Technical Report 176, c4e-Preprint Series, Cambridge

Detailed Population Balance Modelling of TiO2 Synthesis in an Industrial Reactor

ref: Technical Report 176, c4e-Preprint Series, Cambridge

Authors: Astrid Boje, Jethro Akroyd, Stephen Sutcliffe, John Edwards, and Markus Kraft

Associated Themes: Nanoparticles and Particle Processes

  • An industrial titania reactor is modelled
  • A reactor network is used to describe localised flow, composition and temperature
  • A multivariate particle description is used, enabling characteristics of particle shape and size to be explored in detail
  • A short process parameter study is performed, demonstrating the potential to investigate the effect of operational choices on product characteristics.

abstractThis paper uses a network of ideal flow reactors and a detailed population balance model to study the evolution of the size and shape distributions of pigmentary titanium dioxide, formed under industrial synthesis conditions. The industrial reactor has multiple reactant injections, a tubular working zone in which the exothermic reaction is completed, and a cooling zone. A network of continuously stirred tank reactors is used to model variation in composition around the feeds and plug flow reactors with prescribed temperature gradients are used to describe the working and cooling zones. The quality of the industrial product depends on its morphology, and this is influenced by factors including temperature and throughput. In this paper, a multivariate particle model is accommodated using a stochastic method and the particle morphology is characterized in terms of the distributions of primary and aggregate particle diameters, number of primary particles per particle and neck radii of connected primary particles. Increasing temperature or residence time is shown to produce larger particles. Qualitative similarities are highlighted between such findings and previous studies. The throughput studies are also in qualitative agreement with empirical industrial experience. There is scope for extending and improving the current model; however, it is suggested that insights of this type could be used to inform the design and operation of the industrial process.

Material from this preprint has been published in: Chemical Engineering Science 164, 219–231, (2017)


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