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Chemical Process Control

Introduction

The importance of crystallization in the pharmaceutical, food and fine chemical industries stems from its ability to yield highly pure solid products. Beside the final chemical purity, however, the solid state form, the size and the shape of the resulting particles are of paramount importance for the product quality, because they determine characteristics such as filterability, tabletability, flowability and even bioavailability. Practitioners in these industries are well aware of the fact that crystals can take on a variety of shapes, even for the same chemical substance. Any form of control over particle size and especially shape should allow for the design of improved processes. Until recently, however, the optimization of crystallization processes in terms of particle morphology has been hindered by a major obstacle: The lack of reliable, fast and quantitative measurement devices, which prohibited the online monitoring and hence modeling and optimization.

The CrystOCAM project aims to address these limitations by providing setups and analysis protocols that yield reliable, sensitive and accurate data, which can be used, e.g., for optimization and control. To this end, the CrystOCAM project combines the know-how and tools of three groups at ETH Zurich and EPF Lausanne: The Separation Process Laboratory, headed by Prof. Marco Mazzotti (ETHZ), the Automatic Control Laboratory group headed by Prof. Colin Jones (EPFL) and IfA, through Prof. Manfred Morari (ETHZ).

Fig. 1: The Flow Through Cell Setup in the lab, one of the measurement setups designed in the course of CrystOCAM

System Characterization

An important part of the CrystOCAM project is the characterization of systems whose exact behavior has never been accurately and quantitatively monitored before. To this end, new models for the crystallization behavior of complex-shaped particles need to be created and validated against experimental data. Within the scope of this project, a variety of effects has been investigated, ranging from simple, size independent growth mechanisms to studies of growth rate dispersion or agglomeration. Apart from the inherent scientific value of this research, the resulting models can then be used as the basis for reachability analyses, process optimization and control, or simply to provide qualitative lessons regarding the presence and location of (un)desirable process conditions.

Fig. 2: Overview of the PSD reconstruction procedure (adapted from Schorsch et al. (2013))

Optimization and Control

The interest in the optimization and control of particle shape has seen a dramatic rise in research in recent years. With the advent of new imaging tools and efficient numerical algorithms for the modeling of crystal shape, various authors have conducted studies on how to best drive crystal shape towards a desired direction, ex- or implicitly trying to solve the underlying nonlinear, nonconvex optimization task. However, in addition to a notable absence of experimental validation, only a handful of authors has so-far considered the use of novel yet promising process designs to specifically manipulate shape. Such methods could potentially yield a massive enlargement of the attainable particle shape region.
The researchers at ETHZ and EPFL possess the technology, experience and know-how to fill the various gaps currently existing in the optimization and control of crystal shape.