Movement of a secondary immiscible liquid in a suspension using a non-invasive technique

In this paper, the movement of a secondary immiscible liquid when added to a suspension of hydrophilic particles in a continuous hydrophobic phase is investigated. This was achieved through an approach using high speed camera and X-ray computer tomography. These non-invasive approaches allowed the secondary liquid displacement within the suspension to be monitored on the surface level and within the suspension through a time lapse of scans. The addition of a small amount of secondary liquid to suspensions, can lead to a transition from a fluid-like to paste-like structure. The kinetics taking place and responsible for this, during both short and long term storage were investigated to better understand the mechanisms taking place. Water was added as the secondary immiscible liquid to suspensions composed of sucrose (icing sugar) and sunflower oil. Different volumes of secondary liquid were added to the suspensions. The rate of movement as well as the spreading of the secondary liquid into the suspension was calculated from the scans taken. The surface area to volume ratio was proposed as a reason for the spreading of the liquid for the smaller volume droplet being greater in comparison to the larger volume droplet

Studying model suspensions using high resolution synchrotron X-ray microtomography

The addition of minor quantities of secondary liquids to suspensions may lead to a transition from a fluid-like structure to paste-like structure for the system. Previous studies have shown how rheological properties such as viscosity and yield stress are affected, however, qualitative visual observation on the micro-scale during both short and long term storage has yet to be achieved or reported. This research focuses on the movement of a secondary immiscible liquid (water or saturated sucrose solution) when added to a model food system. The model food system used in this study is a suspension of sucrose particles in a continuous oil phase to better understand the interactions between the particles and the liquid phases present. This was accomplished using dynamic X-ray computer tomography to study the behaviour of the sample. This non-destructive approach allowed the movement of the secondary liquid as well as the solid particles from the bulk suspension to be monitored through a time lapse of scans. This was achieved by observing the changes in the grey scale range of the droplet with time, which was then correlated to the uptake and movement of sucrose into the secondary liquid using an innovative method. This movement was due to the hydrophilicity and solubility of sucrose with gravity/sedimentation playing a minimal role

Predictive modelling of the granulation process using a systems-engineering approach

© 2016 Elsevier B.V.The granulation process is considered to be a crucial operation in many industrial applications. The modelling of the granulation process is, therefore, an important step towards controlling and optimizing the downstream processes, and ensuring optimal product quality. In this research paper, a new integrated network based on Artificial Intelligence (AI) is proposed to model a high shear granulation (HSG) process. Such a network consists of two phases: in the first phase the inputs and the target outputs are used to train a number of models, where the predicted outputs from this phase and the target are used to train another model in the second phase to lead to the final predicted output. Because of the complex nature of the granulation process, the error residual is exploited further in order to improve the model performance using a Gaussian mixture model (GMM). The overall proposed network successfully predicts the properties of the granules produced by HSG, and outperforms also other modelling frameworks in terms of modelling performance and generalization capability. In addition, the error modelling using the GMM leads to a significant improvement in prediction

Dem investigation of horizontal high shear mixer flow behaviour and implications for scale-up

In high shear granulation, various dimensionless or dimensioned parameter groups such as constant Froude number, tip speed, relative swept volume and specific energy input are commonly used as scale-up criteria, in order to maintain the powder bed internal flow or stress field across scales. One major challenge is obtaining the internal flow and stress field through experimentation given the lack of precise measurement techniques. Hence, this work employs DEM (discrete element method) simulations to study the internal flow patterns and behaviour of different scale batch, horizontal high shear mixers. The simulations provide a deeper understanding of the interaction of scale, impeller speed and fill level on the flow field, and show that the particle velocity is correlated with the relative swept volume in these mixers. It shows that the relative particle velocity is correlated, independent of scale, to the relative swept volume per rotation and highlights its values as a parameter for understanding and comparing mixer behaviour. The work also demonstrates the importance of the particle size chosen for the simulation as well as the tool-wall gap in the mixer, and highlights its importance as we interpret DEM results