Shear-induced APAP de-agglomeration

Llusa, Marcos; Levin, Michael; Snee, Ronald D.; Muzzio, Fernando J.

doi:10.3109/03639040903025863

Cited by 13 publications

(7 citation statements)

References 28 publications

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“…About the effects of process conditions, the authors found that the abrasion rate increased with the increase of the rotation speed, the mixer size, and the filler particle size. The effects of the mixer rotation speed and the mixer size on abrasion were consistent with experiments . In addition, it was found that the Stoke number, defined as the ratio between the kinetic energy density of a powder bed and work of fracture of an agglomerate, was proportional to the abrasion rate, as observed in the experiments …”

Section: Introductionsupporting

confidence: 83%

DEM–PBM modeling of abrasion dominated ribbon breakage

Loreti

Reynolds

et al. 2017

AIChE Journal

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In dry granulation, fine cohesive powders are compacted into large multi‐particle entities, i.e., briquettes, flakes, or ribbons. The powder compaction is generally followed by milling, a size reduction process, which is crucial to obtain the desired granule size or properties. Abrasion and impact are two primary mechanisms of comminution in ribbon milling, but they are not completely understood. The aim of this article was hence to investigate numerically the fragmentation process induced by abrasion during ribbon milling. The discrete element method (DEM) was employed to simulate abrasion tests, for which three‐dimensional parallelepiped ribbons were generated using auto‐adhesive elastic spheres. The fragmentation rate, and the fragments size and number were determined for various surface energies and abrasive velocities. The DEM results showed that the mass‐equivalent fragment size distributions were bi‐modal, similar to the experimental observations and the numerical results for impact‐dominated ribbon milling reported in the literature. In addition, two quantities were determined from the DEM analysis, i.e., the number of large fragments and the fraction of fines, which was then integrated into the population balance models (PBM) so that a DEM–PBM multiscale modeling framework was developed to predict the granule size distribution during ribbon milling. The DEM–PBM results were compared with the experimental results reported in the literature, and a broad agreement was obtained, implying the proposed DEM–PBM can be used to analyse the ribbon milling behavior. © 2017 American Institute of Chemical Engineers AIChE J, 64: 1191–1204, 2018

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Section: Introductionsupporting

confidence: 83%

DEM–PBM modeling of abrasion dominated ribbon breakage

Loreti

Reynolds

et al. 2017

AIChE Journal

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“…27 Broad bands are obtained at no shear conditions. As the strain is increased the bands became more defined as observed in Figs 3a to c. These spectra show significant differences in two spectral regions: 7450-7000 cm À1 and 5600-5100 cm À1 .…”

Section: Resultsmentioning

confidence: 99%

“…The shear treatment de-agglomerates the constituent powder, reducing the average size of microparticles. 27 As a result, this treatment reduces the scattering intensity. Thus, 160 revolutions (Figure 9b) increase the tilt of BSDF (θ), and after 640 revolutions the BSDF (θ) drops to its minimal level (Figures 8 and 9c).…”

Section: Resultsmentioning

confidence: 99%

“…Figure 3a shows the differences between the diffuse reflectance spectra of tablets obtained after compaction at 8 kN for blends of similar composition subjected to the three strain levels: no shear, 160 revolutions, and 640 revolutions, where strain refers to the duration of exposure to shear rate. 27 Broad bands are obtained at no shear conditions. As the strain is increased the bands became more defined as observed in Figs 3a to c. These spectra show significant differences in two spectral regions: 7450-7000 cm À1 and 5600-5100 cm À1 .…”

Section: Resultsmentioning

confidence: 99%

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Effect of Shear Applied During a Pharmaceutical Process on Near Infrared Spectra

et al. 2016

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This study describes changes observed in the near-infrared (NIR) diffuse reflectance (DR) spectra of pharmaceutical tablets after these tablets were subjected to different levels of strain (exposure to shear) during the mixing process. Powder shearing is important in the mixing of powders that are cohesive. Shear stress is created in a system by moving one surface over another causing displacements in the direction of the moving surface and is part of the mixing dynamics of particulates in many industries including the pharmaceutical industry. In continuous mixing, shear strain is developed within the process when powder particles are in constant movement and can affect the quality attributes of the final product such as dissolution. These changes in the NIR spectra could affect results obtained from NIR calibration models. The aim of the study was to understand changes in the NIR diffuse reflectance spectra that can be associated with different levels of strain developed during blend shearing of laboratory samples. Shear was applied using a Couette cell and tablets were produced using a tablet press emulator. Tablets with different shear levels were measured using NIR spectroscopy in the diffuse reflectance mode. The NIR spectra were baseline corrected to maintain the scattering effect associated with the physical properties of the tablet surface. Principal component analysis was used to establish the principal sources of variation within the samples. The angular dependence of elastic light scattering shows that the shear treatment reduces the size of particles and produces their uniform and highly isotropic distribution. Tablet compaction further reduces the diffuse component of scattering due to realignment of particles.

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“…Powders were placed between the concentric cylinders while the internal cylinder rotated. This system is not shown as photographs of the system have appeared in previous publications (Hernández et al, 2016;Llusa et al, 2009;Mehrotra et al, 2007). Each cylinder contains a certain number of blades controlling revolutions per minute (rpm).…”

Section: Shear Cellmentioning

confidence: 99%

Near infrared spectroscopic calibration models for real time monitoring of powder density

Román-Ospino

Singh

Ierapetritou

et al. 2016

International Journal of Pharmaceutics

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Near infrared spectroscopic (NIRS) calibration models for real time prediction of powder density (tap, bulk and consolidated) were developed for a pharmaceutical formulation. Powder density is a critical property in the manufacturing of solid oral dosages, related to critical quality attributes such as tablet mass, hardness and dissolution. The establishment of calibration techniques for powder density is highly desired towards the development of control strategies. Three techniques were evaluated to obtain the required variation in powder density for calibration sets: 1) different tap density levels (for a single component), 2) generating different strain levels in powders blends (and as consequence powder density), through a modified shear Couette Cell, and 3) applying normal forces during a compressibility test with a powder rheometer to a pharmaceutical blend. For each variation in powder density, near infrared spectra were acquired to develop partial least squares (PLS) calibration models. Test samples were predicted with a relative standard error of prediction of 0.38%, 7.65% and 0.93% for tap density (single component), shear and rheometer respectively. Spectra obtained in real time in a continuous manufacturing (CM) plant were compared to the spectra from the three approaches used to vary powder density. The calibration based on the application of different strain levels showed the greatest similarity with the blends produced in the CM plant.

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Shear-induced APAP de-agglomeration

Cited by 13 publications

References 28 publications

DEM–PBM modeling of abrasion dominated ribbon breakage

DEM–PBM modeling of abrasion dominated ribbon breakage

Effect of Shear Applied During a Pharmaceutical Process on Near Infrared Spectra

Near infrared spectroscopic calibration models for real time monitoring of powder density

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