In Situ Measurement of Solution Concentration during the Batch

Dec 29, 2008 - Antonia Borissova,† Shahid Khan,† Tariq Mahmud,*,† Kevin J. Roberts,† John Andrews,‡. Paul Dallin,‡ Zeng-Ping Chen,§ and J...
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In Situ Measurement of Solution Concentration during the Batch Cooling Crystallization of L-Glutamic Acid using ATR-FTIR Spectroscopy Coupled with Chemometrics Antonia Borissova,† Shahid Khan,† Tariq Mahmud,*,† Kevin J. Roberts,† John Andrews,‡ Paul Dallin,‡ Zeng-Ping Chen,§ and Julian Morris§

CRYSTAL GROWTH & DESIGN 2009 VOL. 9, NO. 2 692–706

Institute of Particle Science and Engineering, School of Process, EnVironmental and Materials Engineering, The UniVersity of Leeds, Leeds LS2 9JT, U.K., Clairet Scientific Limited, 17/18 Scirocco Close, Moulton Park Industrial Estate, Northampton NN3 6AP, U.K., and Centre for Process Analytics and Control Engineering, School of Chemical Engineering and AdVanced Materials, The UniVersity of Newcastle, Newcastle NE1 7RU, U.K. ReceiVed October 17, 2007; ReVised Manuscript ReceiVed September 9, 2008

ABSTRACT: The in situ measurement of solution supersaturation associated with the batch cooling crystallization of L-glutamic acid (LGA) at 500 mL and 20 L scale sizes is assessed via ATR-FTIR spectroscopy. A partial least squares chemometric calibration model was developed for the online prediction of LGA concentration from measured FTIR absorbance spectra overcoming some significant challenges related to the low sensitivity of LGA in the mid-IR frequency range, its low solubility in water, and its complex speciation chemistry. The solubility data of LGA in water over the temperature range from 40 to 80 °C, using ATR-FTIR, reveals excellent agreement with those obtained both from using a gravimetric method and literature data. The metastable zone width determined using the turbidimetric methods as a function of heating/cooling rates and solute concentration is found to increase with increasing cooling rate while it decreases with increasing solution concentration. Monitoring online crystallization via both spontaneous and seeded in 500 mL and 20 L crystallizers reveals good concentration predictions for seeded crystallization, while fouling of the ATR crystal prevents its routine use for unseeded crystallization studies. Higher supersaturation levels are found for the larger crystallizer scale-size consistent with enhancement of secondary nucleation at the smaller scale-size. Introduction An important and recent focus of the chemical industry has been associated with the manufacture of high-added value specialty materials such as agrochemicals, dyes and pigments, food and confectionery products, fine chemicals and pharmaceuticals. Specialty chemicals of high-value per unit product are usually manufactured by batch processes. Solution crystallization is a major industrial process for formulation of particulate products with an aim to meet product specifications such as narrow crystal size distribution (CSD), high yield, crystal purity, and desired crystal morphology. To meet these specifications, a detailed knowledge of the dynamics of the batch process system and the properties of the crystalline material are required. Difficulty in realizing a reproducible crystallization process remains a fundamental and practical challenge for the production of a wide range of specialty materials, particularly, organic solids. In crystallization processes, supersaturation is the driving force for nucleation and crystal growth. There are four main methods by which supersaturation can be generated;1 these include changing solution temperature (cooling crystallization), evaporation of solvent (evaporative crystallization), chemical reactions (reactive crystallization/precipitation), and changing the solvent composition (antisolvent crystallization). The solubility characteristics of a solute in a given solvent have a considerable influence on the choice of a crystallization method.2 In crystallization, small changes in process conditions, such as temperature, cooling rate, or crystallizer hydrodynamics/mixing, can result in a significant variation in the level of supersaturation * Corresponding author. Tel: +44 (0) 113 343 2431. Fax: +44 (0) 113 343 2405. E-mail: [email protected]. † The University of Leeds. ‡ Clairet Scientific Limited. § The University of Newcastle.

which in turn affects the crystal properties (such as polymorphic form, particle size, shape, purity, and defect structure). For example, a certain level of supersaturation may be required to produce particles of a particular CSD and habit. However, if the supersaturation exceeds that value then this can lead to small crystals of different habit,3 which might be difficult to filter, dry, and package. The application of in-process analytical techniques can play a vital role in monitoring and controlling crystallization processes. There are various online techniques for obtaining solute concentration in crystallizers,4 which include measurements of the refractive index,5 density of the liquid phase in slurry,6 and conductivity of electrolyte solution.7 Reliable online measurement of solution concentration is a prerequisite for the control of supersaturation in crystallization processes. However, accurate concentration measurement in the dense slurry of a crystallizer is difficult. One technique, which offers good potential for the in situ measurement of solute concentration, particularly in organic systems, is attenuated total reflection (ATR) Fourier transform infrared (FTIR) spectroscopy (see review in ref 8). For over a decade or more, there have been a number of applications of ATR-FTIR spectroscopy for in situ measurement of solution concentration in spontaneous3,4,8-23 and seeded11,14,17,19,21,23-26 batch cooling crystallization, antisolvent crystallization13,23,27 and reactive precipitation28-30 of mainly organic and, to a much lesser extent, inorganic compounds. Measurements of solubility4,8-25,27,28 and metastable zone width (MSZW),10-12,15,17,18,22,24 and monitoring of solution concentration and supersaturation3,4,8,10-18,20-24,26-30 during crystallization of organic (such as 4-acetamidophenol (paracetamol), benzophenone, citric acid, 1-dimethylurea (IPU) (isoproturon), glycine, L-glutamic acid, maleic acid, nicotinic acid and sulpathiazole) and proprietary pharmaceutical compounds have been performed using ATR-FTIR spectroscopy. These studies

10.1021/cg7010265 CCC: $40.75  2009 American Chemical Society Published on Web 12/29/2008

In Situ Measurement of Solution Concentration

Crystal Growth & Design, Vol. 9, No. 2, 2009 693 Scheme 1. 32

Table 1. Experimental Matrix for FTIR Calibration Data Collection at Different LGA Concentrations and Temperatures ([ ] Validation Data) LGA concentration [g/L] 3 6 9 12 15 20 24 27 30 36 45 54 62.5 solubility data [g/L]

Figure 1. Microscopic images of two polymorphic forms of LGA.

have demonstrated that this technique can be successfully employed for in situ measurements of solute concentration in slurries during crystallization. Online concentration measurement with ATR-FTIR spectroscopy has also been used for feedback and proportional control of supersaturation in cooling and antisolvent crystallization of organic materials including pharmaceutical compounds.3,17,19,23-25 In previous applications of ATR-FTIR spectroscopy, various calibration methods have been used for directly relating the infrared (IR) spectra to the analyte concentration. These include the methods based on the height of the absorbance peak of the analyte or area under the peak at a specific wavenumber ratioed against a water band3,9-12,14,15,18,21,25-27,30 and more advanced chemometric methods, such as partial least squares (PLS)16,17,20,22,28,29 and principal component regression (PCR),4,13,19,23,24 using multiple absorbances from the analyte in a range of wavelengths. The disadvantage of using the peakratio method is that the shift of peak often occurs during measurements reflecting concentration, temperature, pH variations, which may result an error in the concentration prediction, whereas in a chemometric approach the inclusion within the model of multiple absorbances averages the measurement noise and allows for the explicit consideration of peak shifts.4 The study reported in this paper is concerned with the application of ATR-FTIR spectroscopy for the online measure-

temperature [°C] 40 40 40 40 40

15.1

50 50 50 50 50 [50]

21.9

60 60 [60] 60 [60] 60 [60] 60 60 60

31.7

70 [70] 70 70 [70] 70 70 70 [70] 70 70 [70]

45.9

80 80 [80] 80 80 80 80 [80] 80 80 [80] 80 80 66.6

90 90 90 [90] 90 90 90 90 90 90 90 96.6

ments of solute concentration in batch cooling crystallization of an organic substance. The work was carried out as part of a multitask research project (Chemicals BehaVing Badly, www. leeds.ac.uk/chemeng/CBB/cbb2.html) shaped by the industry reflecting the need for developing effective methods for the online measurement and control of batch cooling crystallization processes. The work reported here follows an earlier application3 of the ATR-FTIR spectroscopy coupled with a peak-ratio calibration model for in situ measurement and closed-loop supersaturation control in batch cooling crystallization of monosodium glutamate, a concentrated analyte. In the present study, the crystallization of L-glutamic acid (LGA) from aqueous solution is used as a model system. This is a challenging compound for the application of ATR-FTIR spectroscopy due to its low sensitivity to LGA solutions in the mid-IR frequency range and low solubility in water and complex speciation chemistry.30-32 Previous studies33 had attempted to calibrate LGA spectra using a univariate peak-ratio method but the IR spectral features were not found to be very strong, and this, coupled with the material’s low aqueous solubility, did not lead to success. Hence, this specific system was chosen for the challenge it provides; that is, if a working multivariate chemometric calibration model can be developed and applied for LGA, then this will facilitate its application to a wide range of other, notably industrial, systems. There have been very limited applications of ATR-FTIR spectroscopy for measurements of solute concentration during the crystallization of LGA. These studies include monitoring of solvent-mediated polymorphic transformation of LGA21 and precipitation via acidification of monosodium glutamate.30 It should be noted that in these studies the peak-ratio method was used for the calibration of absorbance spectra. It appears that there is no published work on the calibration of ATR-FTIR spectra using chemometric approaches for this important representative system. In the present study, batch cooling crystallization of LGA from aqueous solutions is carried out in stirred tank crystallizers

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at two scale sizes (500 mL and 20 L). For online monitoring of LGA concentration using ATR-FTIR spectroscopy, a PLS chemometric calibration model has been developed in order to relate the mid-IR spectra to the analyte concentration. The solubility data of LGA in water over a defined temperature range was determined using ATR-FTIR spectroscopy and compared against those obtained directly via gravimetric analysis from the slurry samples in equilibrium at different temperatures and with those reported in the literature. Measurement of the MSZW as a function of both cooling rate and solution concentration was used to determine the boundary of the metastable zone barrier to spontaneous crystallization allowing the operating conditions for both spontaneous and seeded crystallization to be defined. ATR-FTIR spectroscopy together with associated instruments was used to monitor online the LGA concentration in spontaneous and seeded crystallization in both the crystallizer scale sizes. Materials and Methods Materials. LGA (chemical formula: C5H9NO4, molecular weight: 147.13 g/mol) is an R-amino acid with three functional groups for protonation/deprotonation, that is, two carboxylic acid groups and one basic amine group as shown in Scheme 1.30-32 In aqueous solutions, the molecule dissociates to yield four species according to the following protonation reactions:30

Borissova et al.

RH+1 a RH + H+ -1

+

RH a RH + H -2

+

RH a RH + H -1

(R1) (R2) (R3)

where RH-2 and RH-1 are the deprotonated forms of LGA, RH is the neutral zwitterion, and RH+1 is the fully protonated form with an overall charge of +1. The concentrations of these four species depend on the solution pH: below 2.2, mainly in the fully protonated form; between 2.2 and 4.6, mainly the zwitterion, that is, with one negative and one positive charge, with an overall charge of 0 although close to 2.2 the amount of RH+1 is still relatively high; close to 4.6 relatively high level of RH-1. The isoelectric point, that is, where the species has an overall zero charge, comprising the zwitterion with equal but smaller amounts of the +1 and -1 forms, is at pH 3.37. LGA has two well-defined polymorphic forms involving different molecular conformations and yielding different crystal morphologies: the metastable, more soluble, and prismatic R-form and the stable, less soluble, and needle like β-form, as shown in Figure 1. This study focuses on the latter form, samples of which were obtained from VWR International (BDH) in powder form (stated purity 99%). Experimental Set-up and General Procedures. Experiments were carried out in HEL (Hazard Evaluation Laboratory Ltd.) AUTOLAB reactor systems which consisted of 500 mL and 20 L jacketed glass crystallizers with the temperature maintained and controlled using Julabo FP50-HD and Huber Unistat 141 thermostatic baths, respectively, a data interface board (A/D), and a PC running with HEL WinISO (version 2.2.30.3) process control software. The LGA solution was stirred at a defined rate using a stainless steel pitched blade impeller in

Figure 2. (a). Schematic of the crystallizer with associated instrumentations. (b) Photographs of the experimental facilities.

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Figure 3. ATR-FTIR spectra of LGA solutions for different concentrations at 80 °C. the 500 mL crystallizer and a PTFE retreat curve impeller in the 20 L. A platinum resistance thermometer (PT100), an in-house-built3 turbidimetric fiber-optic probe and a glass pH electrode were used to measure temperature, turbidity (to detect the onset of crystallization) and pH, respectively, with signals logged by the control PC. For in situ measurements of solution concentration, mid-IR spectra were taken using an ABB Bomem WorkIR FTIR spectrometer coupled to a Dipper210 ATR immersion probe equipped with a ZnSe conical internal reflection element manufactured by Axiom Analytical Inc. The spectrometer was connected to a PC equipped with Grams software (Galactic Industries Corp.) and EnablIR FTSW100 software (ABB) was used to effect real-time analysis and control. A reflux condenser was provided to prevent solvent loss due to evaporation. The overall experimental facility is shown schematically in Figure 2a and by pictorial representation in Figure 2b. Before an experiment was carried out, the crystallizer was cleaned and washed thoroughly with distilled water in order to ensure that there were no particles or residues left in the vessel from the previous experiment. All the probes were also washed with distilled water. Solutions were prepared by dissolving appropriate amounts of β-form LGA in distilled water. A high resolution analytical balance (MettlerToledo Ltd.) with an accuracy of up to four decimal places was used to weigh the powder samples. The spectrometer, conduits, and ATR probe were purged continuously with dry nitrogen (oxygen free)/air (water vapor free) starting 24 h before and during the measurement in order to minimize the effect of carbon dioxide and water vapor absorption in its optical path. The background spectrum for the ATR probe was chosen to be recorded with the ATR probe in air at room temperature. It is possible that the thermal expansion of the optics in contact with the hot sample and the difference between the refractive index of air and sample can slightly increase the optical path between the background and sample measurements. However, these effects were found to be small and can be expected to make no difference to the predicted concentration. If the solvent (liquid water) was used as the background, there is a high probability of solvent band miscancelation problems as the liquid bands can be affected by both temperature and ionic strength (usually due to intermolecular hydrogen bonding). This can give rise to large “differential” shaped bands, which often obscure the region of interest. FTIR Calibration and Data Modeling Procedures. A multivariate chemometric PLS calibration model was developed for the prediction of LGA concentration from in situ online measurements of IR spectra. The spectral data was used to build a calibration model, and an outline of the modeling procedure and validation of the model are described here with a more detailed review of the PLS multivariate methodology being provided as Supporting Information.

For the experimental conditions given in Table 1, a total of 202 spectra were collected, which were divided into two sets: the calibration data set and the validation data set. The calibration data (also referred to as the training data) was used to build the model, which included 168 spectra, while the validation data included 34 spectra and was used for model validation. This approach gives, in principle, the best model performance since none of the spectra in the validation data set was used to build the model. The PLS calibration model was developed using PLSplusIQ software34 in which mean centring and the baseline corrections were used in the model development and refinement. Two methods of baseline correction were tested: an automatic baseline correction and a method based on the second derivative of the spectra. Two criteria for the model selection were applied to the calibration data set: coefficient of correlation (R2) and the standard error of prediction (SEP). The coefficient of correlation is given by n

R2 )

∑ (Cp - Cj )2 i

i)1 n

(1)

∑ (Ci - Cj )

2

i)1

The SEP is expressed as

SEP )



n

∑ (Ci - Cp )2 i

i)1

n

(2)

where n is the number of samples in the training data set, Cp is the matrix of predicted sample concentrations from the model, and C is the matrix of known concentrations of the samples. The SEP is a measure of how well the model predicts a validation data set that was not used in the construction of the original model. All experiments for the collection of spectral data for calibration of the ATR-FTIR spectrometer were carried out using the 500 mL crystallizer at a stirrer speed of 200 rpm. The calibration matrix, given in Table 1, comprises 45 conditions, with each condition corresponding to different concentrations and temperatures for which separate sample solutions of β-form LGA were prepared and the ATR-FTIR spectra were taken. A number of spectra were taken for each experimental condition, with each spectrum consisting of 64 scans at a spectral resolution of 8 cm-1. The calibration conditions span the following concentration and temperature ranges: 3.0-62.5 g/L (0.02-0.42 M)

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Figure 4. ATR-FTIR spectra of LGA solutions of 12.5 g/L concentration at different temperatures.

Figure 5. Calibration results based on the five-factor PLS model. and 40-90 °C. The spectral range used in building the PLS chemometric model was 2000-1000 cm-1. Before collecting the spectra, the required amount of LGA crystals was dissolved in distilled water and the solution temperature was stabilized. The solution pH was also recorded, which varied between 2.5 and 4.8 for the present calibration data set (see Table 1). Within this pH range the amount of zwitterion is dominant. In a previous study,30 the measured IR spectra showing characteristic bands associated with different functional groups of the LGA molecule at various pH values revealed that the characteristic bands at wavenumbers 1560 and 1404 cm-1 corresponding to the asymmetric and symmetric carboxylate ion stretching vibrations, respectively, were dominant for pH values between 2.5 and 4.2. Determination of Solubility. For further validation of the PLS calibration model, measurements of solubility of β-form LGA at different temperatures were carried out in the 500 mL crystallizer at a constant stirring rate of 300 rpm. The solubility curve of LGA in distilled water over a temperature range from 40 to 80 °C was determined by collecting IR spectra in LGA slurries at equilibrium at five different temperatures with the ATR-FTIR spectrometer and by analyzing slurry samples using the gravimetric (weighing) method. In these measurements, the temperature range was divided into two: 40-60 °C and 70-80 °C. For the first temperature range, a slurry of 17 g of LGA (which is more than that needed to make a saturated solution at 60 °C) in 500 mL of distilled water was prepared. LGA crystals were stirred in distilled water at 40 °C for about 2 h to ensure that equilibrium was reached. Five spectra (64 scans/spectrum) were taken and two

samples from the slurry were collected. Then the slurry temperature was increased by 10 °C and the procedure was repeated for 50 and 60 °C. For the second temperature range, a fresh solution was prepared and the same procedure was followed. The PLS calibration model (see Supporting Information) was used to predict the LGA concentrations from the measured ATR-FTIR spectra. As a cross-check the solute concentrations in the slurry samples were also determined by the gravimetric analysis. This involved filtration of 3-5 mL slurry samples taken from the crystallizer to separate out undissolved crystals using Millipore filter (pore size of 0.22 µm), evaporation of water from the filtrate and drying the solid residue (i.e., LGA crystals) for 24 h and finally weighing. The average concentration of two samples for each temperature was recorded. The average difference between the measured concentrations of two slurry samples using this method was 0.64%. Determination of MSZW. The MSZWs of LGA solutions of initial concentration of 21.9 g/L (corresponding saturation temperature of 50 °C), 31.7 g/L (60 °C), 45.9 g/L (70 °C), and 62.5 g/L (78.9 °C) were determined at four cooling rates using the turbidimetric fiber-optic probe3 in the 500 mL crystallizer at a constant stirring rate of 300 rpm. The onset of crystallization and dissolution of all crystals is indicated by the probe based on the reduction or enhancement in light transmitted because of the presence or absence of crystals in the solution. The turbidity probe output signal (transmittance) was calibrated between 100% for the clear solution and 0% for the cloudy solution (i.e., slurry).18 Initially, the temperature of the solution was set to 20 °C for 10 min. The solution was then heated to 90 °C at a particular heating rate and the temperature was held constant for 60 min to ensure that all crystals dissolved. The solution was cooled down to 35 °C at the same rate as that of the heating and kept at this temperature for 60 min. The solution was heated again to dissolve all crystals following the same procedure as for the heating cycle. The procedure was repeated for four different heating/cooling rates: 0.1, 0.25, 0.5 and 0.75 °C/min, and for solutions with different initial concentrations. Freshly prepared β-form LGA solution was used for each experimental run. Crystallization Procedure. The ATR-FTIR spectrometer coupled with the PLS calibration model was applied to monitor online the concentration of LGA solutions in batch cooling crystallization runs in the 500 mL and 20 L crystallizers. In all experiments, the β-form LGA solution with an initial concentration of 62.5 g/L, corresponding saturation temperature of 78.9 °C, was heated rapidly from room temperature to 90 °C, and the temperature was held constant for about an hour to dissolve all crystals. The solution was then cooled down to 40 °C at prespecified cooling rates. Both unseeded (spontaneous nucleation) and seeded experiments were carried out. In a typical seeded

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Figure 6. Calibration results for Factor Weights (a) four factors, (b) five factors, and (c) six factors.

Figure 7. Comparison between the PLS model predicted concentrations and the validation data (see Table 1). Table 2. PLS Model Error Analysis

|∆C| [g/L] % error

minimum

maximum

average

std dev

0.07 0.35

6.31 16.61

1.67 6.90

1.82 4.79

crystallization run, a certain amount of dry β-form LGA seed crystals, which were 1% and 5% of the feed used to prepare the solution, were added to the solution when the temperature reached a predetermined level within the metastable zone during the cooling stage. The seeds were obtained from the same batch of LGA as used for the preparation of the solution. The absorbance spectra were recorded continuously during the cooling of the solution and the corresponding LGA concentrations were predicted using the PLS model. Seeded crystallization experiments were carried out in both 500 mL and 20 L crystallizers at different cooling rates and using different amounts of dry seed crystals of β-form LGA to monitor the variation of solution concentration and supersaturation using ATR-FTIR spectroscopy. The conditions used in the experiments are given in Table 3. Experiments in the 500 mL crystallizer were performed at an impeller speed of 300 rpm (with corresponding impeller tip velocity of 0.848 m/s and Reynolds number of 16539) while in the 20 L crystallizer at 100 rpm (with a tip velocity of 0.942 m/s and Reynolds number of 61256). These were pragmatic choice of the impeller speeds, as maintaining the same Reynolds number for both scale sizes was not practical. For example, scaling up 300 rpm in a 500 mL vessel to 20 L for the same Reynolds number (16539) would need an agitation rate of ca. 30 rpm which would not be sufficient for good solid/liquid mixing, that is, to keep the crystal mass suspended. Similarly, scaling

down from 100 rpm in 20 L to 500 mL at the same Reynolds number (61256) would yield ca. 1100 rpm, a rate which would lead to an unacceptable degree of vortex formation. These constraints precluded the application of usual scale-up rules to set the impeller speed in the 20 L crystallizer. Therefore, the experiments conducted in these two scale sizes should not be viewed strictly as a scaling up exercise rather than seeking to emphasize the applicability of ATR-FTIR spectroscopy together with the calibration model developed for monitoring the crystallization processes at different scale sizes. During the experiments, the solution and jacket fluid temperatures, solute concentration (C), turbidity and pH of the solution, equilibrium concentration (C*) obtained using the solubility data, and supersaturation ratio, defined as S ) C/C*, were monitored.

Results and Discussion ATR-FTIR Calibration Model. 1. ATR-FTIR Spectral Data. Typical absorbance spectra collected for different LGA solution concentrations ranging between 15-54 g/L at a constant temperature of 80 °C and for different temperatures ranging between 50-80 °C at a constant solution concentration of 12.5 g/L are shown in Figures 3 and 4, respectively. The peaks at the wavenumber 1400 cm-1 are associated with LGA zwitterions (carboxylate ion stretching band). As can be seen in the figures, the absorbance increases with increasing solution concentration at a constant temperature, but the effect of temperature variation is very small.

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Table 3. Conditions for LGA Seeded Crystallization Experiments β-form LGA seeds

initial solution concentration [g/L] run no.

crystallizer size [L]

actual

preda

saturation temperature [°C]

cooling rate [°C/min]

amount [%]

size [µm]

seed addition temp [°C]

1 2 3

0.5 0.5 20.0

62.5 62.5 62.5

58.56 56.97 58.67

78.9 78.9 78.9

0.3 0.3 0.3

5 1 5

132 132 132

77.0 76.0 77.9

a

pred ) predicted concentration using the PLS calibration model.

Figure 8. Comparisons of β-form LGA solubility data obtained from ATR-FTIR spectra, slurry samples in 500 mL crystallizer and reported in the literature.35,36

Figure 9. Profiles of solution and crystallizer jacket temperatures and turbidity probe signal (transmittance) during heating/cooling cycle at 0.75 °C/min in 500 mL crystallizer.

2. Calibration Modeling. The best predictability of the PLS model was obtained by using the second derivative baseline correction method and SEP as a criterion for the selection of the number of factors (for details, see Supporting Information) in the model. Figure 5 shows the model predictions - link between the actual and the predicted concentrations. The model selected was based on five factors. The coefficient of correlation, R2, for the five-factor model was 0.943. The selection of factors was made using the factor weights (see Figure 6). The sensitivity of the model at the wavenumber 1400 cm-1 (the characteristic

wavenumber for LGA) was highest with the five-factor model. It also showed the smallest noise level at this wavelength. The results of the self-prediction of the model revealed that the error of prediction was in the range 1-10%. 3. PLS Model Validation. Figure 7 shows the model validation results, the comparison between the five-factor PLS model predicted concentrations using the measured 34 ATRFTIR spectra of the validation data set (see Table 1 for experimental conditions) and the actual sample concentrations. The model validation results reveal good quality predictions.

In Situ Measurement of Solution Concentration

The results are summarized in Table 2, which gives the difference between the actual and predicted concentrations, |∆C|, percentage error, and the standard deviation. The standard deviations of the |∆C| and percentage error are 1.82 and 4.79%, respectively. Determination of Solubility. The solubility data of β-form LGA determined from the measured ATR-FTIR spectra via the PLS calibration model is compared with that obtained by the gravimetric method in Figure 8. As can be seen, the LGA concentrations obtained using these two methods are in good agreement. The average difference between the measured and PLS model predicted concentrations was ca. 5%. The solubility data of LGA within the temperature range of 5.5 to 90 °C reported in the literature35,36 is also plotted in Figure 8. All four solubility data sets were fitted to a fourth-order polynomial with a R2 value of 0.999:

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C * ) 4.408 - 0.146T + 0.018T 2 - 2.964 × 10-4T 3 + 2.682 × 10-6T 4 (3) where C* is the equilibrium saturation concentration in [g/L] and Tis the solution temperature in [°C]. As revealed in the figure, the present data sets are in general good agreement with the literature values. However, discrepancies were found to exist at the high temperatures (g70 °C) where the PLS model predicted concentrations are lower than the literature values by 6%. Similar results have been reported in a recent study21 which reports discrepancies as high as 7.7% between the solubility data obtained using ATR-FTIR spectroscopy and from the literature. Overall, the present validation study demonstrates that the ATR-FTIR spectrometer together with the PLS calibration model can be used reliably for in situ concentration measurement of a dilute analyte.

Figure 10. Variation of turbidity probe response with solution temperature (experimental conditions are the same as in Figure 9).

Figure 11. Crystallization temperature at different cooling rates for LGA solutions saturated at 50, 60, 70, and 78.9 °C in 500 mL crystallizer.

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Figure 12. The R- and β-form LGA solubility and supersolubility curves showing the MSZW as a function of solution concentration and cooling rates 9 0.1 °C/min, ( 0.25 °C/min, O 0.35 °C/min, 2 0.5 °C/min, and b 0.75 °C/min.

Figure 13. Plot of logarithm of cooling rate, b, versus logarithm of maximum possible undercooling, ∆Tmax, giving the apparent order of nucleation (m ) 3.20, 2.21, 2.31, and 1.51) and the corresponding nucleation rate constant (kn ) 3.7 × 10-6, 1.5 × 10-4, 1.8 × 10-4, and 2.3 × 10-3 (g/L)1-m/min) for solutions saturated at 50, 60, 70, and 78.9 °C.

Figure 14. (a) Clean ATR-FTIR probe and (b) fouled probe in an unseeded crystallization run with 1 °C/min cooling rate at 78.9 °C saturation temperature.

Determination of Metastable Zone and Its Inter-relationship with Final Product Form. Figure 9shows typical time profiles of the solution temperature, the crystallizer jacket fluid temperature and the turbidity probe output signal at a heating/

cooling rate of 0.75 °C/min for an LGA solution with an initial concentration of 62.5 g/L corresponding to a saturation temperature of 78.9 °C. The temperatures for the onset of crystallization (i.e., nucleation) and dissolution of crystals (i.e., saturation temperature) can be determined by plotting the response of the turbidity probe against the solution temperature. These temperatures were taken when the solution transmittance started to drop/rise as recorded by the turbidity probe. The experimental results presented in Figure 9 are replotted in Figure 10 to show the variation of the turbidity probe response with the solution temperature revealing the points of nucleation and crystal dissolution. The difference between the saturation temperature, Tsat, and the crystallization temperature, Tcry, is taken as the MSZW in terms of ∆T as

∆T ) Tsat-Tcry

(4)

The variations of crystallization temperature as a function of cooling rate for LGA solutions saturated at 50.0, 60.0, 70.0,

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Figure 15. PLS model predicted LGA concentration and solution temperature during an unseeded crystallization run at 0.1 °C/min cooling rate in 20 L crystallizer showing predicted negative concentration reflecting probe encrustation effect.

Figure 16. ATR-FTIR spectra taken during unseeded crystallization run at 1 °C/min cooling rate in 500 mL crystallizer.

and 78.9 °C are shown in Figure 11. As can be seen, the crystallization temperature decreases with increasing cooling rate resulting in an apparently wider MSZW, essentially the crystallization temperature is reduced due to a slower nucleation/ growth rate with respect to the rate of supersaturation generation due to solution cooling. The MSZW in general decreases with increasing saturation temperature (see Figure 12) implying that nucleation of LGA from an aqueous solution at a higher concentration can be achieved relatively easily compared with a lower concentration due to the presence of more solute molecules in the solution, which results in the potential for solute/solute interactions. Figure 11 also indicates the crystallographic forms produced at different cooling rates and initial concentrations, which have been identified from optical micro-

scopic analysis of the product crystals. It should be noted that the polymorphic form associated with all the data points has not been identified, as some of the experiments involved crystallization/dissolution cycling where samples removal would be expected to impact solution concentration and hence affect the accuracy of measurement of dissolution temperature. The data provided in Figure 11 reveal, as expected, and what is wellknown, that the R-form crystallizes at the faster solution cooling rates with the stable β-form only crystallizing under slower cooling conditions. It is particularly interesting to note the linearity of the data in Figure 11, which is not really consistent with the behavior of a system crystallizing in different polymorphic forms. An alternative explanation for this could be that the metastable

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Figure 17. Results of seeded crystallization experiments at 0.3 °C/min cooling rate with 5% seed in (a) 500 mL crystallizer (Run #1) and (b) 20 L crystallizer (Run #3).

R-form always crystallizes first, following which, and depending on temperature, it undergoes a solvent-mediated phase transformation to the stable β-form. This hypothesis can be further developed by considering the two extremes of the saturation temperature range examined (Tsat ) 78.5 and 50 °C) for the slowest cooling rate (0.1 °C/min). The respective crystallization temperatures are 70.1 and 20.2 °C from which the expected R to β transformation rates can be calculated by making use of recently published in situ slurry XRD data.37 This analysis reveals conversion times of 29 and 380 min, respectively, which are substantially shorter than the time to sample product crystals supporting the proposition. This model is attractive as it has also close synergy with molecular cluster modeling studies by our group,38 which reveal the polymorphic stability of LGA to be size-dependent with the smaller cluster sizes, typical of higher supersaturation, favoring the R-form and vice versa. Hence, one can use this data to calibrate the above model and propose that for the lowest supersaturation (Tsat ) 50 °C at 0.1 °C/min cooling rate) studied here of S ) 2.4 defines a lower boundary for R phase formation. Clearly further studies at lower cooling rates and saturation temperatures would be needed to define

the critical supersaturation associated with the formation of the R- or β-form as the primary nucleating species. The crystallization temperatures at different cooling rates for solutions with different initial concentrations together with the R- and β-form LGA solubility data are given in Figure 12. The solubility data of R-form was obtained from ref 39 while the β-form was from eq 3. The LGA solubility and supersolubility curves, shown in Figure 12, reveal the MSZW as functions of cooling rates and solution concentration. This figure allows us to determine the operating range of the crystallizer. The Nyvlt40 analysis of the data, that is, using a plot of logarithm of cooling rate, b, against logarithm of ∆Tmax (maximum possible undercooling) based on saturation temperatures for R-form LGA, is shown in Figure 13. The parameters of the nucleation rate expression in terms of mass of nuclei (B ) kn ∆C m) can be evaluated from such a plot, which yields a straight line with slope equal to the apparent order of nucleation, m, and the nucleation rate constant, kn, can be determined from the intercept. This analysis reveals nucleation orders in the range 1.5-3.2 and rate constants in the range 3.7 × 10-6 to 2.3 × 10-3 (g/L)1-m/min.

In Situ Measurement of Solution Concentration

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suggested that nucleation may occur initially on the solid surface rather than in the solution.41 While previous studies have shown that ATR-FTIR probe encrustation and associated loss of measurement accuracy can be remedied by repeated mechanical cleaning of the ATR crystal during crystallization,21 this approach would clearly not be a practical option for real-time measurements. Various crystallization conditions were investigated in order to avoid the encrustation of the probe in the 500 mL crystallizer. These included LGA solutions with lower saturation temperatures of 50 and 60 °C, cooling rates as low as 0.05 °C/min, insertion of the FTIR probe into the solution after the onset of crystallization as indicated by the turbidity probe, seeding the solution at a certain temperature within the metastable zone, and heating the FTIR probe with a heating tape to prevent nucleation on its cold surfaces. These studies revealed that only seeding the solution prevented the encrustation of the probe. Further experiments were carried out to establish the maximum cooling rate and the amount of seeds needed to resolve this problem. Through seeding the possibility of crystal growth is enhanced early in the metastable zone and, as a consequence, the risk of excessive spontaneous nucleation is reduced.42 It should be noted that seeding in batch cooling crystallization is routinely carried out in industry with one of the accepted advantages of this technique being avoiding encrustation due to spontaneous nucleation.43

Figure 18. Microscopic images of (a) dry β-form LGA seeds, (b) seeds in slurry at 77 °C, and (c) product crystals in the 500 mL crystallizer (Run #1).

Monitoring of Spontaneous Crystallization. A number of unseeded crystallization runs at different cooling rates were carried out in the 500 mL and 20 L crystallizers, but the ATRFTIR probe, including the ZnSe crystal at the probe tip, was found to become encrusted with LGA crystals due to nucleation on the probe surface, this even at a cooling rate as low as 0.1 °C/min. Figure 14 shows a clean and fouled probe before and after the onset of spontaneous crystallization at a cooling rate of 1 °C/min. As shown in Figure 15, the predictive ability of the PLS model was good up to the onset of crystallization, after which the accuracy of the predicted concentration deteriorated drastically due to the encrustation of the ATR crystal. This caused the ATR-FTIR spectra to shift upward, as shown in Figure 16, due to the increase in absorbance of IR by solid LGA crystals. In previous studies, encrustation on the surface of the stirrer and stirrer shaft41 and the ATR-FTIR probe21 was also observed during unseeded crystallization of LGA. It has been

Monitoring of Seeded Crystallization. The real-time variations of measured process-dependent parameters in crystallization experiments carried out in the 500 mL (Run #1) and 20 L (Run #3) crystallizers at a cooling rate of 0.3 °C/min with 5% seeds are shown in Figure 17. In order to avoid cluttering of the graphs, the turbidity and pH profiles are omitted from this figure. The solute concentration was also determined by the gravimetric method at different temperatures in Run #1. The PLS model was found to underpredict the initial concentration of the solution prior to seeding by about 6%, which is within the range of self-prediction error of the calibration model. As can be seen in Figure 17a, the PLS model predicted concentrations during the crystallization in 500 mL vessel are reasonably close to those obtained using the gravimetric method. In both crystallizers, at the point of seeding (77 °C in Run #1 and 77.9 °C in Run #3, which are 1.9 and 1.0 °C, respectively, below the saturation temperature), an abrupt change in the turbidity probe signal was observed and the solution concentration started to decrease. The supersaturation profiles shown in Figure 17 indicate that the applied cooling rate is sufficiently high to generate supersaturation up to a peak level of 1.16 in the 500 mL crystallizer and 1.43 in 20 L initially in the process. This is followed by desupersaturation at different rates, depending on the scale-size, as the crystallization progresses reflecting the consumption of the solute resulting from a sudden burst of fresh nuclei via secondary nucleation and the growth of the freshly generated solids as well as the seed crystals. This is evident from the observation of optical microscopic images of the seeds in slurry and the final product crystals for Run #1, as shown in Figure 18. A large number of fine particles in Figure 18c suggests that secondary nucleation is prevalent. The image of product crystals reveals the needle-like β-form LGA. However, it is interesting to note that bursts of fresh nuclei occurs at a higher supersaturation level in the 20 L crystallizer, which is expected to generate more nuclei and consequently faster desupersaturation compared with that observed in the 500 mL vessel.

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Figure 19. Results of Runs #1, 2, and 3 (see Table 2): (a) LGA concentration profiles with the measured MSZW in the 500 mL crystallizer (see Figure 12) and (b) supersaturation (S ) C/C*) profiles.

In the seeded crystallization process, fresh nuclei can be expected to be produced via different mechanisms of secondary nucleation.2,44 In a recent study45 of seeded batch cooling crystallization of a proprietary organic material monitored with ATR-FTIR spectroscopy and by analyzing particle samples collected at different stages of the process, the occurrence of a significant burst of nuclei has been observed leading to a rapid decay of the solute concentration and supersaturation. The authors have suggested two mechanisms of secondary nucleation, depending on the supersaturation level, namely: secondary surface nucleation after seeding, which fades away with the decay of supersaturation, and contact secondary nucleation throughout the cooling stage (see for details of these mechanisms in refs 2 and 44). However, it is difficult to ascertain from the experimental data the relative contributions of the two secondary nucleation and growth processes because of the complex interactions between them and, in this respect, further study is needed. The measured solute concentration and the corresponding supersaturation (S ) C/C*) profiles together with the solubility

and MSZW data in 500 mL crystallizer as a function of the solution temperature for the three crystallization runs (see Table 2) are shown in Figure 19. Figure 19a also reveals the variations of absolute supersaturation, defined as ∆C ) C - C*, with the progress of crystallization. The comparison between the concentration profiles for Run #1 and #2 in the 500 mL crystallizer shows the effect of the amount of seeds on the process. As can be seen in Run #1 with 5% seeds the concentration drops rapidly following the introduction of seeds and is lower than that in Run #2 with 1% seeds due to the enhanced secondary nucleation and crystal growth resulting from the availability of more particle surface area. The effect of the scale-size on the crystallization process can be discerned by comparing the analyte concentration and supersaturation profiles for Runs #1 and #3. As can be seen in Figure 19b, due to an early burst of nuclei via secondary nucleation (at about 180 min, see Figure 17) and subsequent growth of particles the level of supersaturation in the 500 mL crystallizer is lower compared with that in the 20 L crystallizer. The burst of secondary nuclei in a larger vessel occurs at 228

In Situ Measurement of Solution Concentration

min. This is believe to be due, primarily, to enhanced secondary nucleation at the smaller scale-size which is consistent with the case of spontaneously nucleated LGA in our previous work46 where the MSZW was found to be narrower for the smaller vessel size with the nucleation order and rate being higher for a stainless steel impeller, which enhances nucleation, compared with a Perspex impeller.41

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and all members of this academic/industrial team, notably industrial coordinator Leslie J. Ford, and Steve Caddick (Leeds), Robert B. Hammond (Leeds), Xiaojun Lai (Leeds), Ivan Marziano (Pfizer), Christopher J. Price (GSK) for helpful discussions. Supporting Information Available: A detailed review of the PLS multivariate methodology. This material is available free of charge via the Internet at http://pubs.acs.org.

Conclusions A PLS calibration model with a good predictive accuracy for in situ online measurement of analyte concentration using ATR-FTIR spectroscopy during crystallization of LGA from aqueous solutions has been developed. The solubility data of β-form LGA over a temperature range obtained using this technique shows good agreement with that measured from the slurry samples using a gravimetric method and the literature values. The crystallization temperatures of LGA solutions saturated at 50, 60, 70, and 78.9 °C were determined at different cooling rates. The MSZW was found to increase with increasing cooling rate while it deceases with increasing solution concentration. The observed crystallographic forms of the product crystals together with the linearity of crystallization temperature versus cooling rate data, as shown in Figure 11, supports the proposition that the metastable R-form crystallizes first which, depending on temperature, undergoes a solvent-mediated phase transformation to the stable β-form. LGA solution concentration was predicted using the PLS calibration model from measured ATR-FTIR spectra and the variation of supersaturation was monitored during spontaneous and seeded batch cooling crystallization runs in 500 mL and 20 L crystallizers. Severe encrustation on the ATR crystal at the tip of the FTIR probe occurred in unseeded crystallization resulting in the loss of predictive accuracy, rendering the application of this technique impractical for postnucleation LGA supersaturation control via online concentration measurements. However, in seeded crystallization, in the absence of probe fouling, good predictions of LGA concentration were obtained during the cooling and crystallization stages. The predicted solute concentration and the corresponding supersaturation profiles were sensitive to the variations of process conditions and crystallizer scale sizes. The present study has demonstrated that ATR-FTIR spectroscopy coupled with a multivariate chemometric calibration model can be used as an effective analytical technique for online measurement of concentration for a difficult analyte such as LGA. Further development of the calibration method described taking into account temperature dependency will be reported47 in a related paper. Subsequently, this in-process measurement system and chemometric model has been applied to closed-loop feedback control of crystallizer supersaturation not only at the 20 L size but also on an industrial scale through studies at the 250 L scale size.48,49 Acknowledgment. This work has been carried out as part of Chemicals BehaVing Badly Phase 2, a collaborative project funded by the UK Science and Engineering Research Council (EPSRC) together with support from an industrial consortium including ANSYS Europe Ltd, AstraZeneca, Bede Scientific Instruments Ltd, BNFL, Clairet Scientific Ltd, GlaxoSmithKline, HEL Ltd, Malvern Instruments, Pfizer and Syngenta. The academic partners are Leeds, Heriot-Watt, and Newcastle Universities. We gratefully acknowledge all these sponsors

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