How to measure supersaturation?

doi:10.1016/S0009-2509(02)00347-0

Chemical Engineering Science

Volume 57, Issue 20, October 2002, Pages 4301-4310

https://doi.org/10.1016/S0009-2509(02)00347-0 Get rights and content

Abstract

The existing methods for the measurement of supersaturation can be generalized insofar that physical properties are used that show a dependence on concentration of the measurands for supersaturation. The influence of impurities, foreign particles, or ions on the metastable zone width and on the kinetics of nucleation and crystal growth cannot be detected by most of the described methods. Thus, it is necessary to develop a supersaturation sensor which considers the actual crystallization process itself in its measurement method. The idea of that is to induce crystallization on the surface of the sensor by generating an additional supersaturation by cooling and to observe the time-dependent development of the formation of solid matter on the surface which leads finally to incrustation. Assuming a constant cooling rate and constant properties of the sensor surface, the starting time of the incrustation on the sensor surface depends only on the prevailing supersaturation in the process solution. Experimental results obtained for inorganic (KNO₃) and organic (adipic acid) crystallizing solutes proved the working of the new sensor.

Introduction

As the thermodynamic driving force, supersaturation is the most decisive parameter for crystallization processes. It has a tremendous influence on mechanisms occurring during a crystallization process like:

•
crystal growth,
•
agglomeration and aggregation, and
•
primary and secondary nucleation.

Therefore, the product quality characterized by

•
crystal morphology,
•
crystal purity,
•
specific surface area, and
•
crystal size distribution

can be defined by means of measuring and controlling the prevailing supersaturation during the whole crystallization process.

Nevertheless, in many batch cooling crystallization processes natural, linear or precalculated cooling rates are used to generate supersaturation. By applying one of these cooling methods, it is not possible to keep supersaturation throughout the crystallizer at an optimum level. Furthermore, no knowledge of the exact moment of seeding in batch crystallizers exists. Only the application of supersaturation sensors gives the possibility to add seed when supersaturation is obtained Kühberger 1997, Kühberger 1999.

Table 1 gives a short overview of the existing supersaturation measurement methods.

In Table 1 each described method has restrictions regarding its applicability, like certain ranges of temperature, turbidity, viscosity, or suspension density. As can be seen, a lot of different measurands for determining supersaturation are available, but all of them use physical properties (such as density, viscosity or electric conductivity) that show a dependence on concentration in order to obtain the actual level of supersaturation with the help of solubility data. Therefore, all existing measurement methods are more or less concentration measurements which are applicable in pure systems. The actual extent of the driving force of crystallization, the supersaturation, cannot be quantified. Additionally, these concentration-dependent measurement methods require a solubility diagram of the system valid for the actual composition including all impurities. In case of changing or alternating compositions of the mother liquor, this requirement is very hard to fulfil.

A schematic measuring procedure can be seen from Fig. 1. The crystallization process in itself is not considered in the various measurement principles. In case of alternating compositions or changing impurities of the mother liquor, solubility data for each possible composition or impurity would be required, if the right supersaturation should be determined by the way described above.

If impurities (e.g. foreign particles) or other process disturbances exist, the measuring of supersaturation using physical properties of the solution still results in the same value as before. However, it is well known that such impurities influence the metastable zone width and the kinetics of nucleation and crystal growth. As a consequence, the crystallization performance changes without any chance of reacting in adequate time to avoid a reduction of the product quality.

Section snippets

Measuring method

One possible way to gather the complete information of all parameters influencing crystallization processes, including the supersaturation, is to induce a crystallization on the surface of the sensor and to observe the development in time of the first deposition of solid matter which finally leads to incrustation. Therefore, the basic idea of the new measurement method is to conduct an accelerated crystallization according to the current process and to observe it. The main idea is illustrated

Sensors

In the first functional prototype, two different devices for the detection of the incrustation on the sensor surface, the interdigital transducer (IDT) and the surface acoustic wave sensor (SAW), were integrated.

Experiments

Intention of the first experiments was to prove the applicability of the sensor and to test the reproducibility of the measurements. Thus, it was necessary to provide constant conditions for these experiments. For this reason the experiments were performed in beakers (no fluid flow) containing KNO₃ solutions of various degrees of undersaturation. Expressing the concentration in an undercooling with respect to the saturation temperature $T^{∗}$ and keeping these solutions at a constant temperature of

Conclusions

The experiments with potassium nitrate showed the working of the measurement method and the ability of the new sensor to determine different degrees of saturation. The results of the monitored batch cooling crystallizations of adipic acid demonstrated the high potential and applicability of the system. The major advantage of this sensor lies in the direct measurement of the driving force (and not of a concentration) of crystallization including every influence caused by impurities or other

Notation

$C$	concentration, $kmol / m^{3}$
$C^{∗}$	solubility, $kmol / m^{3}$
$f$	frequency, Hz
$t$	time, s
$T$	temperature, K
$T^{∗}$	saturation temperature, K
$T ̇$	cooling rate, K/s
$Z$	impedance, $Ω$

Greek letters

$ε_{r}$	specific inductive capacity
$κ$	electric conductivity, S/m
$η$	dynamic viscosity, Pa s
$ρ$	density, $kg / m^{3}$

Superscripts and subscripts

meas	measurement
proc	process
sensor	sensor
signal	signal
start	start
sol	solution

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Improved product quality at a cooling crystallization process by measurement and control of supersaturation
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This parameter is known to be process dependent and can be influenced by numerous factors including cooling rate, solvent composition, mechanical agitation, impurities in the solution, etc. (Nyvlt et al., 1985). Many process analytical technologies (PATs) have been developed in the past decade for in situ determination of the MZW during solution crystallization processes (Kumar et al., 1996; Groen and Roberts, 2001; Lewiner et al., 2001; Fujiwara et al., 2002; Löffelmann and Mersmann, 2002; Marciniak, 2002; Gürbüz and Özdemir, 2003; Parsons et al., 2003; Genceli et al., 2005; Pöllänen et al., 2006; Schöll et al., 2006; O’Grady et al., 2007; Simon et al., 2009a). These techniques include, but are not limited to, direct visual observation using hot stage microscopy (HSM) (Kumar et al., 1996), in-process video microscopy (PVM) (Barrett and Glennon, 2002) and bulk video imaging (Simon et al., 2009b); detection of the presence of solid particles using focused beam reflectance measurement (FBRM) (Fujiwara et al., 2002; Schöll et al., 2006; O’Grady et al., 2007) and turbidity meter (Parsons et al., 2003); thermal method using differential scanning calorimeter (DSC) (Myerson and Jang, 1999); and monitoring of the solute concentration change via bulk solution property measurements using attenuated reflection-Fourier transform infrared (ATR-FTIR) (Groen and Roberts, 2001; Lewiner et al., 2001; Fujiwara et al., 2002; Pöllänen et al., 2006; Schöll et al., 2006; O’Grady et al., 2007; Trifkovica et al., 2009), ultra-violet–visible (UV–vis) spectroscopy (Simon et al., 2009a), densitometer (Marciniak, 2002), ultrasonic velocity meter (Marciniak, 2002; Gürbüz and Özdemir, 2003), quartz crystal sensor (Löffelmann and Mersmann, 2002), conductivity and refractive index meter (Genceli et al., 2005), etc.
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Various process analytical technologies (PATs) have been utilized for MSZW determination during solution crystallization processes. Commonly used PATs include turbidity meter (Parsons et al., 2003) and focused beam reflectance measurement (FBRM) (Barrett and Glennon, 2002; Fujiwara et al., 2002; Schöll et al., 2006; O’Grady et al., 2007), which rely on the detection of solid particles; attenuated total reflection-Fourier transform infrared (ATR-FTIR) (Groen and Roberts, 2001; Lewiner et al., 2001; Fujiwara et al., 2002; Pöllänen et al., 2006; Schöll et al., 2006; O’Grady et al., 2007), densitometer (Marciniak, 2002), ultrasonic velocity meter (Marciniak, 2002; Gürbüz and Özdemir, 2003), quartz crystal sensor (Löffelmann and Mersmann, 2002), conductivity and refractive index meter (Genceli et al., 2005), which monitor the bulk solution properties. Other techniques include direct visual observation using hot stage microscopy (HSM) (Kumar et al., 1996), bulk video imaging (Simon et al., 2009) and in-process video microscopy (PVM) (Barrett and Glennon, 2002).
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