A study of the mixing and segregation mechanisms in the Bohle Tote blender via DEM simulations

Improvement of a pharmaceutical powder mixing process in a tote blender via DEM simulations

An industrial-scale pharmaceutical powder blending process was studied via discrete element method (DEM) simulations. A DEM model of two active pharmaceutical ingredient (API) components and a combined excipient component was calibrated by matching the simulated response in a dynamic angle of repose tester to the experimentally observed response. A simulation of the 25-minute bin blending process predicted inhomogeneous API distributions along the rotation axis of the blending container. These concentration differences were confirmed experimentally in a production-scale mixing trial using high-performance liquid chromatography analysis of samples from various locations in the bin. Several strategies to improve the blend homogeneity were then studied using DEM simulations. Reversing the direction of rotation of the blender every minute was found to negligibly improve the blending performance. Introducing a baffle into the lid at a 45° angle to the rotation axis sped up the axial mixing and resulted in a better final blend uniformity. Alternatively, rotating the blending container 90° around the vertical axis five minutes prior to the process end was predicted to reduce axial segregation tendencies.

Batch versus continuous blending of binary and ternary pharmaceutical powder mixtures

The material properties of excipients and active pharmaceutical ingredients (API's) are important parameters that affect blend uniformity of pharmaceutical powder formulations. With the current shift from batch to continuous manufacturing in the pharmaceutical industry, blending of excipients and API is converted to a continuous process. The relation between material properties and blend homogeneity, however, is generally based on batch-wise blending trials. Limited information is available on how material properties affect blending performance in a continuous process. Here, blending of API and excipients is studied in both a batch and a continuous process. Homogeneity of the resulting mixtures is analyzed, which reveals that the impact of material properties is very different in a continuous process. Where parameters such as particle size, density and flowability have significant impact on blending performance in a traditional batch process, continuous blending is more robust resulting in uniform blends for a large variety of blend compositions.

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Continuous mixing improves blend uniformity of pharmaceutical powder mixtures.

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Blend uniformity is highly dependent on excipient properties in a batch process.

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Continuous mixing is more robust, with little impact of material properties.

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Powder bulk density strongly affects blend homogeneity in a batch process.

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Blending of low API dosages is more challenging in a continuous process.

A comprehensive review of the application of DEM in the investigation of batch solid mixers

Powder mixing is a vital operation in a wide range of industries, such as food, pharmaceutical, and cosmetics. Despite the common use of mixing systems in various industries, often due to the complex nature of mixing systems, the effects of operating and design parameters on the mixers’ performance and final blend are not fully known, and therefore optimal parameters are selected through experience or trial and error. Experimental and numerical techniques have been widely used to analyze mixing systems and to gain a detailed understanding of mixing processes. The limitations associated with experimental techniques, however, have made discrete element method (DEM) a valuable complementary tool to obtain comprehensive particle level information about mixing systems. In the present study, the fundamentals of solid-solid mixing, segregation, and characteristics of different types of batch solid mixers are briefly reviewed. Previously published papers related to the application of DEM in studying mixing quality and assessing the influence of operating and design parameters on the mixing performance of various batch mixing systems are summarized in detail. The challenges with regards to the DEM simulation of mixing systems, the available solutions to address those challenges and our recommendations for future simulations of solid mixing are also presented and discussed.

Experimental and Discrete Element Model Investigation of Limestone Aggregate Blending Process in Vertical Static and/or Conveyor Mixer for Application in the Concrete Mixture

The numerical model of the granular flow within an aggregate mixture, conducted in the vertical static and/or the conveyor blender, was explored using the discrete element method (DEM) approach. The blending quality of limestone fine aggregate fractions binary mixture for application in self-compacting concrete was studied. The potential of augmenting the conveyor mixer working efficiency by joining its operation to a Komax-type vertical static mixer, to increase the blending conduct was investigated. In addition the impact of the feed height on the flow field in the cone-shaped conveyor mixer was examined using the DEM simulation. Applying the numerical approach enabled a deeper insight into the quality of blending actions, while the relative standard deviation criteria ranked the uniformity of the mixture. The primary objective of this investigation was to examine the behavior of mixture for two types of blenders and to estimate the combined blending action of these two mixers, to explore the potential to augment the homogeneity of the aggregate fractions binary mixture, i.e., mixing quality, reduce the blending time and to abbreviate the energy-consuming.

Virtual Experiments of Particle Mixing Process with the SPH-DEM Model

Particle mixing process is critical for the design and quality control of concrete and composite production. This paper develops an algorithm to simulate the high-shear mixing process of a granular flow containing a high proportion of solid particles mixed in a liquid. DEM is employed to simulate solid particle interactions; whereas SPH is implemented to simulate the liquid particles. The two-way coupling force between SPH and DEM particles is used to evaluate the solid-liquid interaction of a multi-phase flow. Using Darcy’s Law, this paper evaluates the coupling force as a function of local mixture porosity. After the model is verified by two benchmark case studies, i.e., a solid particle moving in a liquid and fluid flowing through a porous medium, this method is applied to a high shear mixing problem of two types of solid particles mixed in a viscous liquid by a four-bladed mixer. A homogeneity metric is introduced to characterize the mixing quality of the particulate mixture. The virtual experiments with the present algorithm show that adding more liquid or increasing liquid viscosity slows down the mixing process for a high solid load mix. Although the solid particles can be mixed well eventually, the liquid distribution is not homogeneous, especially when the viscosity of liquid is low. The present SPH-DEM model is versatile and suitable for virtual experiments of particle mixing process with different blades, solid particle densities and sizes, and liquid binders, and thus can expedite the design and development of concrete materials and particulate composites.

DEM based investigation of powder packing in 3D printing of pharmaceutical tablets

3D printing is emerging as one of the most promising methods to manufacture Pharmaceutical dosage forms as it offers multiple advantages such as personalization of dosage forms, polypill, fabrication of complex dosage forms etc. 3D printing came into existence in 1980s but its use was extended recently to pharmaceutical industry along with the approval of first 3D printed tablet Spritam by FDA in 2015. Spritam was manufactured by Aprecia pharmaceuticals using binder jetting technology. Binder jet 3D printing involves a hopper for powder discharge and printheads for ink jetting. The properties of tablets are highly dependent upon the discharge quality of powder mixture from the hopper and jetting of the ink/binder solution from the printhead nozzle. In this study, numerical models were developed using Discrete element method (DEM) to gain better understanding of the binder jet 3D printing process. The DEM modeling of hopper discharge was performed using in-house DEM code to study the effect of raw material attributes such as powder bed packing density (i.e. particle size, particle density etc) on the printing process, especially during powder bed preparation. This DEM model was further validated experimentally, and the model demonstrated good agreement with experimental results.

Multicomponent granular mixing in a Bohle bin Blender-Experiments and simulation

Study of mixing and segregation of granular materials was performed in a Bohle bin blender using both computational modeling and experiments. A multicomponent mixture of pharmaceutical excipients and coated theophylline granules, an active pharmaceutical ingredient (API) was considered as the blend formulation. A DEM (Discrete Element Method) Model was developed to simulate the flow and mixing of the multicomponent blend to compare with the experimental data. DEM is a numerical modeling technique which incorporates all the material properties (such as Particle size, density, elastic modulus, yield strength, Poisson's ratio, work function etc.)to simulate granular flow (such as mixing, conveying) of particles. In simulation, the degree (Relative standard deviation) of mixing in a Bohle bin blender was assessed as a function of critical processing parameters (loading pattern, rotational rate, and fill percentage). Numerical simulation results reveal radial mixing in a Bohle bin blender is faster than axial mixing due to symmetric geometry limitation. This study investigates a numerical model-based approach to study the effect of the critical process parameters on the mixing dynamics in Bohle bin blender for a moderately cohesive pharmaceutical formulation. The DEM model can be used to provide crucial insights to developed optimized mixing protocols to ascertain the best mixing conditions for different formulation. As for example, as we try to develop a mixing protocol for another formulation with different operational parameters such as loading pattern, rotational speed, and fill percentage, one can device an optimized mixing protocol of the formulation with the help of this DEM model.

Influence of particle size and blender size on blending performance of bi-component granular mixing: A DEM and experimental study

The effect of particle size enlargement and blender geometry down-scaling on the blend uniformity (BU) was evaluated by Discrete Element Method (DEM) to predict the blending performance of a binary granular mixture. Three 10 kg blending experiments differentiated by the physical properties specifically particle size were performed as reference for DEM simulations. The segregation behavior observed during the diffusion blending was common for all blends, while the sample BU, i.e., standard deviation of active ingredient content % was different among the three blends reflecting segregation due to the particle size differences between the components. Quantitative prediction of the sample BU probability density distribution in reality based on the DEM simulation results was successfully demonstrated. The average root mean square error normalized by the mean of the mean sample BU in the blends was 0.228. Beside the ratio of blender container to particle size, total number of particles in the blender and the number of particles in a sample were confirmed critical for the blending performance. These in-silico experiments through DEM simulations would help in setting a design space with respect to the particle size and in a broader sense with respect to the physical properties in general.

A drop penetration method to measure powder blend wettability

Water wettability of pharmaceutical blends affects important quality attributes of final products. We investigate the wetting properties of a pharmaceutical blend lubricated with Magnesium Stearate (MgSt) as a function of the mechanical shear strain applied to the blend. We measure the penetration dynamics of sessile drops deposited on slightly compressed powder beds. We consider a blend composed of 9% Acetaminophen 90% Lactose and 1% MgSt by weight. Comparing the penetration time of water and a reference liquid Polydimethylsiloxane (silicon oil) we obtain an effective cosine of the contact angle with water, based on a recently developed drop penetration method. We repeat the experiments for blends exposed to increasing levels of shear strain and demonstrate a significant decrease in water wettability (decrease in the cosine of the contact angle). The results are consistent with the development of a hydrophobic film coating the powder particles as a result of the increased shear strain. Finally, we show that, as expected dissolution times increase with the level of shear strain. Therefore, the proposed drop penetration method could be used to directly assess the state of lubrication of a pharmaceutical blend and act as a quality control on powder blend attributes before the blend is tableted.

Mathematical Development and Comparison of a Hybrid PBM-DEM Description of a Continuous Powder Mixing Process

This paper describes the development of a multidimensional population balance model (PBM) which can account for the dynamics of a continuous powder mixing/blending process. The PBM can incorporate the important design and process conditions and determine their effects on the various critical quality attributes (CQAs) accordingly. The important parameters considered in this study are blender dimensions and presence of noise in the inlet streams. The blender dynamics have been captured in terms of composition of the ingredients, (relative standard deviation) RSD, and (residence time distribution) RTD. PBM interacts with discrete element modeling (DEM) via one-way coupling which forms a basic framework for hybrid modeling. The results thus obtained have been compared against a full DEM simulation which is a more fundamental particle-level model that elucidates the dynamics of the mixing process. Results show good qualitative agreement which lends credence to the use of coupled PBM as an effective tool in control and optimization of mixing process due to its relatively fewer computational requirements compared to DEM.

Quantitative characterization of agglomerate abrasion in a tumbling blender by using the Stokes number approach

Removal of microcrystalline cellulose agglomerates in a dry-mixing system (lactose, 100 M) predominantly occurs via abrasion. The agglomerate abrasion rate potential is estimated by the Stokes abrasion (StAbr) number of the system. The StAbr number equals the ratio between the kinetic energy density of the moving powder bed and the work of fracture of the agglomerate. Basically, the StAbr number concept describes the blending condition of the dry-mixing system. The concept has been applied to investigate the relevance of process parameters on agglomerate abrasion in tumbling blenders. Here, process parameters such as blender rotational speed and relative fill volumes were investigated. In this study, the StAbr approach revealed a transition point between abrasion rate behaviors. Below this transition point, a blending condition exists where agglomerate abrasion is dominated by the kinetic energy density of the powder blend. Above this transition point, a blending condition exists where agglomerates show (undesirable) slow abrasion rates. In this situation, the blending condition is mainly determined by the high fill volume of the filler.

The variability in nutrient composition of Anaerobic Digestate granules produced from high shear granulation

This study investigates the production of organic fertilizer using Anaerobic Digestate (as a nutrient source) and limestone powder as the raw materials. A two-level factorial experimental design was used to determine the influence of process variables on the nutrient homogeneity within the granules. Increasing the liquid-to-solid ratio during granulation resulted in increased granule nutrient homogeneity. Increasing the processing time and the impeller speed were also found to increase the nutrient homogeneity. In terms of nutrients release into deionized water, the granules effectively released both potassium and phosphate into solution.