Industrial Crystallization Process Monitoring and Control
eBook - ePub

Industrial Crystallization Process Monitoring and Control

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Industrial Crystallization Process Monitoring and Control

About this book

Crystallization is an important technique for separation and purification of substances as well as for product design in chemical, pharmaceutical and biotechnological process industries. This ready reference and handbook draws on research work and industrial practice of a large group of experts in the various areas of industrial crystallization processes, capturing the essence of current trends, the markets, design tools and technologies in this key field. Along the way, it outlines trouble free production, provides laboratory controls, analyses case studies and discusses new challenges. First the instrumentation and techniques used to measure the crystal size distribution, the nucleation and solubility points, and the chemical composition of the solid and liquid phase are outlined. Then the main techniques adopted to control industrial crystallizers, starting from fundamental approaches to the most advanced ones, including the multivariable predictive control are described. An overview of the main crystallizer types is given with details of the main control schemes adopted in industry as well as the more suitable sensors and actuators.

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Yes, you can access Industrial Crystallization Process Monitoring and Control by Angelo Chianese,Herman J. Kramer in PDF and/or ePUB format, as well as other popular books in Physical Sciences & Industrial & Technical Chemistry. We have over one million books available in our catalogue for you to explore.

Information

Chapter 1
Characterization of Crystal Size Distribution
Angelo Chianese

1.1 Introduction

Crystalline population coming out from a crystallizer is characterized by its size distribution, which can be expressed in different ways. The crystal size distribution (“CSD”) may, in fact, be referred to the number of crystals, the volume or the mass of crystals with reference to a specific size range, or the cumulative values of number, volume or mass of crystals up to a fixed crystal size. The first approach refers to a density distribution, whereas the second one to a cumulative size distribution.
However, it is also useful to represent the CSD by means of a lumped parameter as an average size, the coefficient of variation, or other statistical parameters which may be adopted for the evaluation of a given commercial product.
In this section the more usual ways to represent both the whole CSD and the lumped CSD parameters are presented.

1.2 Particle Size Distribution

The particle size distribution may be referred to the density distribution or cumulative distribution. Each distribution may be expressed in number, volume, or mass of crystals.
The cumulative variable, F(L), expresses number, volume, or mass of crystals per unit slurry volume between zero size and the size L, whereas the density distribution function, f(L), refers to number, mass, or volume of crystals per unit slurry volume in a size range, whose average size is L.
The relationship between the cumulative size variable and the density distribution size one is as follows:
1.1
1.1
or in the reverse form:
1.2
1.2
In Table 1.1 the expression of cumulative and density function variables referred to the number, volume, or mass of crystals is reported.
Table 1.1 Cumulative and density variables.
1.1
Examples of number and volume distributions are reported in Figure 1.1.
Figure 1.1 Cumulative and volume crystal size distributions (continuous line for the cumulative distribution and dotted lines for the density distribution).
1.1
In spite of the three geometric dimensions of crystals, the CSD is usually referred to just one dimension, the so-called characteristic one, which is related to the adopted measurement technique. In the case of crystal size measurement by sieving the characteristic dimension is the second one, corresponding to the wire mesh length. Otherwise, if a laser diffraction-based analyzer is used, the characteristic dimension is the length given by the instrument, falling between the first and the second crystal dimension.
The most used density distribution variable is the crystal population density, n(L). It can be used to estimate the total number, NT, the total ...

Table of contents

  1. Cover
  2. Related Titles
  3. Title Page
  4. Copyright
  5. Preface
  6. Scope of the Book
  7. List of Contributors
  8. Chapter 1: Characterization of Crystal Size Distribution
  9. Chapter 2: Forward Light Scattering
  10. Chapter 3: Focused Beam Reflectance Measurement
  11. Chapter 4: Turbidimetry for the Estimation of Crystal Average Size
  12. Chapter 5: Imaging
  13. Chapter 6: Turbidimetry and Nephelometry
  14. Chapter 7: Speed of Sound
  15. Chapter 8: In-Line Process Refractometer for Concentration Measurement in Sugar Crystallizers
  16. Chapter 9: ATR-FTIR Spectroscopy
  17. Chapter 10: Raman Spectroscopy
  18. Chapter 11: Basic Recipe Control
  19. Chapter 12: Seeding Technique in Batch Crystallization
  20. Chapter 13: Advanced Recipe Control
  21. Chapter 14: Advanced Model-Based Recipe Control
  22. Chapter 15: Fines Removal
  23. Chapter 16: Model Predictive Control
  24. Chapter 17: Industrial Crystallizers Design and Control
  25. Index