**Real-Time Analysis to Evaluate Crystallization Processes**

João F.Cajaiba da Silva, Andréia P. M. da Silva and Rodrigo C. de Sena *Instituto de Química – Universidade Federal do Rio de Janeiro Brazil*

## **1. Introduction**

302 Crystallization – Science and Technology

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Crystallization is one of the most important unit operations employed by the pharmaceutical, microelectronics, food and fine chemicals industries for the production of solid products with high added value. This operation can be used as a method to perform separation and purification of crystalline compounds such as proteins, polymers, pharmaceuticals, inorganic salts, etc. (Févotte & Klein, 1995; Feng & Berglund, 2002; Mersmann, 2001; Lewiner et al., 2001; Mullin, 2001; Liotta & Sabesan, 2004; Joung et al., 2005; Pelberg et al., 2005; Derdour et al., 2011).

The experimental conditions used during a crystallization process may alter the physical properties of the final product such as its chemical purity, crystal size distribution and morphology. These properties can have impacts on the subsequent purification operations such as filtration, washing and drying, and can also alter the bioavailability of pharmaceuticals (Sabesan & Liotta, 2004). Polymorphism is another issue related to the crystallization process that has profound importance in the pharmaceutical industry because it can alter the kinetics of a crystal's solubilization and in some cases polymorphs present problems of toxicity (Fujiwara et al., 2005).

The challenges involved in controlling crystallization are significant, since the kinetic parameters of the process are strongly affected by several factors such as the presence of impurities (Gunawan et al., 2002; Ma et al., 1999; Rauls et al., 2000; Poddar, 2002), breaking of crystals (Kougoulos et al., 2005; Gahn & Mersmann, 1995) and clustering (Yu et al., 2005; Paulaime et al., 2003) among other effects that are difficult to characterize.

The identification and control of factors that affect the final quality of crystals are essential to ensure uniformity among different batches and to improve product quality. The development of more accurate and sensitive sensors for real-time analysis of crystallization must allow significant advances in monitoring, control and optimization of crystallization processes (Liotta & Sabesan, 2004).

The accuracy of off line methods for evaluating crystallization processes is strongly dependent on sampling. When the collected samples do not represent the whole, the errors introduced may cause a misinterpretation of the crystallization process. By using real-time analysis these types of errors can be greatly reduced. The possibility of performing in situ analysis of crystal size distribution, crystal shape, crystal habit, agglomeration and breakage

Real-Time Analysis to Evaluate Crystallization Processes 305

The metastable zone width is defined as the difference between saturation temperature and the temperature which is detected in the formation of the first crystals. This temperature difference is known as the maximum undercooling, Tmax. Figure 1 illustrates schematically the solubility curve and metastable zone boundary for a hypothetical case of a system

In batch cooling crystallizations for example, maintaining the solution concentration profile within the metastable zone and close to the solubility curve promotes crystal growth and helps to avoid secondary nucleation (Beckmann, 2000). In the case of industrial crystallizers as a general rule, the level of supersaturation is maintained at about half the metastable zone

**Temperature**

Metastable zone

Solubility curve

Undersaturated solution

Metastable limit

The supersaturation is the main requirement for crystallization to occur and its creation does not imply the immediate separation of the phases. In a supersaturated solution, part of the dissolved solute tends to reorganize again to form the solid phase. However, the formation of the solid phase (positive energy) implies the generation of an interface (energetically unfavourable). Therefore, for the formation of nuclei to occur within the solution, it is necessary that this barrier is overcome (Mullin, 2001; Ulrich & Strega, 2002; Giulietti, 2001).

The nucleation rate depends on the supersaturation. When the supersaturation is extremely high, the nucleus formation is a random process and difficult to reproduce. For this reason, whenever possible, this condition is avoided in industrial applications (Mullin, 2001).

cooled from an under saturated condition until the condition of supersaturation.

Supersaturated solution

Fig. 1. Solubility curve and metastable zone.

**1.3 Nucleation and crystal growth**

(Marciniak, 2002).

**Concentratio**

**n**

can indicate what changes should be made to the crystallization process parameters such as cooling and stirring rates and time for seeding. The optimization of these parameters allows crystals of the desired characteristics to be obtained (Yu et al., 2004).

This section is intended to give a brief overview of crystallization processes and the methods dedicated to monitor them in real-time. Additionally, a comparison between four in line methods to determine the onset of adipic acid crystallization was performed.

#### **1.1 Solubility and supersaturation**

The determination of the solubility of a solid in a specific solvent is a key step in the study of crystallization processes. The solubility curve is used as a benchmark to assess the degree of supersaturation and the metastable zone limits. The solubility or condition of saturation is determined experimentally by heating a suspension and observing the temperature at which the solid phase is completely dissolved. The cooling of a saturated solution results in a system that is not in thermodynamic equilibrium, a supersaturated solution (Mullin, 2001; Giulietti et al., 2001).

The supersaturation is the driving force for crystallization processes and can be defined as the difference between the chemical potential of a solute in a supersaturated solution and the chemical potential of the saturated solution. Supersaturation can be created by cooling, by adding an anti-solvent, by performing a chemical reaction that generates a product of lower solubility, by solvent evaporation, etc. Among the methods used to create supersaturation, cooling is the most used. The usage of this method is restricted to substances whose solubility changes significantly during a temperature variation. The expected properties of the solid material, as well as economic aspects, form the basis for making a decision about which method should be used to create supersaturation (Mullin, 2001; Giulietti et al., 2001).

The difference between the concentration of a compound in a supersaturated solution, c, and its concentration in a saturated solution, c\*, is known as absolute supersaturation and is expressed by equation 1.

$$
\Delta \mathbf{c} \equiv \mathbf{c} \cdot \mathbf{c}^\* \tag{1}
$$

When c is greater than 0, the system is supersaturated. Another important parameter is the supersaturation ratio, S, which is defined by equation 2. In this case the system is said to be supersaturated when S is greater than 1.

$$S = \frac{\mathcal{C}}{\mathcal{C}^\*} \tag{2}$$

#### **1.2 Metastable zone width**

Supersaturated solutions exhibit a metastable region, where despite the instability of the system, there is no separation of a solid phase. The determination of this region is, in general, the first phase in the design of a batch cooling crystallization process. The metastable zone width (MZW) is a property that depends on several characteristics of the system (cooling rate, solute concentration, stirring rate, thermal history of the solution, presence of impurities, etc.) (Liotta & Sabesan, 2004).

can indicate what changes should be made to the crystallization process parameters such as cooling and stirring rates and time for seeding. The optimization of these parameters allows

This section is intended to give a brief overview of crystallization processes and the methods dedicated to monitor them in real-time. Additionally, a comparison between four in line

The determination of the solubility of a solid in a specific solvent is a key step in the study of crystallization processes. The solubility curve is used as a benchmark to assess the degree of supersaturation and the metastable zone limits. The solubility or condition of saturation is determined experimentally by heating a suspension and observing the temperature at which the solid phase is completely dissolved. The cooling of a saturated solution results in a system that is not in thermodynamic equilibrium, a supersaturated solution (Mullin, 2001;

The supersaturation is the driving force for crystallization processes and can be defined as the difference between the chemical potential of a solute in a supersaturated solution and the chemical potential of the saturated solution. Supersaturation can be created by cooling, by adding an anti-solvent, by performing a chemical reaction that generates a product of lower solubility, by solvent evaporation, etc. Among the methods used to create supersaturation, cooling is the most used. The usage of this method is restricted to substances whose solubility changes significantly during a temperature variation. The expected properties of the solid material, as well as economic aspects, form the basis for making a decision about which method should be used to create supersaturation (Mullin,

The difference between the concentration of a compound in a supersaturated solution, c, and its concentration in a saturated solution, c\*, is known as absolute supersaturation and is

 c= c-c\* (1) When c is greater than 0, the system is supersaturated. Another important parameter is the supersaturation ratio, S, which is defined by equation 2. In this case the system is said to be

> \* *c S*

Supersaturated solutions exhibit a metastable region, where despite the instability of the system, there is no separation of a solid phase. The determination of this region is, in general, the first phase in the design of a batch cooling crystallization process. The metastable zone width (MZW) is a property that depends on several characteristics of the system (cooling rate, solute concentration, stirring rate, thermal history of the solution,

*c* (2)

crystals of the desired characteristics to be obtained (Yu et al., 2004).

**1.1 Solubility and supersaturation**

Giulietti et al., 2001).

2001; Giulietti et al., 2001).

expressed by equation 1.

**1.2 Metastable zone width**

supersaturated when S is greater than 1.

presence of impurities, etc.) (Liotta & Sabesan, 2004).

methods to determine the onset of adipic acid crystallization was performed.

The metastable zone width is defined as the difference between saturation temperature and the temperature which is detected in the formation of the first crystals. This temperature difference is known as the maximum undercooling, Tmax. Figure 1 illustrates schematically the solubility curve and metastable zone boundary for a hypothetical case of a system cooled from an under saturated condition until the condition of supersaturation.

**Temperature**

Fig. 1. Solubility curve and metastable zone.

In batch cooling crystallizations for example, maintaining the solution concentration profile within the metastable zone and close to the solubility curve promotes crystal growth and helps to avoid secondary nucleation (Beckmann, 2000). In the case of industrial crystallizers as a general rule, the level of supersaturation is maintained at about half the metastable zone (Marciniak, 2002).

## **1.3 Nucleation and crystal growth**

The supersaturation is the main requirement for crystallization to occur and its creation does not imply the immediate separation of the phases. In a supersaturated solution, part of the dissolved solute tends to reorganize again to form the solid phase. However, the formation of the solid phase (positive energy) implies the generation of an interface (energetically unfavourable). Therefore, for the formation of nuclei to occur within the solution, it is necessary that this barrier is overcome (Mullin, 2001; Ulrich & Strega, 2002; Giulietti, 2001).

The nucleation rate depends on the supersaturation. When the supersaturation is extremely high, the nucleus formation is a random process and difficult to reproduce. For this reason, whenever possible, this condition is avoided in industrial applications (Mullin, 2001).

Real-Time Analysis to Evaluate Crystallization Processes 307

The FBRM measurement principle is based on backward light scattering. A laser beam is coupled to a probe via an optical fibre. This laser beam is deviated from the probe's central axis and focused into a disperse medium with an optical conduit. When this laser beam intersects with a particle, light scattering occurs. A certain fraction of the light is scattered back into the system. This back scattered light is coupled via a beam splitter to a second fibre and conduced to a detector. The rotational velocity of the laser is constant. The time span in which back scattering is detected is therefore directly proportional to the path length of the laser on the particle. It is assumed that the particle velocity is small compared to the laser rotational velocity. The length of the laser path on the particle is therefore proportional to the time span in which scattering is detected. This path length is called a chord length. Depending on the laser position, different chord lengths are measured even for a single particle. Those chord lengths are generally different from any characteristic particle length. In order to calculate the particle size distribution from the chord length distribution, a model is needed. This model has to cover all relevant aspects of the measurement technology (Kail et al., 2008; Barrett & Glennon, 2002). Figure 2 presents a schematic view of

**1.4.2 Focused beam reflectance measurement (FBRM)**

Fig. 2. Measurement principles of the Lasentec FBRM probe.

Sheikhzadeh et al., 2008; Nguyen & Kim, 2008).

**1.4.3 Calorimetry**

Just as with the ATR-FTIR technique, the FBRM is a well-established method of monitoring crystallization processes (Sun et al., 2010; Barrett & Glennon, 2002; Czapla et al., 2010;

The principle of reaction calorimetry is based on the heat flow in processes involving changes in chemical or physical properties. The rate of release or absorption of heat is a parameter dependent on the kinetics and thermodynamics of the process under study (Gesthuisen et al., 2005; Mantel & Meyer, 2008). The combination of heat flow with the mass balance allows us to estimate the conversion of the instantaneous and cumulative process under study. Reaction calorimetry is non-invasive, fast, robust, relatively simple and its

the Mettler Toledo FBRM probe.

The crystal growth also depends on the supersaturation level. High growth rates lead to products with a degree of purity lower than those generated in conditions of lower supersaturation owing to the inclusion of liquids and other impurities. From the industrial point of view there is a compromise between the desired characteristics of the products and the economic efficiency of the process. This means that is not always possible to carry out crystallizations with a low rate of crystal growth because such a condition significantly increases the residence time of the product inside the crystallizer (Mullin, 2001; Ulrich & Strege, 2002).

## **1.4 Sensor technologies for monitoring crystallization processes**

Continuous monitoring and control of crystallization processes in real-time require the use of sensors able to provide information regarding product quality and critical process variables.

The methods used to assess information of the products obtained from crystallization processes can be divided into four main groups (Yu et al., 2004):

The real-time analyses described in this chapter can be included in the in line and the noninvasive methods.

## **1.4.1 Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR)**

ATR-FTIR is a consolidated technique in the monitoring of crystallization processes (Chen et al., 2009; Kadam et al., 2011; Pöllänen et al., 2006; Qu et al., 2009; Sheikhzadeh et al., 2008; Liotta & Sabesan, 2004). The method allows estimating the degree of supersaturation of the system by measuring the concentration of solute in the solution. The only prerequisite for application of the technique is the absorption of infrared radiation in the medium by the solute. The sensor used in this method has an element of internal reflection of high refractive index. The radiation passes through the element of reflection, being reflected when it encounters a material with lower refractive index. The amount of reflected radiation depends on the angle of incidence on the interface and when this angle is greater than a critical angle (depending on the ratio between the two refraction index) the refraction is attainable. However, radiation penetrates only a short distance into material of lower refractive index; this radiation is called the evanescent radiation (evanescent wave). Thus, if a sample is able to absorb infrared radiation, the beam is attenuated at frequencies absorbed by the sample (Man et al., 2010; Dunuwilaa et al., 1994).

The crystal growth also depends on the supersaturation level. High growth rates lead to products with a degree of purity lower than those generated in conditions of lower supersaturation owing to the inclusion of liquids and other impurities. From the industrial point of view there is a compromise between the desired characteristics of the products and the economic efficiency of the process. This means that is not always possible to carry out crystallizations with a low rate of crystal growth because such a condition significantly increases the residence time of the product inside the crystallizer (Mullin, 2001; Ulrich &

Continuous monitoring and control of crystallization processes in real-time require the use of sensors able to provide information regarding product quality and critical process

The methods used to assess information of the products obtained from crystallization

on line methods: the sample stream is diverted from the crystallizer for analysis and

 in line methods: sensors are integrated into the crystallizer and provide real-time information about the process. The sensors are in direct contact with the material and

 non-invasive methods: sensors are integrated into the crystallizer and provide real-time information of the process. In this case, the sensors do not come into direct contact with

The real-time analyses described in this chapter can be included in the in line and the non-

**1.4.1 Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR)**  ATR-FTIR is a consolidated technique in the monitoring of crystallization processes (Chen et al., 2009; Kadam et al., 2011; Pöllänen et al., 2006; Qu et al., 2009; Sheikhzadeh et al., 2008; Liotta & Sabesan, 2004). The method allows estimating the degree of supersaturation of the system by measuring the concentration of solute in the solution. The only prerequisite for application of the technique is the absorption of infrared radiation in the medium by the solute. The sensor used in this method has an element of internal reflection of high refractive index. The radiation passes through the element of reflection, being reflected when it encounters a material with lower refractive index. The amount of reflected radiation depends on the angle of incidence on the interface and when this angle is greater than a critical angle (depending on the ratio between the two refraction index) the refraction is attainable. However, radiation penetrates only a short distance into material of lower refractive index; this radiation is called the evanescent radiation (evanescent wave). Thus, if a sample is able to absorb infrared radiation, the beam is attenuated at frequencies absorbed

**1.4 Sensor technologies for monitoring crystallization processes**

processes can be divided into four main groups (Yu et al., 2004): off line methods: the analysis is performed after sampling;

subsequently returned to the system;

can cause disturbances in the system;

by the sample (Man et al., 2010; Dunuwilaa et al., 1994).

Strege, 2002).

variables.

the material.

invasive methods.

### **1.4.2 Focused beam reflectance measurement (FBRM)**

The FBRM measurement principle is based on backward light scattering. A laser beam is coupled to a probe via an optical fibre. This laser beam is deviated from the probe's central axis and focused into a disperse medium with an optical conduit. When this laser beam intersects with a particle, light scattering occurs. A certain fraction of the light is scattered back into the system. This back scattered light is coupled via a beam splitter to a second fibre and conduced to a detector. The rotational velocity of the laser is constant. The time span in which back scattering is detected is therefore directly proportional to the path length of the laser on the particle. It is assumed that the particle velocity is small compared to the laser rotational velocity. The length of the laser path on the particle is therefore proportional to the time span in which scattering is detected. This path length is called a chord length. Depending on the laser position, different chord lengths are measured even for a single particle. Those chord lengths are generally different from any characteristic particle length. In order to calculate the particle size distribution from the chord length distribution, a model is needed. This model has to cover all relevant aspects of the measurement technology (Kail et al., 2008; Barrett & Glennon, 2002). Figure 2 presents a schematic view of the Mettler Toledo FBRM probe.

Fig. 2. Measurement principles of the Lasentec FBRM probe.

Just as with the ATR-FTIR technique, the FBRM is a well-established method of monitoring crystallization processes (Sun et al., 2010; Barrett & Glennon, 2002; Czapla et al., 2010; Sheikhzadeh et al., 2008; Nguyen & Kim, 2008).

#### **1.4.3 Calorimetry**

The principle of reaction calorimetry is based on the heat flow in processes involving changes in chemical or physical properties. The rate of release or absorption of heat is a parameter dependent on the kinetics and thermodynamics of the process under study (Gesthuisen et al., 2005; Mantel & Meyer, 2008). The combination of heat flow with the mass balance allows us to estimate the conversion of the instantaneous and cumulative process under study. Reaction calorimetry is non-invasive, fast, robust, relatively simple and its

Real-Time Analysis to Evaluate Crystallization Processes 309

The solubility of adipic acid (99.8%) in ethanol (analytical grade) was determined for twelve different temperatures ranging from 16.0 to 64.0C. The experiments were performed in a 1.8-L Hastelloy jacketed reactor vessel connected to an RC1e reaction calorimeter. The solutions were prepared by successive additions of adipic acid to a solution containing ethanol at a stirring rate of 300 rpm. For measurements at 44.0C, the mass of ethanol used was 524.0g. The used mass for other temperatures are presented in Table 1. The

Temperature (K) Temperature (ºC) Ethanol mass (g) 289.15 16.0 590.3 293.95 20.8 582.7 298.15 25.0 574.7 303.95 30.8 564.3 306.15 33.0 556.3 308.25 35.1 550.8 312.15 39.0 537.0 317.15 44.0 524.0 323.15 50.0 492.4 330,15 57.0 459.5 334.15 61.0 428.1 337.15 64.0 405.3

Table 1. Experimental conditions for testing the solubility of the adipic acid in ethanol.

The ATR-FTIR measurements were performed by using a Mettler-Toledo ReactIR IC10 spectrometer. The base unit contains the Fourier transform mid-infrared source and the mercuric cadmium telluride (MCT) detector that should be cooled with liquid nitrogen. The sample interface module (SIM) is the interface on the instrument base unit where the K6 (16 mm diameter) conduit connects. It contains the optics that transfer the infrared source light from the base unit to the probe in contact with the chemical materials contained in the vessel and then back to the detector. Measurements are taken optically using a diamond sensing element that uses a multiple reflection ATR crystal and a gold seal between the metal housing and the sensor. Figure 3 illustrates schematically the K6

The focused beam reflectance measurements were obtained by using a Mettler-Toledo Lasentec D600L probe consisting of a Hastelloy C-22 tube with the sensor at one end with an optical diameter of 19 mm and a length of ∼406 mm. The FBRM laser provides a continuous beam of monochromatic light with a wavelength of 780 nm. The beam is located

The ATR-FTIR and FBRM probes were kept immersed in the adipic acid solution 5 cm above the propeller stirrer. Infrared spectra obtained from 4000 to 650 cm-1 at 4 wave numbers

resolution were collected at 15 s intervals with each spectrum averaged over 30 scans.

solubilization temperature was maintained constant during the whole process.

**2.1 Materials and methods**

Mettler Toledo probe tip.

approximately 3 mm to the focal point.

**2.2.1 Solubility**

principle is based on the measurement of temperature differences (Gesthuisen et al., 2005; Mantel & Meyer, 2008). From the industrial point of view, calorimetry is a technique of great importance because it allows safely scaling up a process from pilot to industrial scale (Gesthuisen et al., 2005). The method finds application in the study of polymerization reactions (Benamor et al., 2002; Elizalde et al., 2005), biotechnological processes (Marison et al., 1985), study of supercritical fluids (Lavanchy et al., 2004; Mantel & Meyer, 2008), optimization of chemical reactions (Barton et al., 2003) and determination of kinetic parameters of chemical reactions (Silva et al., 2003; Seiceira et al., 2005) among other applications. There are few articles where heat flow calorimetry is applied to the study of crystallization processes (Févotte & Klein, 1995)

### **1.4.4 Image analysis**

The use of Complementary Metal Oxide Semiconductor (CMOS) and Charge Coupled Device (CCD) cameras has been widely introduced in analytical chemistry for different reasons such as fast image capturing, stable background and good linearity (Jolling et al., 2007). These sensors are capable of converting the intensity of light that focuses on it in digital storable values as bits. The analytical response that generates an image representing the patterns of the colours Red (R), Green (G) and Blue (B). These patterns are known as RGB 8 bits for each channel, totalling 256 levels. The combination of the three matrices (R, G and B) allows the acquisition of 16 million colours (Gaiao et al., 2006; Safavi et al., 2007). Different methodologies employing this image analysis has been described in literature. A digital camera was used as a sensor for simultaneous determination of Al(III) and Fe(III) in alloys using the chrome azurol S(CAS) as chromogenic reagent (Maleki et al., 2004). An instrumental detection technique for titration based on digital images was proposed (Gaiao et al., 2006). A similar method for the measurement of lithium, calcium and sodium through the radiation emitted by the sample into an air-butane flame was developed (Lyra et al. (2009). Image analysis was also used for a real-time assessment of the coffee roasting process (Hernández et al., 2008). An approach employing a CCD camera as a sensor for recognizing volatile alcohols was described (Shirshov et al., 2007). A method based on external bulk video imaging was proposed for metastable zone identification in food and pharmaceutical crystallization processes, and showed good performance when compared to FBRM and ultra-violet visible spectroscopy (Simon et al., 2009). Additionally, CCD cameras have been used as detectors in clinical analysis and showed high detection sensitivity (Liang et al., 2004; Alexandre et al., 2001). The rapid improvements in digital camera technology provide the opportunity for the development of new methodologies employing digital cameras as an analytical sensor with high sensitivity, robustness, speed and low cost for implementation that reduces the analysis time.

### **2. Experimental part**

In this section batch cooling crystallization of adipic acid will be used as a model to demonstrate the use of in line and non-invasive techniques for monitoring crystallization. For this purpose, four analytical tools with different physical principles were used. The procedures and techniques used in the experiments are described in the following subsections.

## **2.1 Materials and methods**

## **2.2.1 Solubility**

308 Crystallization – Science and Technology

principle is based on the measurement of temperature differences (Gesthuisen et al., 2005; Mantel & Meyer, 2008). From the industrial point of view, calorimetry is a technique of great importance because it allows safely scaling up a process from pilot to industrial scale (Gesthuisen et al., 2005). The method finds application in the study of polymerization reactions (Benamor et al., 2002; Elizalde et al., 2005), biotechnological processes (Marison et al., 1985), study of supercritical fluids (Lavanchy et al., 2004; Mantel & Meyer, 2008), optimization of chemical reactions (Barton et al., 2003) and determination of kinetic parameters of chemical reactions (Silva et al., 2003; Seiceira et al., 2005) among other applications. There are few articles where heat flow calorimetry is applied to the study of

The use of Complementary Metal Oxide Semiconductor (CMOS) and Charge Coupled Device (CCD) cameras has been widely introduced in analytical chemistry for different reasons such as fast image capturing, stable background and good linearity (Jolling et al., 2007). These sensors are capable of converting the intensity of light that focuses on it in digital storable values as bits. The analytical response that generates an image representing the patterns of the colours Red (R), Green (G) and Blue (B). These patterns are known as RGB 8 bits for each channel, totalling 256 levels. The combination of the three matrices (R, G and B) allows the acquisition of 16 million colours (Gaiao et al., 2006; Safavi et al., 2007). Different methodologies employing this image analysis has been described in literature. A digital camera was used as a sensor for simultaneous determination of Al(III) and Fe(III) in alloys using the chrome azurol S(CAS) as chromogenic reagent (Maleki et al., 2004). An instrumental detection technique for titration based on digital images was proposed (Gaiao et al., 2006). A similar method for the measurement of lithium, calcium and sodium through the radiation emitted by the sample into an air-butane flame was developed (Lyra et al. (2009). Image analysis was also used for a real-time assessment of the coffee roasting process (Hernández et al., 2008). An approach employing a CCD camera as a sensor for recognizing volatile alcohols was described (Shirshov et al., 2007). A method based on external bulk video imaging was proposed for metastable zone identification in food and pharmaceutical crystallization processes, and showed good performance when compared to FBRM and ultra-violet visible spectroscopy (Simon et al., 2009). Additionally, CCD cameras have been used as detectors in clinical analysis and showed high detection sensitivity (Liang et al., 2004; Alexandre et al., 2001). The rapid improvements in digital camera technology provide the opportunity for the development of new methodologies employing digital cameras as an analytical sensor with high sensitivity, robustness, speed and low cost for implementation

In this section batch cooling crystallization of adipic acid will be used as a model to demonstrate the use of in line and non-invasive techniques for monitoring crystallization. For this purpose, four analytical tools with different physical principles were used. The procedures and techniques used in the experiments are described in the following

crystallization processes (Févotte & Klein, 1995)

**1.4.4 Image analysis**

that reduces the analysis time.

**2. Experimental part**

subsections.

The solubility of adipic acid (99.8%) in ethanol (analytical grade) was determined for twelve different temperatures ranging from 16.0 to 64.0C. The experiments were performed in a 1.8-L Hastelloy jacketed reactor vessel connected to an RC1e reaction calorimeter. The solutions were prepared by successive additions of adipic acid to a solution containing ethanol at a stirring rate of 300 rpm. For measurements at 44.0C, the mass of ethanol used was 524.0g. The used mass for other temperatures are presented in Table 1. The solubilization temperature was maintained constant during the whole process.

Table 1. Experimental conditions for testing the solubility of the adipic acid in ethanol.

The ATR-FTIR measurements were performed by using a Mettler-Toledo ReactIR IC10 spectrometer. The base unit contains the Fourier transform mid-infrared source and the mercuric cadmium telluride (MCT) detector that should be cooled with liquid nitrogen. The sample interface module (SIM) is the interface on the instrument base unit where the K6 (16 mm diameter) conduit connects. It contains the optics that transfer the infrared source light from the base unit to the probe in contact with the chemical materials contained in the vessel and then back to the detector. Measurements are taken optically using a diamond sensing element that uses a multiple reflection ATR crystal and a gold seal between the metal housing and the sensor. Figure 3 illustrates schematically the K6 Mettler Toledo probe tip.

The focused beam reflectance measurements were obtained by using a Mettler-Toledo Lasentec D600L probe consisting of a Hastelloy C-22 tube with the sensor at one end with an optical diameter of 19 mm and a length of ∼406 mm. The FBRM laser provides a continuous beam of monochromatic light with a wavelength of 780 nm. The beam is located approximately 3 mm to the focal point.

The ATR-FTIR and FBRM probes were kept immersed in the adipic acid solution 5 cm above the propeller stirrer. Infrared spectra obtained from 4000 to 650 cm-1 at 4 wave numbers resolution were collected at 15 s intervals with each spectrum averaged over 30 scans.

Real-Time Analysis to Evaluate Crystallization Processes 311

temperature of solution was kept 5°C higher than that saturation condition in order to assure that no crystal was presented in the solution prior to starting the cooling process. After 0.5 h, the solution was cooled at constant rate of 0.2 and 1°C/min, until the onset of crystallization. The experimental conditions of experiments are presented in Table 2.

13.2 30.0 -2.00 91.20 15.1 35.0 5.00 106.8 17.3 40.0 10.0 125.2 19.7 45.0 15.0 146.8 22.3 50.0 15.0 172.2 25.2 55.0 20.0 202.1 28.4 60.0 25.0 237.6 31.8 65.0 25.0 279.7

Table 2. Experimental conditions for crystallization experiments of adipic acid in ethanol.

In situ methods, FBRM and ATR-FTIR, were used to monitor adipic acid crystallization. Non-invasive measurements were carried out by monitoring the heat released and the image patterns of colours red, green and blue during the crystallization. Images of experiments were acquired by using a low cost PC webcam (Microsoft Life Cam VX-2000). The webcam was placed externally and, in order to avoid interferences by external light and to maintain the CCD noise under controlled conditions, the reactor was enclosed with a black box. The images were captured during whole experiments. A light-emitting diode (LED) was used as a source of illumination. The images acquired were analysed according to their patterns of colour red, green and blue, and for this purpose software was developed which allows the evaluation of alteration in these patterns of colours. The software enables the analysis of the whole image or the user can define a specific region previously selected from an image. The software automatically saves the coordinates of the delimited region for all digital images and calculates the R, G and B values averaging

The heat released during the crystallization was monitored using the RC1e. To be able to calculate the heat flow during the crystallization, the total heat transfer coefficient (U) and

This section presents the results obtained in the study of solubilization of adipic acid in ethanol as well as its crystallization, evaluating the possibility of using calorimetry, infrared (ATR-FTIR) and FBRM as techniques for determining the width of the metastable zone.

the heat capacity (Cp) of the solution of adipic acid were measured.

Final temperature (ºC)

Mass of adipic acid (g)

Temperature at the start of cooling (ºC)

Concentration (mass %)

all pixels.

**3. Results and discussion**

Fig. 3. Schematic draw of the Mettler Toledo K6 probe tip.

## **2.2.2 Batch cooling crystallization**

The batch cooling crystallization experiments were carried out in a double walled glass reactor with a capacity of 2.0L. The solutions were stirred by a propeller stirrer at 300 rpm. The experimental setup is schematically presented in Figure 4.

Fig. 4. Experimental setup.

The mass of ethanol used in each run was 600 g and the amount of adipic acid was varied from 91.2 to 279.9 g. The temperature was controlled by the precise RC1e thermostat. The

The batch cooling crystallization experiments were carried out in a double walled glass reactor with a capacity of 2.0L. The solutions were stirred by a propeller stirrer at 300 rpm.

The mass of ethanol used in each run was 600 g and the amount of adipic acid was varied from 91.2 to 279.9 g. The temperature was controlled by the precise RC1e thermostat. The

Fig. 3. Schematic draw of the Mettler Toledo K6 probe tip.

The experimental setup is schematically presented in Figure 4.

**2.2.2 Batch cooling crystallization**

Fig. 4. Experimental setup.

temperature of solution was kept 5°C higher than that saturation condition in order to assure that no crystal was presented in the solution prior to starting the cooling process. After 0.5 h, the solution was cooled at constant rate of 0.2 and 1°C/min, until the onset of crystallization. The experimental conditions of experiments are presented in Table 2.

Table 2. Experimental conditions for crystallization experiments of adipic acid in ethanol.

In situ methods, FBRM and ATR-FTIR, were used to monitor adipic acid crystallization. Non-invasive measurements were carried out by monitoring the heat released and the image patterns of colours red, green and blue during the crystallization. Images of experiments were acquired by using a low cost PC webcam (Microsoft Life Cam VX-2000). The webcam was placed externally and, in order to avoid interferences by external light and to maintain the CCD noise under controlled conditions, the reactor was enclosed with a black box. The images were captured during whole experiments. A light-emitting diode (LED) was used as a source of illumination. The images acquired were analysed according to their patterns of colour red, green and blue, and for this purpose software was developed which allows the evaluation of alteration in these patterns of colours. The software enables the analysis of the whole image or the user can define a specific region previously selected from an image. The software automatically saves the coordinates of the delimited region for all digital images and calculates the R, G and B values averaging all pixels.

The heat released during the crystallization was monitored using the RC1e. To be able to calculate the heat flow during the crystallization, the total heat transfer coefficient (U) and the heat capacity (Cp) of the solution of adipic acid were measured.

## **3. Results and discussion**

This section presents the results obtained in the study of solubilization of adipic acid in ethanol as well as its crystallization, evaluating the possibility of using calorimetry, infrared (ATR-FTIR) and FBRM as techniques for determining the width of the metastable zone.

Real-Time Analysis to Evaluate Crystallization Processes 313

release decreased and became nearly constant. The region where heat release is constant may be associated with the growth of crystals (Riesen, 2005). The heat release continued until the moment when the reactor temperature was maintained at 15.0 °C. With the constant temperature the heat flow remained stable, indicating that the process that was responsible for the release of heat had ceased. As the only process that was taking place inside the reactor was the crystallization of adipic acid, this release is solely related to this

> Heat Flow (Qr) Jacket Temperature (Tj) Temperature inside reactor (Tr)

> > Onset crystallization temperature

Steady heat flow

0.0 3.5 7.0 10.5 14.0 17.5 21.0 24.5 28.0 31.5 35.0 38.5 42.0 45.5 49.0 52.5

**Temperature (ºC)**

Fig. 6. Heat release curve (Qr), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22%, cooled at a rate of 1°C/min and with a stirring rate of

heat flow increasing = onset of crystallization

20 30 40 50 60 70 80

**Time (min)**

The maximum supersaturation achieved in the solution is a function of the maximum cooling achieved by the system. Thus, it is expected that the higher the maximum cooling achieved by a system, the greater the value of supersaturation in the medium. In general the smaller nucleation rates are obtained at lower cooling rates (Mullin, 2001). In order to check this information, the crystallization of adipic acid was performed at a lower cooling rate as

The rate at which heat is released when employing a cooling rate of 1°C/min is higher than

The comparison between the results presented in Figures 6 and 7 confirms that the

process.

300 rpm.

0

20

40

**Heat flow (W)**

60

80

100

120

presented in Figure 7.

when using a cooling rate of 0.2°C/min.

maximum heat released is a function of cooling rate.

#### **3.1 Determination of the solubility of adipic acid**

The solubility curve of adipic acid in ethanol, presented in Figure 5, was prepared according to procedure in literature that used ATR-FTIR and heat flow to calculate the solubility curve of adipic acid in acetone (Silva & Silva, 2011).

Fig. 5. Solubility curves of adipic acid in ethanol by using ATR-FTIR and heat flow calorimetry.

#### **3.2 Determination of the onset temperature for the crystallization of adipic acid in ethanol by heat flow calorimetry**

Since during crystallization there is a decrease in entropy, the second term of the Gibbs free energy (equation 3) becomes positive and therefore, for ∆G to be negative, it is necessary that the change in enthalpy is negative, which shows that the crystallization processes are exothermic.

$$
\Delta \mathbf{G} = \Delta \mathbf{H} \text{ - T\Delta\mathbf{S}} \tag{3}
$$

The heat flow for cooling at 10C/min is presented in Figure 6.

The analysis of Figure 6 shows that when the solution temperature was approximately 37.2°C, the jacket temperature was reduced by about 10°C, so that the cooling rate of 1°C/min could be maintained, meaning that an exothermic process had started. The heat flow measurement had a fast increase at the same moment indicating that the crystallization of the adipic acid (the exothermic process) had begun. In the initial moments of the crystallization there was an intense release of heat and soon after that the

The solubility curve of adipic acid in ethanol, presented in Figure 5, was prepared according to procedure in literature that used ATR-FTIR and heat flow to calculate the solubility curve

Fig. 5. Solubility curves of adipic acid in ethanol by using ATR-FTIR and heat flow calorimetry.

288 296 304 312 320 328 336 344

**T (K)**

Since during crystallization there is a decrease in entropy, the second term of the Gibbs free energy (equation 3) becomes positive and therefore, for ∆G to be negative, it is necessary that the change in enthalpy is negative, which shows that the crystallization processes are

The analysis of Figure 6 shows that when the solution temperature was approximately 37.2°C, the jacket temperature was reduced by about 10°C, so that the cooling rate of 1°C/min could be maintained, meaning that an exothermic process had started. The heat flow measurement had a fast increase at the same moment indicating that the crystallization of the adipic acid (the exothermic process) had begun. In the initial moments of the crystallization there was an intense release of heat and soon after that the

∆G = ∆H - T∆S (3)

**3.2 Determination of the onset temperature for the crystallization of adipic acid in**

**3.1 Determination of the solubility of adipic acid**

of adipic acid in acetone (Silva & Silva, 2011).

 ATR - FTIR Heat Flow

**ethanol by heat flow calorimetry**

The heat flow for cooling at 10C/min is presented in Figure 6.

exothermic.

0,02

0,04

0,06

0,08

0,10

**mole fraction (%)**

0,12

0,14

0,16

release decreased and became nearly constant. The region where heat release is constant may be associated with the growth of crystals (Riesen, 2005). The heat release continued until the moment when the reactor temperature was maintained at 15.0 °C. With the constant temperature the heat flow remained stable, indicating that the process that was responsible for the release of heat had ceased. As the only process that was taking place inside the reactor was the crystallization of adipic acid, this release is solely related to this process.

Fig. 6. Heat release curve (Qr), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22%, cooled at a rate of 1°C/min and with a stirring rate of 300 rpm.

The maximum supersaturation achieved in the solution is a function of the maximum cooling achieved by the system. Thus, it is expected that the higher the maximum cooling achieved by a system, the greater the value of supersaturation in the medium. In general the smaller nucleation rates are obtained at lower cooling rates (Mullin, 2001). In order to check this information, the crystallization of adipic acid was performed at a lower cooling rate as presented in Figure 7.

The rate at which heat is released when employing a cooling rate of 1°C/min is higher than when using a cooling rate of 0.2°C/min.

The comparison between the results presented in Figures 6 and 7 confirms that the maximum heat released is a function of cooling rate.

Real-Time Analysis to Evaluate Crystallization Processes 315

Fig. 8. Monitoring of the onset of the crystallization of adipic acid using the image analysis

**crystallization**

Fig. 9. Monitoring of the onset of the crystallization of adipic acid using the image analysis

method (increasing the mass of adipic acid crystals due to cooling).

method (saturated solution).

Fig. 7. Heat release curve (Qr), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22%, cooled at a rate of 0.2°C/min and with a stirring rate of 300 rpm.

#### **3.3 Determination of the onset temperature for the crystallization of adipic acid in ethanol by RGB image analysis**

The image video analysis was performed by using software named MasterView RGB that captures images in real-time from a PC webcam by evaluating changes in the component's RGB colour pixel by pixel. The software automatically saves the coordinates of the delimited region for all digital images and calculates the RGB values averaging all pixels (de Sena et al., 2011).

Figure 8 shows the graphic interface of MasterView RGB for an adipic acid solution and Figure 9 presents the crystallization onset by measuring the RGB variation.

The method of image analysis is based on comparison of images. This procedure is comparable to human visual inspection and the method of image analysis has greater sensitivity and is not subject to misinterpretation.

The variation of the red channel during the crystallization of adipic acid is presented in Figure 10.

 Heat Flow (Qr) Jacket Temperature (Tj) Temperature inside of reactor (Tr)

> Onset crystallization temperature

Fig. 7. Heat release curve (Qr), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22%, cooled at a rate of 0.2°C/min and with a stirring rate of

heat flow increasing = onset of crystallization Steady heat flow

Time (min)

50 100 150 200 250

0

6

12

18

24

Temperature (ºC)

30

36

42

48

54

**3.3 Determination of the onset temperature for the crystallization of adipic acid in**

The image video analysis was performed by using software named MasterView RGB that captures images in real-time from a PC webcam by evaluating changes in the component's RGB colour pixel by pixel. The software automatically saves the coordinates of the delimited region for all digital images and calculates the RGB values averaging all pixels (de Sena et

Figure 8 shows the graphic interface of MasterView RGB for an adipic acid solution and

The method of image analysis is based on comparison of images. This procedure is comparable to human visual inspection and the method of image analysis has greater

The variation of the red channel during the crystallization of adipic acid is presented in

Figure 9 presents the crystallization onset by measuring the RGB variation.

300 rpm.

0

20

40

Heat flow (W)

60

80

100

120

al., 2011).

Figure 10.

**ethanol by RGB image analysis**

sensitivity and is not subject to misinterpretation.

Fig. 8. Monitoring of the onset of the crystallization of adipic acid using the image analysis method (saturated solution).

Fig. 9. Monitoring of the onset of the crystallization of adipic acid using the image analysis method (increasing the mass of adipic acid crystals due to cooling).

Real-Time Analysis to Evaluate Crystallization Processes 317

Fig. 12. Adipic acid carbonyl absorption variation measured in the interval of 1750-1600 cm-1.

Figure 13.

The carbonyl absorption trend related to the data presented in Figure 12 is presented in

crystallization onset

Fig. 11. ATR/FTIR spectra of adipic acid in the infrared region.

saturated solution

Fig. 10. Image analysis red channel, the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using ethanol solution with initial concentration of 22%, cooled at a rate of 1°C/min and with a stirring rate of 300 rpm.

As can be seen in Figure 8, before the crystallization of adipic acid (red signal channel close to zero), the red value increases immediately when the adipic acid crystallization starts. This result is in total accordance with the results obtained by heat flow calorimetry. It was established that the onset temperature of crystallization, determined by the variation in RGB signal, would be that corresponding to the time when the RGB signal began to increase.

#### **3.4 Determination of the onset temperature of crystallization using infrared (ATR-FTIR)**

The infrared absorption spectrum of adipic acid is presented in Figure 11.

The carbonyl stretching absorption region of carboxylic acids used in the ATR-FTIR analysis is indicated in Figure 11.

The analysis of crystallization of a solution of adipic acid in ethanol was accompanied by infrared (ATR-FTIR), through the decrease of the signal of the peak area for the absorption of carbonyl (C=O) in the medium. Figure 12 presents the carbonyl absorption variation during a crystallization process that started at 50 °C.

Fig. 10. Image analysis red channel, the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from crystallization experiments using ethanol solution with initial concentration of 22%, cooled at a rate of 1°C/min and with a stirring rate of 300 rpm.

Time (min)

20 30 40 50 60 70 80

As can be seen in Figure 8, before the crystallization of adipic acid (red signal channel close to zero), the red value increases immediately when the adipic acid crystallization starts. This result is in total accordance with the results obtained by heat flow calorimetry. It was established that the onset temperature of crystallization, determined by the variation in RGB signal, would be that corresponding to the time when the RGB signal began to increase.

**3.4 Determination of the onset temperature of crystallization using infrared (ATR-**

The carbonyl stretching absorption region of carboxylic acids used in the ATR-FTIR analysis

The analysis of crystallization of a solution of adipic acid in ethanol was accompanied by infrared (ATR-FTIR), through the decrease of the signal of the peak area for the absorption of carbonyl (C=O) in the medium. Figure 12 presents the carbonyl absorption variation

The infrared absorption spectrum of adipic acid is presented in Figure 11.

during a crystallization process that started at 50 °C.

**FTIR)**

0

20

40

RGB Value (a.u)

60

RGB value

 Jacket Temperature (Tj) Temperature inside of reactor (Tr)

RGB value increasing = onset of crystallization

80

100

120

is indicated in Figure 11.

Temperature (ºC)

0,0 3,5 7,0 10,5 14,0 17,5 21,0 24,5 28,0 31,5 35,0 38,5 42,0 45,5 49,0 52,5

Onset crystallization temperature

Fig. 11. ATR/FTIR spectra of adipic acid in the infrared region.

Fig. 12. Adipic acid carbonyl absorption variation measured in the interval of 1750-1600 cm-1.

The carbonyl absorption trend related to the data presented in Figure 12 is presented in Figure 13.

Real-Time Analysis to Evaluate Crystallization Processes 319

Fig. 14. Infrared absorption curve of the carbonyl C=O (1765-1660 cm-1) of adipic acid during

25 50 75 100 125 150 175 200 225 250 275

**Time (min)**

Fig. 15. Total chord counts (FBRM), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from the crystallization experiments using a solution of ethanol with initial concentration of 22%, cooled at a rate of 1°C/min and stirring rate of 300 rpm.

**Time (min)**

20 30 40 50 60 70 80

0,0

5,5

11,0

16,5

22,0

27,5

**Temperature (ºC)**

33,0

Onset crystallization temperature

38,5

44,0

49,5

55,0

crystallizations performed at cooling rates of 1.0 and 0.20C/min.

Coun ts of particles i ncreasing

 = Onset of c rystallization

Jacket Temperature (Tj) Temperature inside reactor (Tr)

**Counts/sec**

0.2° o C/min 1.0° o C/min

24 Counts/sec

 **Peak area C=**

**O**

0

Fig. 13. Absorption curve of the carbonyl C=O (1765-1660 cm 1) in ethanol, the temperature inside the reactor (Tr) and jacket temperature (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22% , cooled at a rate of 1°C/min and stirring rate of 300 rpm.

The carbonyl absorption area presented a decrease at the precise moment the crystallization started. This observation is in total agreement with the fact that the ATR probe detects the concentration of adipic acid soluble in ethanol. A comparison between the infrared absorption for the cooling rates of 1 and 0.20C/min is presented in Figure 14.

The FTIR analysis may be considered as an indirect measurement of the kinetics of crystallization, since the ATR probe cannot detect the crystallized adipic acid. As expected, the diminution of the carbonyl absorption was more pronounced when the higher cooling rate was used.

#### **3.5 Determination of onset temperature of the crystallization using Focused Beam Reflectance Measurement**

The variation in the total chord counts obtained from the FBRM analysis can detect the crystallization onset. This signal remained in the form of a stable baseline, with a few counts per second before the formation of crystals. By the time the crystallization of adipic acid had started the chord counts increased dramatically. This behaviour can be seen in Figure 15.

Fig. 13. Absorption curve of the carbonyl C=O (1765-1660 cm 1) in ethanol, the temperature inside the reactor (Tr) and jacket temperature (Tj), obtained from crystallization experiments using an ethanol solution with initial concentration of 22% , cooled at a rate of 1°C/min and

The carbonyl absorption area presented a decrease at the precise moment the crystallization started. This observation is in total agreement with the fact that the ATR probe detects the concentration of adipic acid soluble in ethanol. A comparison between the infrared

The FTIR analysis may be considered as an indirect measurement of the kinetics of crystallization, since the ATR probe cannot detect the crystallized adipic acid. As expected, the diminution of the carbonyl absorption was more pronounced when the higher cooling

**3.5 Determination of onset temperature of the crystallization using Focused Beam**

The variation in the total chord counts obtained from the FBRM analysis can detect the crystallization onset. This signal remained in the form of a stable baseline, with a few counts per second before the formation of crystals. By the time the crystallization of adipic acid had started the chord counts increased dramatically. This behaviour can be seen in Figure 15.

absorption for the cooling rates of 1 and 0.20C/min is presented in Figure 14.

stirring rate of 300 rpm.

rate was used.

**Reflectance Measurement**

Fig. 14. Infrared absorption curve of the carbonyl C=O (1765-1660 cm-1) of adipic acid during crystallizations performed at cooling rates of 1.0 and 0.20C/min.

Fig. 15. Total chord counts (FBRM), the temperature inside the reactor (Tr) and temperature of the jacket (Tj), obtained from the crystallization experiments using a solution of ethanol with initial concentration of 22%, cooled at a rate of 1°C/min and stirring rate of 300 rpm.

Real-Time Analysis to Evaluate Crystallization Processes 321

length distribution indicates crystal growth. The crystal sizes presented in Figure 17 confirm

The average size of the chord length of adipic acid particles produced in the set of

concentration (% mass) cooling rate (ºC/min) average size (μm) 13.2 0.2 75.20 13.2 1.0 65.24 15.1 0.2 76.91 15.1 1.0 73.11 17.3 0.2 84.36 17.3 1.0 73.59 19.7 0.2 73.48 19.7 1.0 70.76 22.3 0.2 119.4 22.3 1.0 77.47 25.2 0.2 106.7 25.2 1.0 88.88 28.4 0.2 127.9 28.4 1.0 80.31 31.8 0.2 132.2 31.8 1.0 88.78 Table 3. Average size of the chord length of adipic acid crystals in the different experimental

The results presented in Table 3 show that the average size of adipic acid crystals increases as the cooling rate decreases. This fact is directly correlated with the metastable zone width, which is directly proportional to the rate of nucleation (Nyvlt et al., 2001). Thus, the largest crystals were observed when the cooling rate was 0.2°C/min, the rate at which the

The metastable zone width of a system is dependent on the methodology employed for its determination. Depending on the sensitivity of the technique used to detect the onset of crystallization, significant deviations can occur between two different methodologies (Marciniak, 2002). For a satisfactory evaluation of the metastable zone limit, it is necessary that the reactor be cooled at a constant rate. This constant cooling can be seen through the

The onset crystallization temperatures determined by the different real-time methods are

**3.6 Determination of metastable zone width of adipic acid in ethanol**

linear behaviour of both the crystallizer temperature and the jacket of the reactor.

presented in Table 4 and the agreement between these data can be seen in Figure 18.

the crystal growth.

conditions.

narrowest metastable zone was maintained.

experiments is presented in Table 3.

The comparison between the chord length distribution in the crystallization onset with the values obtained in the end cooling, presented in Figure 16, can furnish information about crystal growth and this variation can also be detected by analysing the particle video microscopy images correspondent to these different moments that are shown in Figure 17.

Fig. 16. Chord length distribution obtained in the crystallization onset, green curve and at the end of the experiment.

Fig. 17. Real-time particle video microscopy obtained in the crystallization onset (a) and in the end of the experiment (b).

The distributions shown in Figure 16 were displayed on a logarithmic scale on the horizontal axis (length of chords) for easy viewing. The shift to the right side in the chord

The comparison between the chord length distribution in the crystallization onset with the values obtained in the end cooling, presented in Figure 16, can furnish information about crystal growth and this variation can also be detected by analysing the particle video microscopy images correspondent to these different moments that are shown in Figure 17.

Fig. 16. Chord length distribution obtained in the crystallization onset, green curve and at

 Fig. 17. Real-time particle video microscopy obtained in the crystallization onset (a) and in

The distributions shown in Figure 16 were displayed on a logarithmic scale on the horizontal axis (length of chords) for easy viewing. The shift to the right side in the chord

the end of the experiment.

the end of the experiment (b).

length distribution indicates crystal growth. The crystal sizes presented in Figure 17 confirm the crystal growth.

The average size of the chord length of adipic acid particles produced in the set of experiments is presented in Table 3.

Table 3. Average size of the chord length of adipic acid crystals in the different experimental conditions.

The results presented in Table 3 show that the average size of adipic acid crystals increases as the cooling rate decreases. This fact is directly correlated with the metastable zone width, which is directly proportional to the rate of nucleation (Nyvlt et al., 2001). Thus, the largest crystals were observed when the cooling rate was 0.2°C/min, the rate at which the narrowest metastable zone was maintained.

## **3.6 Determination of metastable zone width of adipic acid in ethanol**

The metastable zone width of a system is dependent on the methodology employed for its determination. Depending on the sensitivity of the technique used to detect the onset of crystallization, significant deviations can occur between two different methodologies (Marciniak, 2002). For a satisfactory evaluation of the metastable zone limit, it is necessary that the reactor be cooled at a constant rate. This constant cooling can be seen through the linear behaviour of both the crystallizer temperature and the jacket of the reactor.

The onset crystallization temperatures determined by the different real-time methods are presented in Table 4 and the agreement between these data can be seen in Figure 18.

Real-Time Analysis to Evaluate Crystallization Processes 323

**3.7 Study of the effect of the cooling rate on the metastable zone width of adipic acid**

Considering that the calorimetric method presented the highest sensibility, this was the chosen method to present the metastable zone limits for the crystallization of adipic acid by

Fig. 19. Solubility curve of adipic acid in ethanol and the metastable zone limits determined

10 20 30 40 50 60 70

**Temperature**

The metastable zone width, expressed in terms of maximum cooling achieved, Δt, which is the difference between the saturation temperature, T saturation, and the onset temperature of crystallization, is reduced when the cooling rate is diminished. This statement can be

Considering that the experimental conditions employed during crystallization may affect physical properties of the product, such as its chemical purity, crystal size distribution and polymorphism and that these properties are completely related to the metastable zone width, accurate measurement techniques capable of providing data to construct solubility curves, as well as the onset of crystallization, are of vital importance. Off line analytical methods used to determine solubility curves and to detect the onset of crystallization present much higher errors than those that use real-time analysis for the same purpose. The

using cooling rates of 1.0 and 0.20C/min as presented in Figure 19.

Solubility curve

 1.0 0 C/min 0.2 OC/min

**in ethanol**

at 1.0 and 0.20C/min.

10

15

20

25

**Concentration (mass percent )**

30

35

**4. Conclusion**

confirmed by the data presented in Figure 19.

Table 4. Comparison of the calorimetric method, infrared and total chord counts for the determination of the onset temperature of crystallization of adipic acid in ethanol using a cooling rate of 1°C/min.

Fig. 18. Curves of the peak area of absorption of carbonyl (C=O), total count (FBRM), image analysis by RGB (**RGB**), calorimetry (heat flow) obtained from the cooling of a solution of 22% adipic acid in ethanol, cooled to 1.0 ° C / min with a stirring rate of 300 rpm.

The results presented in Figure 18, obtained by the different real-time analyses, were similar. In this case, the heat flow measurement presented higher sensibility than the other real-time analyses, but all techniques can be considered equivalent.

13.2 16.45 16.13 16.23 15.1 18.02 17.78 17.90 17.3 24.44 24.34 24.20 19.7 30.91 30.70 30.79 22.3 37.34 37.16 37.28 25.2 42.77 42.70 42.72 28.4 50.30 50.24 50.27 31.8 57.22 57.11 57.19

T infrared (ºC) T FBRM (ºC)

0

3

6

9

12

15

Peak area C=O, counts/sec

18

21

24

27

30

T calorimetry (ºC)

Table 4. Comparison of the calorimetric method, infrared and total chord counts for the determination of the onset temperature of crystallization of adipic acid in ethanol using a

Fig. 18. Curves of the peak area of absorption of carbonyl (C=O), total count (FBRM), image analysis by RGB (**RGB**), calorimetry (heat flow) obtained from the cooling of a solution of

Time (min)

10 20 30 40 50 60 70 80

The results presented in Figure 18, obtained by the different real-time analyses, were similar. In this case, the heat flow measurement presented higher sensibility than the other

22% adipic acid in ethanol, cooled to 1.0 ° C / min with a stirring rate of 300 rpm.

real-time analyses, but all techniques can be considered equivalent.

Adipic acid concentration (%)

cooling rate of 1°C/min.

 Heat Flow (W) RGB value (a.u) Counts/sec Peak area C=O

0

20

40

Heat flow (W), RGB value (a.u)

60

80

100

120

#### **3.7 Study of the effect of the cooling rate on the metastable zone width of adipic acid in ethanol**

Considering that the calorimetric method presented the highest sensibility, this was the chosen method to present the metastable zone limits for the crystallization of adipic acid by using cooling rates of 1.0 and 0.20C/min as presented in Figure 19.

Fig. 19. Solubility curve of adipic acid in ethanol and the metastable zone limits determined at 1.0 and 0.20C/min.

The metastable zone width, expressed in terms of maximum cooling achieved, Δt, which is the difference between the saturation temperature, T saturation, and the onset temperature of crystallization, is reduced when the cooling rate is diminished. This statement can be confirmed by the data presented in Figure 19.

## **4. Conclusion**

Considering that the experimental conditions employed during crystallization may affect physical properties of the product, such as its chemical purity, crystal size distribution and polymorphism and that these properties are completely related to the metastable zone width, accurate measurement techniques capable of providing data to construct solubility curves, as well as the onset of crystallization, are of vital importance. Off line analytical methods used to determine solubility curves and to detect the onset of crystallization present much higher errors than those that use real-time analysis for the same purpose. The

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**12**

*Ireland*

**Phenacetin Crystallization:**

Humphrey A. Moynihan and Dawn M. Kelly

*University College Cork, Cork*

**Cooling Regimes and Crystal Morphology**

*Dept. of Chemistry / Analytical and Biological Chemistry Research Facility,*

Phenacetin crystallizations were undertaken to gain an insight into how to better control the various parameters of a crystallization process. Good control of the crystallization process allows the design of experiments to control certain characteristics of the final crystal product. These include crystal morphology, phase, particle size and crystal size distribution (CSD). These physical attributes of a crystal population are thought to be achieved through the control of the nucleation and growth of crystals during the crystallization process. One of the first attempts to control crystallization processes was proposed by Griffiths (Griffiths, 1925), who suggested the idea of "controlled cooling" in batch crystallizations by maintaining the supersaturation in the metastable region in order to improve the product CSD. Garside et al. performed experimental studies employing this concept of controlled cooling in crystallization processes, which included simple strategies such as isothermal operation and linear cooling (Garside et al., 1972). Since these early crystallization control approaches, there have been many strategies that indirectly affect the CSD of a crystallization process, often involving a change in temperature or the addition of an antisolvent during a pre-defined timescale so as to follow a given supersaturation profile in the phase diagram. These profiles are obtained using simple trial-and-error experimentation or more complex model-based or direct-design approaches (Abu Bakar et al., 2009a). Woo et al. proposed an adaptive concentration control strategy that employs the measurement of the number of particle counts per unit time provided by *in situ* laser backscattering in order to detect the onset of nucleation and adapt the operating curve accordingly (Woo et al., 2009). In a move towards new strategies for directly affecting the CSD of a crystallisation process, Abu Baker et al. (Abu Bakar et al., 2009a) used a model-free approach to crystallization control known as 'direct nucleation control' (DNC), in which the number of counts measured by an *in situ* laser probe is directly controlled using a feedback control strategy. An alternative strategy is to chart an oscillating cooling regime within the metastable zone of the crystallization, in which the overall cooling trend drives crystal growth while the temperature fluctuations provided by the oscillating cool allows partial dissolution (Abu Bakar et al., 2009b). The result should be an equalizing of crystal size and shape. Both of these approaches were utilized in the present study. Phenacetin was selected as the subject for this study as it is an Active Pharmaceutical Ingredient - now withdrawn

(Prescott, 1980) - and is not known to be crystal polymorphic (Hansen, 2006).

**1. Introduction**

## **Phenacetin Crystallization: Cooling Regimes and Crystal Morphology**

Humphrey A. Moynihan and Dawn M. Kelly *Dept. of Chemistry / Analytical and Biological Chemistry Research Facility, University College Cork, Cork Ireland*

### **1. Introduction**

328 Crystallization – Science and Technology

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> Phenacetin crystallizations were undertaken to gain an insight into how to better control the various parameters of a crystallization process. Good control of the crystallization process allows the design of experiments to control certain characteristics of the final crystal product. These include crystal morphology, phase, particle size and crystal size distribution (CSD). These physical attributes of a crystal population are thought to be achieved through the control of the nucleation and growth of crystals during the crystallization process. One of the first attempts to control crystallization processes was proposed by Griffiths (Griffiths, 1925), who suggested the idea of "controlled cooling" in batch crystallizations by maintaining the supersaturation in the metastable region in order to improve the product CSD. Garside et al. performed experimental studies employing this concept of controlled cooling in crystallization processes, which included simple strategies such as isothermal operation and linear cooling (Garside et al., 1972). Since these early crystallization control approaches, there have been many strategies that indirectly affect the CSD of a crystallization process, often involving a change in temperature or the addition of an antisolvent during a pre-defined timescale so as to follow a given supersaturation profile in the phase diagram. These profiles are obtained using simple trial-and-error experimentation or more complex model-based or direct-design approaches (Abu Bakar et al., 2009a). Woo et al. proposed an adaptive concentration control strategy that employs the measurement of the number of particle counts per unit time provided by *in situ* laser backscattering in order to detect the onset of nucleation and adapt the operating curve accordingly (Woo et al., 2009). In a move towards new strategies for directly affecting the CSD of a crystallisation process, Abu Baker et al. (Abu Bakar et al., 2009a) used a model-free approach to crystallization control known as 'direct nucleation control' (DNC), in which the number of counts measured by an *in situ* laser probe is directly controlled using a feedback control strategy. An alternative strategy is to chart an oscillating cooling regime within the metastable zone of the crystallization, in which the overall cooling trend drives crystal growth while the temperature fluctuations provided by the oscillating cool allows partial dissolution (Abu Bakar et al., 2009b). The result should be an equalizing of crystal size and shape. Both of these approaches were utilized in the present study. Phenacetin was selected as the subject for this study as it is an Active Pharmaceutical Ingredient - now withdrawn (Prescott, 1980) - and is not known to be crystal polymorphic (Hansen, 2006).

Phenacetin Crystallization: Cooling Regimes and Crystal Morphology 331

rougher surfaces than the ethanol-derived needles, again assisting crystal growth. In addition, any differences in habit after the crystallization of phenacetin from ethanol using these seed crystals would assist in the determination of whether growth or nucleation dominated these processes. The seed crystals were sieved to give the size ranges described below using a set of U.S.A. standard testing sieves (Avantech Manufacturing) in mesh sizes of 150 m, 300 m and 500 m. The seeds were added to crystallisations in an ethanol slurry using seed crystals with a weight in grams equal to

Fig. 1. A schematic representation of the experimental setup for phenacetin crystallization

Only one crystalline form of phenacetin has been reported to date (Hansen, 2006). To check that no new polymorphs or solvates of phenacetin were obtained during these experiments, powder X-ray diffraction (PXRD) patterns were recorded for all of the samples and compared with the theoretical pattern generated from the structure reported by Hansen et al. (Hansen, 2006). PXRD was performed at an ambient temperature using a Stoe Stadi MP diffractometer operating in transmission mode with a linear PSD detector, with an anode current of 40 mA, an accelerating voltage of 40 kV and Cu Kα1 X-radiation (λ = 1.5406 Å), typically over a scan range of 3.5° to 60° 2θ, scanning in steps of 2° for 90 s per step. The samples were held between acetate foils. The theoretical patterns were generated from the crystallographic information file downloaded from the Cambridge Structural Database (CSD) - CSD reference code PYRAZB21 - using the THEO function on the Stoe WinXPOW software package. Figure 2 shows a typical example of a PXRD pattern of a phenacetin batch with the theoretical pattern overlaid, with excellent correspondence between the observed

20% of the total batch concentration.

experiments.

and theoretical patterns.

This chapter will present work on phenacetin crystallization using two forms of modified cooling regimes in an attempt to directly affect the product CSD of the crystallization process. We begin with a cooling regime using turbidity counts as a termination clause for each cooling and heating step. We then move to a more in-depth study in Section 3.2, where the cyclic cooling paths that had predefined temperature parameters were used, ensuring that a cyclic temperature profile was maintained within the limits of the metastable zone width (MSZW). This temperature profile was coupled with a seeding regime where each experiment was seeded with crystals that were sieved to give specific size ranges of less than 150 μm (fine particles), between 150-300 μm (medium particles) and over 500 μm (coarse particles). The objective of both of these types of modified cooling regimes is to provide a narrower range of crystal sizes and shapes than would otherwise be obtained by a simple linear cooling regime.

## **2. Experimental methods**

Phenacetin was purchased from Sigma-Aldrich. GPR grade absolute ethanol was purchased from Carbon Group Chemical Ltd. (Cork, Ireland) and was used in all of the experiments. Ethanol was chosen as a solvent for these experiments because the solubility of phenacetin in ethanol varies significantly over the temperature range 10 °C to 30 °C, allowing for the development of a practical crystallization method. The determination of phenacetin solubility and metastable zone width is described below. Phenacetin crystallizes cleanly from ethanol to give well-formed needles which are largely free from the inclusions of other defects.

A HEL Autolab jacketed reactor vessel equipped with a HEL Lasertrack *in situ* particle sizing laser probe was used to monitor the presence and size of phenacetin crystals on a 1 L scale. The laser wavelength was 795 nm. It is possible to get readings of particles as small as 0.5 μm. A PTFE PT100 thermocouple gave *in situ* temperature measurements of the crystallization medium. The temperature of the jacket fluid (Huber DW-Therm thermal fluid, operating range −90 °C to 200 °C) was controlled by a Huber Unistat 815 circulation thermostat. The system was entirely controlled from one PC using HEL WinISO software, allowing the control of stirring rates, the addition of material (the pumping rate and mass pumped), and the heating parameters (heating or cooling rates, reactor vessel temperature set point, jacket fluid temperature set point). The software allowed the pre-programming of crystallization regimes containing as many separate steps as required, e.g., multiple heat/cool steps, solvent addition steps, etc. The steps could be programmed to terminate and move to a next step upon reaching a specified set point, such as the reactor temperature or the number of particles observed.

Crystal habits were observed using a Nikon Polarizing Microscope Eclipse 50i POL and photomicrographs were taken on a Nikon Digital Sight DS-Fi1 digital camera. Figure 1 shows a schematic representation of the experimental setup for phenacetin crystallization experiments.

In the experiments described below, in which seeding was used, crystals obtained from water were used as seed crystals because they typically have a plate-like habit. The platelike habit provides a greater surface area for growth and so is more suitable for seeds than the needle-like habit obtained from ethanol. The crystals formed from water also have

This chapter will present work on phenacetin crystallization using two forms of modified cooling regimes in an attempt to directly affect the product CSD of the crystallization process. We begin with a cooling regime using turbidity counts as a termination clause for each cooling and heating step. We then move to a more in-depth study in Section 3.2, where the cyclic cooling paths that had predefined temperature parameters were used, ensuring that a cyclic temperature profile was maintained within the limits of the metastable zone width (MSZW). This temperature profile was coupled with a seeding regime where each experiment was seeded with crystals that were sieved to give specific size ranges of less than 150 μm (fine particles), between 150-300 μm (medium particles) and over 500 μm (coarse particles). The objective of both of these types of modified cooling regimes is to provide a narrower range of crystal sizes and shapes than would otherwise be obtained by a

Phenacetin was purchased from Sigma-Aldrich. GPR grade absolute ethanol was purchased from Carbon Group Chemical Ltd. (Cork, Ireland) and was used in all of the experiments. Ethanol was chosen as a solvent for these experiments because the solubility of phenacetin in ethanol varies significantly over the temperature range 10 °C to 30 °C, allowing for the development of a practical crystallization method. The determination of phenacetin solubility and metastable zone width is described below. Phenacetin crystallizes cleanly from ethanol to give well-formed needles which are largely free from the inclusions of other

A HEL Autolab jacketed reactor vessel equipped with a HEL Lasertrack *in situ* particle sizing laser probe was used to monitor the presence and size of phenacetin crystals on a 1 L scale. The laser wavelength was 795 nm. It is possible to get readings of particles as small as 0.5 μm. A PTFE PT100 thermocouple gave *in situ* temperature measurements of the crystallization medium. The temperature of the jacket fluid (Huber DW-Therm thermal fluid, operating range −90 °C to 200 °C) was controlled by a Huber Unistat 815 circulation thermostat. The system was entirely controlled from one PC using HEL WinISO software, allowing the control of stirring rates, the addition of material (the pumping rate and mass pumped), and the heating parameters (heating or cooling rates, reactor vessel temperature set point, jacket fluid temperature set point). The software allowed the pre-programming of crystallization regimes containing as many separate steps as required, e.g., multiple heat/cool steps, solvent addition steps, etc. The steps could be programmed to terminate and move to a next step upon reaching a specified set point, such as the reactor temperature

Crystal habits were observed using a Nikon Polarizing Microscope Eclipse 50i POL and photomicrographs were taken on a Nikon Digital Sight DS-Fi1 digital camera. Figure 1 shows a schematic representation of the experimental setup for phenacetin crystallization

In the experiments described below, in which seeding was used, crystals obtained from water were used as seed crystals because they typically have a plate-like habit. The platelike habit provides a greater surface area for growth and so is more suitable for seeds than the needle-like habit obtained from ethanol. The crystals formed from water also have

simple linear cooling regime.

**2. Experimental methods**

or the number of particles observed.

defects.

experiments.

rougher surfaces than the ethanol-derived needles, again assisting crystal growth. In addition, any differences in habit after the crystallization of phenacetin from ethanol using these seed crystals would assist in the determination of whether growth or nucleation dominated these processes. The seed crystals were sieved to give the size ranges described below using a set of U.S.A. standard testing sieves (Avantech Manufacturing) in mesh sizes of 150 m, 300 m and 500 m. The seeds were added to crystallisations in an ethanol slurry using seed crystals with a weight in grams equal to 20% of the total batch concentration.

Fig. 1. A schematic representation of the experimental setup for phenacetin crystallization experiments.

Only one crystalline form of phenacetin has been reported to date (Hansen, 2006). To check that no new polymorphs or solvates of phenacetin were obtained during these experiments, powder X-ray diffraction (PXRD) patterns were recorded for all of the samples and compared with the theoretical pattern generated from the structure reported by Hansen et al. (Hansen, 2006). PXRD was performed at an ambient temperature using a Stoe Stadi MP diffractometer operating in transmission mode with a linear PSD detector, with an anode current of 40 mA, an accelerating voltage of 40 kV and Cu Kα1 X-radiation (λ = 1.5406 Å), typically over a scan range of 3.5° to 60° 2θ, scanning in steps of 2° for 90 s per step. The samples were held between acetate foils. The theoretical patterns were generated from the crystallographic information file downloaded from the Cambridge Structural Database (CSD) - CSD reference code PYRAZB21 - using the THEO function on the Stoe WinXPOW software package. Figure 2 shows a typical example of a PXRD pattern of a phenacetin batch with the theoretical pattern overlaid, with excellent correspondence between the observed and theoretical patterns.

Phenacetin Crystallization: Cooling Regimes and Crystal Morphology 333

Fig. 4. The solubility/super-solubility diagram of phenacetin from ethanol.

Fig. 5. The progression diagram of a heat/cool experiment of phenacetin in ethanol using turbidity counts as a termination clause (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm – and Qz(x) is the lessthan-size for parameter x and weight z, where x is counts and z = 3 is interpreted as the

volume equivalent distribution).

Fig. 2. Comparison of the theoretical PXRD pattern of phenacetin (black) generated from single crystal data (Hansen, 2006; CSD reference code PYRAZB21) overlaid with the experimental pattern (red) of a batch of phenacetin crystallized from ethanol.

## **3. Results and discussion**

### **3.1 Cooling with feedback control**

The metastable zone width (MSZW) of phenacetin from ethanol was first found by a heat / cool experiment in which the concentration was diluted after each heat /cool step until enough data points were collected to plot a solubility/super-solubility diagram. Figure 3 is the experiment progression diagram, illustrating the alternate heating and cooling cyclic programme from which the data points were collected, and Figure 4 is the solubility/supersolubility diagram of phenacetin in ethanol.

Fig. 3. The experiment progression diagram for measuring the metastable zone width (MSZW) of phenacetin in ethanol.

Fig. 2. Comparison of the theoretical PXRD pattern of phenacetin (black) generated from single crystal data (Hansen, 2006; CSD reference code PYRAZB21) overlaid with the experimental pattern (red) of a batch of phenacetin crystallized from ethanol.

The metastable zone width (MSZW) of phenacetin from ethanol was first found by a heat / cool experiment in which the concentration was diluted after each heat /cool step until enough data points were collected to plot a solubility/super-solubility diagram. Figure 3 is the experiment progression diagram, illustrating the alternate heating and cooling cyclic programme from which the data points were collected, and Figure 4 is the solubility/super-

Fig. 3. The experiment progression diagram for measuring the metastable zone width

**3. Results and discussion**

**3.1 Cooling with feedback control**

solubility diagram of phenacetin in ethanol.

(MSZW) of phenacetin in ethanol.

Fig. 4. The solubility/super-solubility diagram of phenacetin from ethanol.

Fig. 5. The progression diagram of a heat/cool experiment of phenacetin in ethanol using turbidity counts as a termination clause (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm – and Qz(x) is the lessthan-size for parameter x and weight z, where x is counts and z = 3 is interpreted as the volume equivalent distribution).

Phenacetin Crystallization: Cooling Regimes and Crystal Morphology 335

Fig. 7. Design of an experiment showing the proposed heating and cooling path using turbidity counts as the termination clause for each step (the red dot indicates the point of

Fig. 8. The experiment progression diagram of a seeded phenacetin crystallization in ethanol using turbidity counts as a termination clause (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm - and Qz(x) is the less-than-size for parameter x and weight z, where x is counts and z = 3 is interpreted as the

The use of turbidity counts as the terminating step to control the temperature in seeded phenacetin crystallizations resulted in a more controlled experiment. The crystallization was

seeding).

volume equivalent distribution)

Our first experiments were undertaken using the phenacetin crystallizations in ethanol involved controlling the crystallization using turbidity counts as a termination clause for each heating and cooling step. The first experiment involved a batch without seeding. Phenacetin, at a concentration of 50 g L-1, was dissolved in ethanol, stirred at 180 rpm and followed by a slow cool at -0.5 °C / min until the phenacetin crystallized out of solution. The termination clause was set on the cooling step so that the cooling was terminated when the turbidity counts exceeded a set number. In this case, the programme was set to cool until the crystal population reached a turbidity of 300 counts / s. Once the turbidity counts reached the pre-set level, the experiment began to heat again until the turbidity counts dropped below another pre-set number. In this experiment, the lower limit was set at 290 counts / s, thereby terminating the step and beginning the cooling process once again. Ideally, this cyclic heating and cooling should be continued until a steady state is reached, which should result in a crystallization process where the turbidity counts are maintained at the pre-set number. Figure 5 gives this experiment's progression diagram of phenacetin in ethanol under this regime.

Using turbidity counts as the terminating clause for controlling the temperature in crystallization batches that were not seeded proved difficult. The temperature response to this terminating clause was slow, causing large fluctuations in the turbidity counts and the fine and medium total particle counts. The coarse particle counts remained relatively stable. The crystals collected at the end of the experiment were needles of varying size. PXRD analysis proved that no new forms of phenacetin were present. Since the experiment was carried out in ethanol, the crystallization of needle shaped crystals was expected. Figure 6 is a photomicrograph of the crystals collected at the end of the experiment.

Fig. 6. Photomicrograph of crystals at the end of the experiment from a batch of a phenacetin crystallization without seeding.

It was then proposed to seed a phenacetin crystallization experiment, using the same conditions as before and with seeds of varying sizes, in order to see if better control could be achieved. It was decided to use phenacetin crystals obtained from water as the seed crystals because they typically have a plate-like habit. Any differences in habit after the crystallization of phenacetin from ethanol using these seed crystals would assist the determination of whether growth or nucleation was dominating these processes. Figure 7 is an experimental design showing the proposed heating and cooling path in the seeded experiment and Figure 8 is the experiment progression diagram of a seeded phenacetin crystallization in ethanol using turbidity counts as the termination clause.

Our first experiments were undertaken using the phenacetin crystallizations in ethanol involved controlling the crystallization using turbidity counts as a termination clause for each heating and cooling step. The first experiment involved a batch without seeding. Phenacetin, at a concentration of 50 g L-1, was dissolved in ethanol, stirred at 180 rpm and followed by a slow cool at -0.5 °C / min until the phenacetin crystallized out of solution. The termination clause was set on the cooling step so that the cooling was terminated when the turbidity counts exceeded a set number. In this case, the programme was set to cool until the crystal population reached a turbidity of 300 counts / s. Once the turbidity counts reached the pre-set level, the experiment began to heat again until the turbidity counts dropped below another pre-set number. In this experiment, the lower limit was set at 290 counts / s, thereby terminating the step and beginning the cooling process once again. Ideally, this cyclic heating and cooling should be continued until a steady state is reached, which should result in a crystallization process where the turbidity counts are maintained at the pre-set number. Figure 5 gives this experiment's progression diagram of phenacetin in ethanol under this regime.

Using turbidity counts as the terminating clause for controlling the temperature in crystallization batches that were not seeded proved difficult. The temperature response to this terminating clause was slow, causing large fluctuations in the turbidity counts and the fine and medium total particle counts. The coarse particle counts remained relatively stable. The crystals collected at the end of the experiment were needles of varying size. PXRD analysis proved that no new forms of phenacetin were present. Since the experiment was carried out in ethanol, the crystallization of needle shaped crystals was expected. Figure 6 is

Fig. 6. Photomicrograph of crystals at the end of the experiment from a batch of a phenacetin

It was then proposed to seed a phenacetin crystallization experiment, using the same conditions as before and with seeds of varying sizes, in order to see if better control could be achieved. It was decided to use phenacetin crystals obtained from water as the seed crystals because they typically have a plate-like habit. Any differences in habit after the crystallization of phenacetin from ethanol using these seed crystals would assist the determination of whether growth or nucleation was dominating these processes. Figure 7 is an experimental design showing the proposed heating and cooling path in the seeded experiment and Figure 8 is the experiment progression diagram of a seeded phenacetin

crystallization in ethanol using turbidity counts as the termination clause.

a photomicrograph of the crystals collected at the end of the experiment.

crystallization without seeding.

Fig. 7. Design of an experiment showing the proposed heating and cooling path using turbidity counts as the termination clause for each step (the red dot indicates the point of seeding).

Fig. 8. The experiment progression diagram of a seeded phenacetin crystallization in ethanol using turbidity counts as a termination clause (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm - and Qz(x) is the less-than-size for parameter x and weight z, where x is counts and z = 3 is interpreted as the volume equivalent distribution)

The use of turbidity counts as the terminating step to control the temperature in seeded phenacetin crystallizations resulted in a more controlled experiment. The crystallization was

Phenacetin Crystallization: Cooling Regimes and Crystal Morphology 337

Fig. 10. An experiment design illustrating the pre-set path of the cyclic heating and cooling

Fig. 11. Experiment progression diagram of the seeded (crystals between 150-300 μm) phenacetin crystallization from ethanol using a pre-set cyclic plan (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm - and Qz(x) is the less-than-size for parameter x and weight z, where x is counts and z

The experiment progression diagram shows the point of seeding as the point where there is a simultaneous increase in the turbidity counts (the black line), the medium-sized particles (the pink line indicating particles between 80-150 μm) and the coarse particles (light blue

programme for phenacetin crystallizations in ethanol.

= 3 is interpreted as the volume equivalent distribution).

slowly cooled to within the solubility limit at a cooling rate of -0.5 °C / min. The batch was seeded with phenacetin crystals of various sizes and the crystallization was rapidly cooled at a rate of -5 °C / min. When the turbidity counts exceeded the stated level - which in this experiment was a turbidity of 200 counts / s - the process began to heat, causing the dissolution of fines and medium particles. Once the turbidity counts had reached the desired level (190 counts / s), cooling began again. The coarse and medium particles began to rise (indicating growth) while the fines remained steady. Figure 9 shows photomicrographs of the seed crystals, which are of varying size, and the end of experiment crystals, which show a more uniform crystal size and are no longer needle-like. The final crystals have a regular prismatic habit, unlike than the needles obtained from ethanol without seeding or the plates obtained from water. This reflects the operation of crystal growth from ethanol on plate-like seeds obtained from water, generating a new and more desirable prismatic habit.

Fig. 9. Photomicrographs of (a) the seed crystals of phenacetin of varying sizes and (b) end of experiment crystals.

## **3.2 Cyclic cooling**

The next series of experiments used cyclic cooling paths that had predefined temperature parameters, ensuring that a cyclic temperature profile was maintained within the MSZW limits. Rather than using the turbidity counts as a termination clause, these experiments followed plans that were programmed before the experiment began, using the data from the MSZW diagram to find the temperature limits. Figure 10 shows the design of the experiment for this crystallization.

In order to achieve the best control, it was decided to carry out a series of phenacetin crystallizations from ethanol, keeping the crystallization conditions constant throughout but varying the seed crystals. Each experiment was seeded with crystals that were sieved to give a specific size range. The three size ranges used were seed crystals under 150 μm, between 150-300 μm and over 500 μm. All of the crystallization experiments were seeded with crystals grown from water and added to an ethanol slurry using seed crystals with a weight in grams equal to 20% of the total batch concentration. Figure 11 gives the experiment progression diagram of the phenacetin crystallization from ethanol that was seeded with crystals grown from water within the size range 150-300 μm.

slowly cooled to within the solubility limit at a cooling rate of -0.5 °C / min. The batch was seeded with phenacetin crystals of various sizes and the crystallization was rapidly cooled at a rate of -5 °C / min. When the turbidity counts exceeded the stated level - which in this experiment was a turbidity of 200 counts / s - the process began to heat, causing the dissolution of fines and medium particles. Once the turbidity counts had reached the desired level (190 counts / s), cooling began again. The coarse and medium particles began to rise (indicating growth) while the fines remained steady. Figure 9 shows photomicrographs of the seed crystals, which are of varying size, and the end of experiment crystals, which show a more uniform crystal size and are no longer needle-like. The final crystals have a regular prismatic habit, unlike than the needles obtained from ethanol without seeding or the plates obtained from water. This reflects the operation of crystal growth from ethanol on plate-like seeds obtained from water, generating a new and more

(a) (b)

Fig. 9. Photomicrographs of (a) the seed crystals of phenacetin of varying sizes and (b) end

The next series of experiments used cyclic cooling paths that had predefined temperature parameters, ensuring that a cyclic temperature profile was maintained within the MSZW limits. Rather than using the turbidity counts as a termination clause, these experiments followed plans that were programmed before the experiment began, using the data from the MSZW diagram to find the temperature limits. Figure 10 shows the design of the

In order to achieve the best control, it was decided to carry out a series of phenacetin crystallizations from ethanol, keeping the crystallization conditions constant throughout but varying the seed crystals. Each experiment was seeded with crystals that were sieved to give a specific size range. The three size ranges used were seed crystals under 150 μm, between 150-300 μm and over 500 μm. All of the crystallization experiments were seeded with crystals grown from water and added to an ethanol slurry using seed crystals with a weight in grams equal to 20% of the total batch concentration. Figure 11 gives the experiment progression diagram of the phenacetin crystallization from ethanol that was seeded with

desirable prismatic habit.

of experiment crystals.

experiment for this crystallization.

crystals grown from water within the size range 150-300 μm.

**3.2 Cyclic cooling**

Fig. 10. An experiment design illustrating the pre-set path of the cyclic heating and cooling programme for phenacetin crystallizations in ethanol.

Fig. 11. Experiment progression diagram of the seeded (crystals between 150-300 μm) phenacetin crystallization from ethanol using a pre-set cyclic plan (F is the number of particles inside the given size range - e.g., the size range 0.00-80.00 is the content between 0 - 80 μm - and Qz(x) is the less-than-size for parameter x and weight z, where x is counts and z = 3 is interpreted as the volume equivalent distribution).

The experiment progression diagram shows the point of seeding as the point where there is a simultaneous increase in the turbidity counts (the black line), the medium-sized particles (the pink line indicating particles between 80-150 μm) and the coarse particles (light blue

Phenacetin Crystallization: Cooling Regimes and Crystal Morphology 339

of the crystals falling under a mean crystal size. Figure 13 gives the particle size distributions

Fig. 13. Crystal size distributions of crystals shortly after the experiment is seeded (series 1)

distribution and indicating growth (inset is a bar chart of the D10, D50 and D90 distributions

The crystal size distributions in Figure 13 show an upward shift in the particle size from the beginning of the experiment (series 1) to the end of the experiment (series 2), which is indicative of growth. Also shown in Figure 13 are the distributions D10 (meaning the size under which 10% of the crystal population falls), D50 (the size under which 50% of the crystal population falls) and D90 (the size under which 90% of the crystal population falls). The inset of Figure 13 gives these size distributions for the crystal population at the beginning of the experiment, after the cyclic heat/cool program and at the end of the experiment. It agrees with the particle size distributions and also indicates growth. Figure 14

The photographs of the crystals at the beginning and the end of the experiment show the growth of those seed crystals that began plate-like and then grew to elongated plate-like needles. The difference in size also indicates growth. When we take the seed crystal into consideration, we can see that the crystals are flat and plate-like in shape, with round edges and a rough surface. In contrast, the end of experiment crystals tend to be elongated plate-

and at the end of the experiment (series 2), showing an increase in the particle size

displays photomicrographs of a seed crystal and an end of experiment crystal.

like needles with a rigid, defined shape and a smooth surface.

at three points throughout the experiment).

of the crystals at the beginning and at the end of the experiment.

line indicating particles between 150-1000 μm). It should be noted that at this point there is no increase in the fine particles (the dark blue line indicating particles between 0-80 μm). This is expected as the crystallization is seeded when the temperature just reaches the limit of the solubility curve, indicating a saturated solution and that spontaneous nucleation has not occurred. Therefore, the only particles in the solution are the seed crystals. Since these crystals are within the size range of 150-300 μm, no fine particles are present at this stage. As the solution is cooled in a cyclic heat/cool manner, any nucleation will register a rise in the counts for the fraction, indicating fine particles (the dark blue line). It can be seen from the above diagram that the dark blue line stays close to the baseline throughout the experiment, with some small intermittent increases, indicating that a small amount of nucleation occurs when the crystallization is cooling and that these fine particles are being dissolved during heating. This illustrates that this cyclic heating and cooling program is effective in controlling the nucleation process and riding the sample of fine particles, which tend to be problematic when filtering large scale crystallizations. This experiment progression diagram shows that throughout the crystallization, the mediumsized particles (the pink line) are maintained at a steady level with a slight increase in the coarse particles (the light blue) indicating growth. Figure 12 presents photomicrographs of the seed crystals grown from water and the end of experiment crystals.

Fig. 12. Photomicrographs of (a) seed crystals between 150-300 μm and (b) end of experiment crystals.

The experiment was seeded with crystals grown from water which were plate-like in shape, and the end of experiment crystals were elongated plate-like needles. If nucleation occurs after the experiment was seeded, then these crystals will be very needle-like in shape. If the crystallization predominantly favours growth, then those seed crystals that are plate-like to begin with would have a distorted shape due to the solvent effects on the phenacetin crystals. In theory, if very fine particles precipitate during the cooling process, indicating nucleation, then these would be dissolved on the heating step. This continual heating and cooling would ensure that enough time is given to the growth of the seed crystals, while at the same time ridding the crystallization process of fine particles. The heating cycle would also ensure that the very large crystals are dissolved slightly - thereby reducing their size - the result of which would likely be a crystal batch where there is a good crystal size distribution, with the majority

line indicating particles between 150-1000 μm). It should be noted that at this point there is no increase in the fine particles (the dark blue line indicating particles between 0-80 μm). This is expected as the crystallization is seeded when the temperature just reaches the limit of the solubility curve, indicating a saturated solution and that spontaneous nucleation has not occurred. Therefore, the only particles in the solution are the seed crystals. Since these crystals are within the size range of 150-300 μm, no fine particles are present at this stage. As the solution is cooled in a cyclic heat/cool manner, any nucleation will register a rise in the counts for the fraction, indicating fine particles (the dark blue line). It can be seen from the above diagram that the dark blue line stays close to the baseline throughout the experiment, with some small intermittent increases, indicating that a small amount of nucleation occurs when the crystallization is cooling and that these fine particles are being dissolved during heating. This illustrates that this cyclic heating and cooling program is effective in controlling the nucleation process and riding the sample of fine particles, which tend to be problematic when filtering large scale crystallizations. This experiment progression diagram shows that throughout the crystallization, the mediumsized particles (the pink line) are maintained at a steady level with a slight increase in the coarse particles (the light blue) indicating growth. Figure 12 presents photomicrographs of

(a) (b)