Granular segregation is a common and costly challenge among industries dealing with particulate materials. Controlling segregation requires a deep understanding of its underlying mechanisms. Gaining this understanding, experimentally, is challenging especially for polydisperse systems, where at least one of the main ingredients is in low-level content and highly prone to segregation. In this regard validated numerical simulations could overcome the limitations of the experimental techniques in analysing the segregation and its root causes.
A relevant example is the segregation of enzyme granules with low-level content (less than 2% by weight) in laundry detergent powders which has cost and health issues for the production as well as consumers. This study focuses on predicting, analysing, and controlling the segregation tendency of minor active ingredients in polydisperse formulated powder mixtures, using high-fidelity numerical simulations. An extensive literature review is carried out on the capabilities and shortcomings of the available numerical methods; where the Discrete Element Method (DEM) is found to be the most suitable tool for mimicking the segregation phenomenon in this research project.
The segregation of the main ingredients of the conventional home washing powders (i.e. Blown powder (BP), tetraacetylethylenediamine (TAED), and enzyme granules) during the heap formation and vibration processes is investigated using DEM modelling. The particles properties including size, density, shape, and surface properties are measured experimentally, where possible, and the values are calibrated for the DEM simulations. The results are validated against experiments, where the Enzyme Placebo granules (EP) are used instead of the real enzyme for the health and safety reasons.
As a part of this study, the significance of using particle shape in simulations instead of employing spheres with calibrated rolling friction is investigated. To simulate shape in DEM, particles are scanned using X-Ray Tomography technique (XRT) and their shapes are approximated by the clumped-sphere method. The results reveal that considering the particle shape in simulations is a necessity, as the clumped-sphere approach reliably predicts the segregation during the heap formation; whereas, the rolling friction approach underestimates the particles segregation tendency.
In the second part of this study, a special attention is paid to minimising the segregation of the minor ingredient, i.e. EP granules, which constitutes less than 2% of the weight of the mixture and is highly prone to segregation. This is investigated through 1) making the EP granules cohesive by tackifying agents as well as 2) manipulating their shapes.
For the DEM simulation of the multi-component system with the cohesive EP granules, the interfacial energies of the components are inferred by matching the experimental and simulated repose angles. In addition, a dimensionless Cohesion number is introduced, based on the ratio of the particles cohesion energy and gravitational potential energy, to scale the interfacial energy when reducing Young’s modulus or changing the particle size for minimising the computation time.
As a result of implementing a careful calibration methodology, a good match between the numerical and experimental analyses of the segregation of minor ingredient is observed. The results show that before coating, the EP granules easily penetrate into the top moving layers of the powder mixture during the heap formation, and therefore, segregate to the central area of the heap. This occurs due to their high density and round shape (push-away effect), leaving the corners and side walls with a lower mass concentration. However, both approaches of coating EP granules and making their shapes irregular reduce their ability to penetrate the powder bed, and hence, they are well distributed over the entire heap. It is observed via DEM simulations that manipulating shapes of minor ingredients in a mixture is a possible alternative to the coating approach. Less compromise in flowability of powder mixture and less exposure to variation in surface properties through time are two main advantages of the shape manipulation. Nevertheless, manufacturing particles which have a designed shape is more complex and costly compared to the coating approach. It is concluded that securing a reliable and predictive DEM simulation of segregation of formulated powder mixtures is possible only if the DEM input parameters are 1) justifiably selected and 2) precisely calibrated.
