to significantly impact the final CSD. It is underlined that, in addition to continuous Raman in situ spectroscopic concentration measurements, image acquisition yields highly valuable data on the dispersed phase. Advantages and drawbacks of the technique for the monitoring of solution crystallization are discussed. Introduction Today, the industrial production of solid fine chemicals is more and more confronted with the requirement of controlling parameters defining the quality of the particles: habits and size distribution, crystallinity, polymorphic state, chemical purity, etc. Indeed, the properties of solid products (e.g., filterability, specific surface, or therapeutic properties of active pharmaceutical ingredients (API) clearly depend on the state and features of the dispersed solid phase, and this is the reason why it is a major industrial issue to monitor these feature in “real-time”. As far as in-line process analyzers are concerned, substantial progress has been made in the past 10 years; however, it remains difficult to quantitatively measure solid-phase transitions during drug production, processing, and storage.1-4 Among analytical technologies, vibrational spectroscopy appeared as a privileged means of monitoring solids elaboration processes. Attenuated total reflectance Fourier infrared spectroscopy (ATR FTIRS), near infrared spectroscopy (NIRS), and Raman spectroscopy were used in various reported applications aimed at quantifying in line the state of solids generated during industrial crystallization processes. In particular, several applications of Raman spectroscopy were reported during which the solid state of complex organic ingredients was successfully monitored (i.e., polymorphic composition, hydration state, crystallinity, ...). The technique was therefore claimed to be “one of the fastest, most reliable, and most suitable techniques to identify crystals forms in drug products”.5 Actually, it is reasonable to write that many satisfactory technical solutions are available to monitor both the solid composition and the solute concentration during crystallization processes.6-10 As far as the in situ acquisition of relevant information about the dispersed phase is concerned, the situation is more difficult and appears to be more challenging as it is clear that no accurate and reliable crystal size distribution (CSD) * To whom correspondence should be addressed. E-mail: fevotte@ lagep.cpe.fr. † Universite ´ Lyon 1, LAGEP, UMR CNRS 5007. ‡ CPE Lyon, Domaine scientifique de La Doua.

sensors have been developed and marketed yet. As outlined by many authors,10 in-line size distribution sensors provide fingerprints of the time variations of particular crystallization systems rather than real CSD measurements. From this point of view, one of the major problems is due to the difficulty of establishing theoretical models relating indirect CSD measured data (e.g., light scattering, laser reflectance, acoustic attenuation, etc.) to the real CSD. This latter limitation of existing techniques becomes more and more restricting when the difference between the actual particle shape and ideally spherical particles cannot be neglected.11-15 As a consequence, due to the lack of trustworthy particle size data, theoretical studies aiming at quantitatively modeling the time variations of CSD often remain questionable. Among existing particle sizing techniques, image acquisition and processing appear as a possible means of circumventing the many difficulties mentioned above. For both industrial applications and academic research, “seeing” the real particless and, consequently, dealing with true crystal shapessis obviously an invaluable means of monitoring crystallization processes. Unfortunately, serious restrictions make the in-line and in situ use of image analysis difficult. Among these restrictions, two major difficulties should be outlined: first, it is unrealistic to analyze pictures of concentrated slurries (i.e., with solid contents above about 8-10%); second, the processing algorithms allowing reliable CSDs to be computed still lack of efficiency. Nevertheless, it is one of the goals of the present work to show that image analysis (IA) can yield in situ CSD quantitative estimates. Valuable information about the basic crystallization mechanisms also can be obtained from the qualitative analysis of pictures recorded during the course of the crystallization process. The study presented here is the second step of a larger work focused on both monitoring and population balance modeling of phase transition phenomena during solution crystallization processes. With this aim in view, citric acid was selected as model product, even though “true” polymorphism is not involved in this case. The anhydrous to monohydrate phase transition of citric acid in water takes place below a transition

10.1021/cg060557b CCC: $37.00 © 2007 American Chemical Society Published on Web 10/03/2007

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Figure 1. Schematic of the lab-scale crystallization plant equipped with in situ Raman spectroscopy and image acquisition for the monitoring of anhydrous citric acid isothermal crystallization experiments.

temperature of about 34 °C.16 A previous paper17 has reported the possibility of measuring in-line both the overall solid concentration and the composition of the solid phase with various anhydrous and monohydrate concentrations of the solid phase in suspension. Following and complementing our previous paper, the present series of two papers in this issue reports the joint use of Raman spectroscopy, together with in situ image acquisition, to monitor both the solid concentration and the CSD of anhydrous citric acid, respectively (this is the aim of the present paper, Part 1 in this issue). The estimation of nucleation and growth kinetic parameters, followed by the development of a PBE model relating the isothermal crystallization of citric acid monohydrate, will be presented in the following paper in this issue (Part 2 of this series). In other words, Part 1 reports on the experimental approach that was developed to monitor both the continuous and dispersed phases present in suspension and on the qualitative analysis of these results that led to the selection of kinetic nucleation and growth equations. The following paper (Part 2 in this issue) deals with quantitative kinetic modeling of the crystallization process, including the estimation of kinetic parameters, and the development of a mathematical model, based on population balance equations (PBE) describing the CSD time variations. Experimental Section The crystallization of citric acid in water was investigated as a model system. Data on the behavior of the monohydrate/anhydrous transition of this organic compound are available in the literature;16 in particular, the solubility of citric acid is very high (about 1.5 kg/kg of water at 20 °C). Above 34 °C, the anhydrous form is the more stable form, while the monohydrate becomes more stable below this temperature.17 Both the monohydrate and the anhydrous solids were purchased from Acros Organics (citric acid anhydrous, Reagent ACS, 99.5% and monohydrate p.a.) and used in distilled water without further purification. Figure 1 shows a schematic representation of the lab-scale crystallization equipment that was used in the present study. The 2.5 L glass reactor was equipped with a jacket and a condenser. Stainless-steel baffles were used in conjunction with a speed-controlled stirrer. A high efficiency profiled-blade propeller (Mixel TT) maintained a good homogeneity of particles in the slurry. The stirring rate was constant and set to 415 rpm. The whole operating device was instrumented and microcomputer-controlled to allow the tracking of temperature trajectories and/or of constant temperature set-points. In situ measurements were performed using the ReactRA Raman spectrometer manufactured by Mettler-Toledo, equipped with a 16mm diameter immersion Hastelloy probe sealed with a sapphire window. As shown in Figure 1, the probe is connected to the spectrometer through fiber optic (200 µm) allowing spectral resolution

of 7 cm-1. The light source is an integrated stabilized 785 nm laser diode with a 300 mW nominal output. The detection is ensured by an open electrode charge coupled device (CCD) with a resolution of 1024 × 256 pixels, cooled using a Peltier element. The calibration of the Raman measurements was developed and presented elsewhere.17 A twofold calibration model was previously developed, which allowed us to estimate the solid composition and the overall solid concentration in the slurry from the Raman spectral data. Actually, no satisfactory multivariate model was found to predict both variables quantifying the solid phase. The measurement of anhydrous/monohydrate composition was finally obtained from the experimental relationship between a specific ratio of peak heights and the composition of samples slurries prepared with known composition. The in-line measurement of the overall solid composition was satisfactorily ensured using partial leastsquares (PLS) analysis performed after vectorial normalization of the spectral data. The absolute uncertainty of the overall solid composition measurement was found to be on the order of 3%, for measurements performed in the range 0-25 wt %, while it was found to be about 10% for composition measured between 0 and 100% anhydrous concentration. Using such calibration, complete information about the solid phase (i.e., partial and overall solid concentration) was therefore obtained in real time, which is a very significant advantage of the technique. Moreover, through the computation of solute mass balance, the obtained Raman solid concentration measurements allowed computing reliable estimates of solute concentration, even though this latter concentration was not directly measured. In the following, continuous in-line supersaturation estimates were computed using the “measured” dissolved monohydrate concentration and the available solubility data. The solute concentration was expressed on the basis of anhydrous content. Two definitions of supersaturation were used:

∆C(t) ) C(t) - C*(T(t)) σ(t) )

C(t) - C*(T(t)) C*(T(t))

(1) (2)

where C* is the solubility and C is the estimated solute concentration expressed in % (100 kg of anhydrous basis solid/kg of water.) ∆C(t) and σ(t) will be referred to as absolute and relative supersaturation, respectively. The monitoring of the dispersed solid phase was performed using in situ image acquisition and off-line image analysis. As depicted in Figure 2, pictures of the suspension were taken using the CCD camera probe developed in our laboratory. This equipment was described elsewhere.18,19 The use of the probe is restricted to the first minutes of the crystallization process, due to the difficulty of separating individual particles for estimating their size at high solid contents. Despite such stringent limitation, the extraction of CSDs from pictures such as the ones presented in Figure 2 is invaluable for process modeling purposes

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Figure 2. Development of isothermal batch crystallization of monohydrate citric acid during run 3: monitoring of the relative supersaturation using Raman solute concentration measurements and typical acquired images.

because, unlike other size analysis techniques, image processing allows one to take the real particle shape into account and therefore to extract relevant and reliable size information. The sampling period for the acquisition of one picture was 1 s. The projected area of each particle was determined using analySIS, an image processing software developed by Soft Imaging System. To obtain a one-dimensional representation of the particles, the diamond-like crystals shown in Figure 2 were compared to equivalent spheres. The diameter of spherical particles with same projected area than the real crystals was computed from the recorded images. This diameter was stored as the “measured” particle size. Such characteristic equivalent size is referred to as Dm in the following. The experimental design was focused on the investigation of the nucleation and growth kinetics of monohydrate citric acid, which is stable at 15 °C. Indeed, as far as the identification of kinetic models is concerned, it is essential to separate the various mechanisms involved and to reduce the number of unknown parameters. From this point of view, seeding avoids dealing with primary nucleation, on the one hand, and allows ensuring satisfactory experimental reproducibility, on the other hand. Stirred temperature-controlled slurries of seed crystals were prepared from sieved monohydrate particles; the class of size was selected to be 250-315 µm. To “activate” the seed crystals through partial surface dissolution, about 3% of the solid mass was dissolved prior to its introduction in the reactor. Six typical crystallization operations were selected for the present study. As displayed in Table 1, runs 1-4 were carried out with almost constant seed mass, to evaluate the effect of the initial degree of supersaturation on the progress of the crystallization phenomena (i.e., secondary nucleation and growth). Runs 5 and 6 were further performed to get additional information on the effect of the seed mass and, notably, to investigate more deeply the initial growth of the seed crystals.

Results and Discussion Effect of the Initial Supersaturation. Figure 3 displays the de-supersaturation profiles measured using Raman spectroscopy during batch runs 1-4. Slight corrections of the measured

Table 1. Main Experimental Conditions of the Selected Batch Seeded Crystallization Experiments

run 1 run 2 run 3 run 4 run 5 run 6

initial solute conc (kg/kg)

duration of the CSD measurements (min)

initial relative supersaturation (%)

absolute seed mass (g)

relative seed mass with respect to final mass of solid (%)

1.40 1.50 1.60 1.70 1.7 1.39

150 26 12 6 6 150

3.8 11.3 18.3 26.0 3.5 26.4

1.03 1.07 1.15 1.12 12.23 12.06

1.57 0.55 0.36 0.25 2.64 12.0

concentration trajectories were brought to the experimental data so as to obtain the convergence of the final concentration to the solubility (i.e., 1.348 g L-1 at 15 °C). Indeed, as they mainly reflect the dispersed solid phase present in suspension, Raman spectra are likely to exhibit some dependency upon both the solid content and the CSD. This problem was mentioned by several authors21,22 but, to the best of our knowledge, was never investigated in detail. It is likely that the calibration previously developed for the Raman measurements17 is sensitive to such effects, which were not explicitly taken into account. For both anhydrous/monohydrate composition (even though the solidphase composition was not involved in the present study) and solid concentration measurements, some drifts of the initial and/or final values were observed, which could easily be corrected as both the initial and the final concentrations are known with accuracy. The drifts in question never exceeded 10% of the measured value and were corrected assuming a linear relationship between the measured value and the corrected ones.

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Figure 4. Estimation of the growth kinetic parameters from runs 1-4.

Figure 3. Measured solute concentration profiles during runs 1-4.

For all experiments, the pattern of the measured concentration profiles is similar. An initial plateau phase, characterized by low solute consumption, is followed by a noticeable drop of supersaturation. Figure 2 displays a qualitative overview of the time variations of CSD during the seeded batch crystallization process. As expected, Figure 3 shows that the overall rate of crystallization increases with the initial level of supersaturation. For a given supersaturation value, the rate of solute consumption (i.e., the rate dC/dt measured at fixed value of C(t)) varies with the level of initial supersaturation. This observation suggests that the seed crystals are not the only growing particles and allows the assumption that secondary nucleation mechanisms generate increasing number of particles with increasing initial supersaturation levels. It is therefore likely that the growth of secondary nuclei occurs in competition with the growth of seed particles during the de-supersaturation process. Such an assumption is also consistent with the fact that the duration of the initial plateau phase decreases with increasing initial supersaturation. Actually, the initial variation of solid mass, ms, can be related to the linear growth rate according to the following expression:20

RG )

φv φv dDm 1 dms )3 )3 Fm F G ac dt φA dt φA m m

(3)

where RG is the rate of solute consumption per unit seed area [kg m-2 s-1], and Gm is the linear growth rate for monohydrate crystals [m s-1]. Assuming the following linear overall growth expression 4, one can compute the time evolution of ms (measured using in situ Raman spectroscopy) using eq 5:20

Gm )

dDm ) Kgm∆C km ) Kgm(C(t) - C/m)km dt

(4)

dms φv | ) 3ac,0 FmKgm∆C0km dt t)0 φA

(5)

where index 0 refers to the initial conditions, index m in eq 4 refers to the solubility of MCA, C(t) is the solute concentration, km is the supersaturation exponent for monohydrate crystal growth, ac is the overall seed area [m2], Fm is the density of monohydrate crystals [kg m-3], ms is the mass of crystals [kg], φv is the volume shape factor (π/6 for spherical particles) [-],

φA is the area shape factor (π for spheres) [-], Kgm is the overall monohydrate growth kinetic constant (varying with km), and km is the growth kinetic exponent [-]. Because the seed preparation and the amount of seed particles are constant for runs 1-4, one can assume constant initial seed area, ac,0, which leads to the following expression:

ln

( |) ( dms dt

t)0

) ln 3ac,0

)

φv F K + km ln(∆C0) φA m gm

(6)

Figure 4 displays the plot of expression 6, as computed from runs 1-4. The two kinetic parameters for the initial growth expression 4 were thus estimated:

Gm ) 5.1 × 10-6∆C1,55

(7)

The intercept in Figure 4 gives Kgm, the overall growth coefficient at 15 °C, assuming that the geometric ratio φv/φA is equal to 1/6 (spherical particles). The density of monohydrate citric acid23 is 1542 kg m-3, and the initial seed area, computed from the average size of seed particles, was assumed to be on the order of 0.0315 m2. Expression 7 cannot be regarded as accurate, due to the many simplifying assumptions that are required before writing eq 6, and to obvious measurements uncertainties during the calculation of the initial slope dms/dt. However, the estimated rates will be used further to specify more clearly the impact of the initial seed growth on the solute concentration profile. As outlined above, and as displayed in Table 1 (third column), the possibility of monitoring the dispersed phase using in situ IA during the crystallization process depends on the solid contents and, consequently, on the rate of crystallization. This explains why the CSD was measured during run 1 until time t ) 150 min, while this time was reduced to t ) 6 min during run 4. Figure 5 displays some of the size distributions that were computed using image analysis. For the sake of readability, the size classes are presented with a rather wide width of 100 µm. The overall trend of the evolutions of CSD presents many similarities for all batch experiments. The reproducibility of the CSD of the seed particles is satisfactory, as shown in Figure 5 for initial measurements (i.e., at time t ) 0). The mode of the initial seed size is located at about 175 and 380 µm, if one considers the number and weight distribution, respectively. For all experiments, it appears that the number of fine particles increases with time. This latter increase becomes more intense for increasing initial supersaturation levels. The bimodal mass distribution obtained after runs 1 and 2 (Figure 5b,d) shows the continuous growth of seed particles together with the generation of new fine particles. In contrast with runs 1 and 2, the amount of fines during runs 3 and 4, which were performed

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Figure 5. (a-h) Number (left) and weight (right) CSD measured using image analysis, during runs 1-4. Dpa is the diameter of the equivalent sphere with same projected area than the measured particle.

at higher initial supersaturation levels, becomes very soon predominant with respect to the population of growing seed particles. Such observations suggest the onset of activated secondary nucleation. It is clear also that increasing initial supersaturation yields higher solids content in the crystallizer and allows more frequent collisions between crystals. The observed generation of fine particles could therefore also be attributed to attrition phenomena. Finally, one can reasonably assume that the intensification of the secondary nucleation rate with the initial supersaturation results from competitive attrition and activated nucleation mechanisms. However, it should be noticed that the experimental information is not sufficient to differentiate the two mechanisms from the only particle size analysis displayed in Figure 5. It is also important to notice that the assumption of contact secondary nucleation phenomena is consistent with the previous observations made from the measured supersaturation profiles displayed in Figure 3. Effect of the Mass of Seeds. To obtain more experimental information about the respective contribution to the solute consumption of initial seed growth and overall secondary nucleation, the previous experimental results are now put in

contrast with the results obtained after runs 5 and 6 where the mass of seeds was significantly increased. As shown in Table 1, run 6 can be compared to run 1, and run 5 can be compared to run 4, the initial supersaturation values being quite similar while the seed mass was increased by a factor of about 12. As displayed in Figure 6, the solute concentration profiles measured during runs 5 and 6 exhibit similar trends: no clear plateau precedes the concentration drop, which is now steeper. This latter experimental increase of the initial rate of solute consumption can be explained in two ways: First, the seed area is higher, which allows increased solid integration rate through crystal growth. Second, the secondary nucleation rate can be promoted by higher solids concentration in the slurry, subsequent growth of nuclei leading to higher solute consumption. To discriminate between these two possible mechanisms, which of course could occur simultaneously, the seed growth rate was roughly evaluated from the measured initial rates of concentration decrease, as described above. Using eq 7, the initial slope dms/dt was computed for both runs 5 and 6, after estimating the initial seed area ac,0. The calculated results were then compared with the experimental

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tion of initial crystallization process dominated by the growth of seed particles, without excluding continuous secondary nucleation mechanisms. In fact, the pictures displayed in Figure 7 show clearly the onset of fine particles during both runs 5 and 6 (see the second and fourth pictures presented in Figure 7.) However, it is worth noting that only a few fines were observed during run 5, even after 215 min. Selected Secondary Nucleation and Growth Kinetic Expressions. For the sake of simplifying the modeling approach, the growth of monohydrate crystals was described using the following “standard” phenomenological expression:

Gm )

dDm ) Kgm∆Ckm ) Kgm(C(t) - C/m)km dt

(8)

As explained above, in situ image acquisition has clearly shown that secondary nucleation is involved during the crystallization process, even though this phenomenon does not significantly impact the initial solute consumption. Indeed, the onset of secondary nucleation is not surprising as really high solid concentrations are involved during the crystallization of citric acid in water. However, the previous analysis of the experimental results has demonstrated that the generation of secondary nuclei depends significantly on both supersaturation and solid concentration in suspension. It was also underlined that, even though several mechanisms are likely to occur,22,24 one can hardly discriminate the respective contribution of these mechanisms to the overall particle generation. This is why the following phenomenological model was selected to relate the secondary nucleation events as a whole: Figure 6. Comparison between the concentration profiles measured during runs 4, 5 (a) and 1, 6 (b). Table 2. Comparison between Estimates of the Initial Rates of Solid Generation during Runs 5 and 6

run 5 run 6

dms/dt|t)0, computed using eq 7 (kg/s)

dms/dt|t)0, from Raman measurements (kg/s)

2.9 × 10-4 1.2 × 10-5

2.1 × 10-4 0.7 × 10-5

ones, as displayed in Table 2. The values of dms/dt computed using eqs 6 and 7 are rather similar to the experimental ones, which allows one to state that the increase of seed amount does not significantly trigger initial secondary nucleation phenomena. The growth of seed particles would therefore be sufficient to explain the shape of the initial concentration profile. Now, examination of the size distributions should confirm this assumption. Figure 7 displays a comparison between the CSDs estimated through in situ image analysis during runs 1, 6 and 4, 5. For low seed amounts, the contribution of fine particles to the overall crystallization process is rather important, which clearly leads to bimodal weight distributions. The last measured CSD comprises many fines and, as a consequence, a second population of “big” particles. In contrast, for high seed amounts, the CSD is narrowed and mainly corresponds to grown seed particles: compared with the previous case, the last measured weight CSD exhibits few fines, and the second population of larger particles is represented by a larger percentage and smaller average size. These observations confirm the previous assump-

/ jm RNm(t) ) K2mCim S (t)‚(C(t) - Cm)

(9)

where RNm is the secondary monohydrate nucleation rate [Nb s-1 m-3], CS is the concentration of monohydrate crystals in suspension [kg/m3], K2m is a “lumped” kinetic constant for secondary nucleation of monohydrate, C/m is the monohydrate solubility in anhydrate basis (kg of Anh/kg of water), and im and jm are exponents related to the secondary nucleation of monohydrate particles. Among the many equations proposed in the literature, and despite the fact that mechanistic models could be evaluated here, eq 9 was selected for its ability to account for both the supersaturation and the overall solid concentration dependency of the rate of particle generation. The related parameters were estimated through one-dimensional population balance modeling of the crystallization of monohydrate citric acid, which will be the object of a forthcoming paper. Conclusions Batch seeded isothermal crystallization of monohydrate citric acid in water was investigated as the first stage of a wider study devoted to the modeling of the anhydrous to monohydrate phase transition of citric acid at 15 °C (i.e., below the transition point of the system.) The occurrence and the intensity of the basic nucleation and growth mechanisms occurring during this process were examined. Both continuous in situ Raman measurements of solid concentration and estimates of the CSD were performed to monitor the crystallization. CSD analysis was developed from in situ image acquisition performed

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Figure 7. Time variations of the monohydrate weight-CSD during runs 1, 6 (a) and run 4, 5 (b), and selected pictures of the slurry at two different times during runs 6 (a, pictures 1 and 2) and 5 (b, pictures 3 and 4).

during the first moments of the batch operation (i.e., before the solid content was too high to allow separating the observed particles). After seeding, both the measured desupersaturation profiles and the time variations of the CSD were explained by the simultaneous occurrence of secondary nucleation and crystal growth of two different populations of particles: seed crystals and particles issued from sustained secondary nucleation. However, qualitative examination of the experimental results did not allow us to fully establish the different possible secondary and/or heterogeneous nucleation mechanisms involved. It was thus proposed that, on the whole, secondary nucleation would be described using a single phenomenological law. The experimental results demonstrate promising features of the in situ image acquisition technique. First, visualization of the crystals in suspension provides reliable information about the mechanisms involved. Unlike model-based optical sensing techniques, one can observe and count particles without being misled by unsuitable CSD analysis models. Second, the physical meaning of the measured characteristic particle sizes is clearly defined and can be selected without any complication, even when complex particle shapes are involved (which is not true for standard models used in analytical equipments on the market.) Third, one can rather easily get specific information on the different population of particles involved (i.e., during the present study, it was possible to see that neither agglomeration nor breakage was significantly occurring and to separate

seed crystals from nucleated particles). However, some major drawbacks and restrictions of the technique were also outlined: small crystals (crystals below 15 µm) cannot be detected with “standard” optics, and, as mentioned above, measurements cannot be performed until the end of the crystallization process as the solid concentration should remain below a threshold value of about 8-10 wt %. References (1) Bernstein, J.; Henck, J. O. Cryst. Eng. 1998, 1, 119-128. (2) Bauer, J.; Spanton S.; Henry, R.; Quick, J.; Dziki, W.; Porter, W; Morris, J. Pharm. Res. 2001, 18, 859-866. (3) Brittain, H. G. Polymorphism in Pharmaceutical Solids; Marcel Dekker; New York, 1999. (4) Threlfall, T. L. Analyst 1995, 120, 2435-2460. (5) Auer, M. E.; Griesser, U. J.; Sawatzki, J. J. Mol. Struct. 2003, 661662, 307-317. (6) Wang, F.; Wachter, J. A.; Antosz, F. J.; Berglund, K. A. Org. Proc. Res. DeV. 2000, 4, 391-395. (7) Fevotte, G. Int. J. Pharm. 2002, 241, 263-278. (8) O’Sullivan, B.; Barrett, P.; Hsiao, G.; Carr, A.; Glennon, B. Org. Proc. Res. DeV. 2003, 7, 977-982. (9) Hu, Y. R.; Liang, J. K.; Myerson, A. S.; Taylor, L. S. Ind. Eng. Chem. Res. 2005, 44, 1233-1240. (10) Yu, L. X.; Lionberger, R. A.; Raw, A. S.; D’Costa, R.; Wu, H.; Hussain, A. S. AdV. Drug DeliVery ReV. 2004, 56, 349-369. (11) Wynn, E. J. W. Powder Technol. 2003, 133, 125-133. (12) Ruf, A.; Worlitschek, J.; Mazzotti, M. Part. Part. Syst. Charact. 2000, 17, 167-179. (13) Worlitschek, J. M.; Mazzotti, M. Cryst. Growth Des. 2004, 4, 891903.

Crystallization of Monohydrate Citric Acid (14) Li, M.; Wilkinson, D. Chem. Eng. Sci. 2005, 60, 3251-3265. (15) Li, M.; Wilkinson, D.; Patchigolla, K. Chem. Eng. Sci. 2005, 60, 4992-5003. (16) Groen, H., Roberts, K. J. J. Phys. Chem. B. 2001, 105, 10723-10730. (17) Caillet, A.; Puel, F.; Fevotte, G. Int. J. Pharm. 2006, 307, 201-208. (18) Subero-Couroyer, C.; Mangin, D.; Rivoire, A.; Blandin, A. F.; Klein, J. P. Powder Technol. 2006, 161, 98-109. (19) Blandin, A. F.; Mangin, D.; Subero-Couroyer, C.; Rivoire, A.; Klein, J. P.; Bossoutrot, J. M. Powder Technol. 2005, 156, 19-33. (20) Myerson, A. S. Handbook of Industrial Crystallization; ButterworthHeinemann, Worburn, MA, 2003.

Crystal Growth & Design, Vol. 7, No. 10, 2007 2087 (21) O’Sullivan, B.; Barrett, P.; Hsiao, G.; Carr, A.; Glennon, B. Org. Proc. Res. DeV. 2003, 7, 977-982. (22) Scho¨ll, J.; Bonalumi, D.; Vicum, L.; Mazzotti, M.; Muller, M. Cryst. Growth Des. 2006, 6, 881-891. (23) Lague´rie, C.; Aubry, M.; Couderc, J. P. J. Chem. Eng. Data 1973, 21, 85-87. (24) Mersmann, A. Fundamentals of Crystallization. Crystallization Technology Handbook, 2nd ed.; Marcel Dekker: New York, 2002.

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