Crystallization and precipitation engineering

doi:10.1016/j.compchemeng.2005.02.022

Computers & Chemical Engineering

Volume 29, Issue 6, 15 May 2005, Pages 1159-1166

https://doi.org/10.1016/j.compchemeng.2005.02.022 Get rights and content

Abstract

New computational techniques for the analysis and design of systems for the manufacture of particulate crystals have become available, and the more complex precipitation processes whereby crystallization follows fast chemical reactions have also been analysed more deeply. This progress has been aided by the growing power of the population balance and kinetic models, computational fluid dynamics (CFD) and mixing theory, respectively. These aspects are selectively reviewed and areas requiring further progress are identified.

Introduction

Crystallization from solution is a core technology in major sectors of the chemical process and allied industries. Crystals are produced in varying sizes ranging from as small as a few tens of nanometres to several millimetres or more, both as discrete particles and as structured agglomerates. Well-established examples include bulk and fine chemicals and their intermediates, such as common salt, sodium carbonate, zeolite catalysts and absorbents, ceramic and polyester precursors, detergents, fertilisers, foodstuffs, pharmaceuticals and pigments. Applications that are more recent include crystalline materials and substances for electronics devices, healthcare products and a wide variety of speciality applications.

Thus, the tonnage and variety of particulate crystal products worldwide is enormous, amounting to possibly more than half the product of the modern chemical industry. The economic value, social benefit and technical sophistication of crystal products and processes are ever increasing, particularly in the newer high added value sectors of global markets. This places yet greater demands on the skill and ingenuity of the scientist and engineer to form novel materials of the required product characteristics and devise viable process engineering schemes for their manufacture (Jones, 2002).

Previously, a largely empirical art, the design of process systems for manufacturing particulate crystals has now begun to be put on a rational basis, and the more complex precipitation processes whereby crystallization follows fast chemical reactions have also been analysed more deeply. This progress has been aided by the growing power of the population balance and kinetic models, computational fluid dynamics and mixing theory. This not only increases understanding of existing processes but also enhances the possibility of innovative product and process designs, and speedier times to market.

The process engineering goal for crystallization systems is to develop generic scale-up methodologies to integrate across the length scales—from the formation of primary crystals to industrial scale plant operation. In this selective review, particular attention is paid both to the fundamental mechanisms of mixing and the formulation of computer aided mathematical methods for scale-up, whilst emphasising throughout the continuing need for careful yet efficient practical experimentation to collect basic data; the latter being essential in order to discriminate between competing theories, to inform and validate process models, and to discover the unexpected. Substantial progress has been made in integrating computational fluid dynamics (CFD) with particulate process models but because of the extra dimensionality, however, there remain substantial challenges (Bezzo et al., 2004).

Section snippets

Particulate crystal characteristics

Crystallization is an important separation process that purifies fluids by forming solids. Crystallization is also a particle formation process by which molecules in solution or vapour are transformed into a solid phase of regular lattice structure, which is reflected on the external faces. Crystallization may be further described as a self-assembly molecular building process. Crystallographic and molecular factors are thus very important in affecting the shape (habit), purity and structure of

Fluid-particle transport processes

The formation and subsequent solid–liquid separation of particulate crystals from solution normally involves alternate periods of suspension and sedimentation during which they experience relative fluid-particle motion. Similarly, solid matter may change phase from liquid to solid or vice versa. New particles may be generated or existing ones lost, e.g. in crystallizers or mills. They may be separated from fluids by flow through vessels, e.g. settlers, thickeners or filters. Thus, both the

Conclusion

Combined population balance and kinetic models, computational fluid dynamics and mixing theory enable prediction and scale-up of crystallization and precipitation systems. Though these hybrid approaches represent essentially a compromise, their lifetime is likely to be quite long, as the full CFD solution at each node awaits a radical breakthrough in computer software and hardware technology. Simultaneously, alternatives to conventional agitated vessels for crystallization and precipitation

References (48)

M.H. Al-Rashed et al.
CFD modelling of gas–liquid reactive precipitation
Chemical Engineering Science
(1999)
J. Baldyga et al.
Interaction between chemical reactions and mixing on different scales
Chemical Engineering Science
(1997)
M. Bauer et al.
A concept for multi-scale modelling of bubble columns and loop reactors
Chemical Engineering Science
(1999)
J. Baldyga et al.
Closure problem for precipitation
Transactions of the Institution of Chemical Engineers
(1997)
J. Baldyga et al.
Barium sulphate precipitation in a pipe—an experimental study and CFD modelling
Chemical Engineering Science
(2001)
J. Baldyga et al.
Mixing–precipitation model with application to double feed semibatch precipitation
Chemical Engineering Science
(1995)
J. Baldyga et al.
Turbulent micromixing in chemical reactors—a review
Chemical Engineering Journal
(1995)
F. Bezzo et al.
A general framework for the integration of computational fluid dynamics and process simulation
Computers and Chemical Engineering
(2000)
F. Gelbard et al.
Numerical solution of the dynamic equation for particulate systems
Journal of Computational Physics
(1978)
S. Kumar et al.
On the solution of population balance by discretization II. A moving pivot technique
Chemical Engineering Science
(1996)

A general methodology for hybrid multizonal (CFD) models

Computers and Chemical Engineering

(2004)

A. Brucato et al.

Experimental investigation and CFD simulation of dense solid–liquid suspensions in a fully baffled stirred tank

L. Falk et al.

A PDF modelling of precipitation reactors

Chemical Engineering Science

(2001)

P.J. Hill et al.

New discretization procedure for the breakage equation

American Institution of Chemical Engineers Journal

(1995)

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¹: Present address: Department of Mechanical Engineering, Imperial College London, SW7 2BX, UK.

²: Present address: Austrian Research Centers, A-2444 Seibersdorf, Austria.

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Crystallization and precipitation engineering

Abstract

Introduction

Section snippets

Particulate crystal characteristics

Fluid-particle transport processes

Conclusion

Chemical Engineering Science

Chemical Engineering Science

Chemical Engineering Science

Transactions of the Institution of Chemical Engineers

Chemical Engineering Science

Chemical Engineering Science

Chemical Engineering Journal

Computers and Chemical Engineering

Journal of Computational Physics

Chemical Engineering Science

Chemical Engineering Science

Chemical Engineering Science

Chemical Engineering Science

Chemical Engineering Science

Transactions of the Institution of Chemical Engineers

Computers and Chemical Engineering

A fluid mechanical approach to turbulent mixing and chemical reaction. Part I: Inadequacies of available methods

Chemical Engineering Communications

A fluid mechanical approach to turbulent mixing and chemical reaction. Part II: Micromixing in the light of turbulence theory

Chemical Engineering Communications

A fluid mechanical approach to turbulent mixing and chemical reaction. Part III: Computational and experimental results for the new micromixing model

Chemical Engineering Communications

Turbulent mixing and chemical reactions

A general methodology for hybrid multizonal (CFD) models

Computers and Chemical Engineering

Experimental investigation and CFD simulation of dense solid–liquid suspensions in a fully baffled stirred tank

A PDF modelling of precipitation reactors

Chemical Engineering Science

New discretization procedure for the breakage equation

American Institution of Chemical Engineers Journal