Function Of Fluidizing Velocity Research Articles

A new method to predict flowability using a microscale fluid bed

The purpose of this research was to develop a new method to predict the flow behavior of pharmaceutical powders using a multichamber microscale fluid bed. Different amounts of poorly flowing paracetamol were added to various grades of microcrystalline celluloses and silicified microcrystalline cellulose powders. Magnesium stearate was used as a lubricant. Experimental minimum fluidization velocities (u(mf)) were defined using 2 to 4 g (equal to 10 mL) of material (Video 1). The reference flowability of the powders was determined using a specific flow meter. Also, the weight variation of the compressed powders, using a single-punch press, was measured. When the amount of paracetamol in the excipients was increased, the experimental umf increased and the fluidization behavior grew worse (Video 2). Principal component analysis (PCA) established that the pressure difference over the bed as a function of fluidization velocity could be used to characterize the behavior of powders. The increase in poor fluidization behavior of the powders was in accordance with the increasing amount of paracetamol and with the increasing weight variation of the tablets. Furthermore, the angle of repose and the flow rate of silicified microcrystalline cellulose powders were predicted using a partial least squares (PLS) model. The developed method to predict flowability is a promising approach for use in the preformulation and formulation stages of new drug candidates, for example.

Fluidization characteristics of and protein adsorption on fluoride-modified porous zirconium oxide particles

Porous zirconia particles of specific gravity ∼3.2 g/ml, mean particle sizes of ∼50 μm, and terminal settling velocity of ∼2.8 mm/s in water, were synthesized using an oil emulsion method from 1000 Å colloids and were evaluated for their potential use in expanded bed protein adsorption. Expanded beds of particles were stable even for small volume, shallow beds (settled bed: 10 ml, height to diameter ratio <1.0) and even for fluidization velocities common to much larger particles (210 cm/h for a three-fold bed expansion). When the surface of these particles was modified by fluoride adsorption, the total bed capacity for bovine serum albumin (BSA) adsorption was 42±2 mg BSA/ml of settled bed volume at linear velocities of 109–210 cm/h. Residence time distribution studies of several solutes under non-binding conditions were performed to assess the degree of liquid mixing and channeling in the expanded bed as a function of fluidization velocity. Liquid mixing and channeling were also studied as a function of distributor design. With these very dense particles, the degree of channeling and mixing did not worsen with the degree of expansion. Elution of adsorbed BSA while the bed was expanded (by a step increase in ionic strength) was rapid resulting in a narrow peak at high fluidization velocities without resorting to settling of the bed. The dynamic binding capacity of BSA at 5% breakthrough (protein effluent concentration equal to 5% of the inlet concentration) was the same for a two-fold expanded bed as for a settled bed (22±2 mg BSA/ml of settled bed volume), though it decreased for higher bed expansions. BSA binding was reproducible following repeated cleaning of the adsorbent with 0.25 M sodium hydroxide.

Diagnostic procedures for establishing the quality of fluidization of gas-solid systems

Fluidization experiments were conducted on two dolomite beds of average diameters 1490 and 2010 μm in a 0.153 m square fluidized bed at ambient conditions. In particular, the pressure drops across the distributor plate and the test bed were measured as a function of fluidization velocity. In addition, temperature and pressure histories were recorded at different fluidization velocities. The data are employed to compute minimum fluidization velocity, bed voidage, relative heat transfer coefficient, variances in temperature and pressure fluctuation data, probability density function, skewness, kurtosis, autocorrelation function, and power spectral density function. These parameters and functions were assessed as to their potential to characterize the quality of fluidization and thereby establish a methodology of diagnostic procedures for such a task based on the knowledge of those statistical functions that have proven successful in this endeavor.