Characterisation and Control of Particle Attributes for Cyber-Physical Systems in Crystallisation Processes

The project will develop an automated workflow for the robust characterisation of particle attributes in crystallisation processes in the presence of impurities. Reliable data on particle attributes such as size, shape and form are essential for process understanding and for the development and validation of process design, scale-up and control strategies.

However, an accurate representation of these characteristics is not always possible due to complexities in measurement environment and sample presentation.

The workflow will incorporate innovative mechanistic and data-driven models for the determination of multidimensional particle size distributions and crystal form from in situ process analytical technologies (PAT), e.g., in-line imaging, chord length distribution measurements and Raman spectroscopy. Established ex situ measurements such as offline microscopy, laser diffraction and X-Ray Powder Diffraction will be leveraged for model validation.

The main strengths and limitations of individual PAT will be investigated while exploring potential fusion strategies through multi-sensor setups. The characterisation framework will consider the influence of impurities on crystallisation outcomes and will span multiple scales to enable scale-up strategies driven by rich data streams from autonomous robotic platforms.

Overall, the aim is to produce the best possible representation of the evolution of particle attributes in crystallisation processes to inform robust and integrated modelling approaches within Cyber-Physical Systems.