Assessment of predictive models for characterizing the atomization process in a spray dryer’s bi-fluid nozzle

Poozesh, Sadegh; Setiawan, Nico; Akafuah, Nelson K.; Saito, Kozo; Marsac, Patrick J.

doi:10.1016/j.ces.2018.01.033

Cited by 24 publications

(4 citation statements)

References 22 publications

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“…The low yield at 283 L•h −1 is caused by the corresponding droplet size (Table S1) because a large droplet will stick to the wall of drying chamber before being dried. The droplet sizes at different spray drying conditions were calculated by using an empirical formula for the bi-fluid nozzle (see details in Discussion S2) [25]. The droplet decreases in size as X 1 is increased (Table S1), just as for the resulted particle size.…”

Section: Single-factor Experimentsmentioning

confidence: 99%

Optimization of Spray-Drying Process with Response Surface Methodology (RSM) for Preparing High Quality Graphene Oxide Slurry

Ye¹,

Shi²,

Shen³

et al. 2021

Processes

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The “Drying-redissolution” method is promising for the industrial production of high-concentration well-dispersed graphene oxide slurry (GOS). As the potential key step in this method, the spray drying process requires a statistical investigation which guides the large-scale preparation of graphene oxide powder (GOP). This work systematically studies the effects of operating parameters, including nozzle airflow rate (439–895 L·h−1), atomization pressure (0.5–0.7 MPa), and liquid feed rate (3.0–9.0 mL·min−1), by using the response surface methodology integrated Box–Behnken design (RSM–BBD), aiming to produce GOP with high yield and easy re-dispersion. The optimized spray drying condition is predicted to be 439 L·h−1, 0.59 MPa, and 9.0 mL·min−1, at which a powder yield of 70.45% can be achieved. The experimentally obtained GOP has an average particle size of 11.65 μm and the low crumpling degree of the particle morphology results in the good re-dispersibility (97.95%) and excellent adsorption performance (244.1 mg·g−1) of GOP. The GOS prepared by the spray-dried GOP possess low viscosity and high exfoliation efficiency with a single-layer fraction up to 90.8%, exhibiting good prospects for application. This work first applied the RSM–BBD model on the spray drying process of GO, and evidenced the possibility of producing high-quality GO slurry with the “drying-redissolution” method.

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Section: Single-factor Experimentsmentioning

confidence: 99%

Optimization of Spray-Drying Process with Response Surface Methodology (RSM) for Preparing High Quality Graphene Oxide Slurry

Ye¹,

Shi²,

Shen³

et al. 2021

Processes

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“…These deviations are most likely due to the overestimating impacts of liquid properties, especially viscosity, on SMD. It has been argued that liquid properties in the two-fluid nozzle are weaker driving forces in determining SMD, compared to process conditions-e.g., relative velocities [28,34,35]. This is especially the case at higher relative velocities where high aerodynamic forces suppress the impacts of fluid properties.…”

Section: Data Comparisonmentioning

confidence: 99%

Experimental and Mathematical Tools to Predict Droplet Size and Velocity Distribution for a Two-Fluid Nozzle

Poozesh

Akafuah

Campbell

et al. 2020

Fluids

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Despite progress in laser-based and computational tools, an accessible model that relies on fundamentals and offers a reasonably accurate estimation of droplet size and velocity is lacking, primarily due to entangled complex breakup mechanisms. Therefore, this study aims at using the integral form of the conservation equations to create a system of equations by solving which, the far-field secondary atomization can be analyzed through predicting droplet size and velocity distributions of the involved phases. To validate the model predictions, experiments are conducted at ambient conditions using water, methanol, and acetone as model fluids with varying formulation properties, such as density, viscosity, and surface tension. Droplet size distribution and velocity are measured with laser diffraction and a high-speed camera, respectively. Finally, an attempt is made to utilize non-scaled parameters to characterize the atomization process, useful for extrapolating the sensitivity analysis to other scales. The merit of this model lies in its simplicity for use in process control and optimization.

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“…For bi-fluid nozzles, which are commonly utilized at the laboratory scale, droplet size is chiefly determined by the physical properties of the liquid feed (e.g., viscosity, surface tension, and density), the atomizing gas to liquid mass flow rate ratios, and the nozzle size and/or design. 31 As such, any change in solvent will impact dissolution performance due to alterations in the droplet (particle) size when otherwise holding the remaining process parameters constant. This underscores the importance of conducting intrinsic dissolution studies to control for surface area when investigating solvent effects exclusive of the atomization process.…”

Section: ■ Introductionmentioning

confidence: 99%

“…The role of solvent choice in SDDs has garnered increasing attention regarding its potential to influence key formulation properties such as homogeneity, physical stability, and dissolution performance. − Several rationalizations have been offered to explain solvent effects in SDDs, which include changes in droplet size, kinetic effects arising from varying evaporation rates, and thermodynamic processes attributed to drug–polymer–solvent interactions prior to and during the drying event. For bi-fluid nozzles, which are commonly utilized at the laboratory scale, droplet size is chiefly determined by the physical properties of the liquid feed (e.g., viscosity, surface tension, and density), the atomizing gas to liquid mass flow rate ratios, and the nozzle size and/or design . As such, any change in solvent will impact dissolution performance due to alterations in the droplet (particle) size when otherwise holding the remaining process parameters constant.…”

Section: Introductionmentioning

confidence: 99%

Approaches to Understanding the Solution-State Organization of Spray-Dried Dispersion Feed Solutions and Its Translation to the Solid State

et al. 2020

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It is well established that polymers adopt a range of conformations and solution-state organization in response to varying solution environments, although very little work has been done to understand how these effects might impact the physical stability and bioavailability of spray-dried amorphous dispersions (SDDs). Potentially relevant solution-state polymer-solvent/cosolute interactions include preferential solvation, hydrodynamic size (i.e., polymer swelling or collapse), and solvent quality effects (i.e., attractive or repulsive self-interactions). Of particular interest is the investigation of preferential solvation, defined as the relative attraction or rejection of a cosolvent and/or cosolute from the local environment of a solvated macromolecule, which often occurs in multicomponent macromolecular solutions. As spray drying and other solvent-based dispersion processing necessitates the use of complex media consisting of at least three or more components (drug, polymer, solvent(s), and other possible excipients), the prevalence of this phenomenon is likely. This work characterizes largely unexplored solution-state properties in model spray-dried dispersion feed solutions using light scattering and viscometric techniques to add greater context and guidance in studying these information-rich materials. These systems are found to exhibit complex non-intuitive behavior, which serves to highlight the potential utility of preferential solvation in spray-dried dispersion processing and stability. It is hypothesized that solution-state organization of the liquid feed can be engineered and translated to the solid-state for the optimization of SDD properties.

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Assessment of predictive models for characterizing the atomization process in a spray dryer’s bi-fluid nozzle

Cited by 24 publications

References 22 publications

Optimization of Spray-Drying Process with Response Surface Methodology (RSM) for Preparing High Quality Graphene Oxide Slurry

Optimization of Spray-Drying Process with Response Surface Methodology (RSM) for Preparing High Quality Graphene Oxide Slurry

Experimental and Mathematical Tools to Predict Droplet Size and Velocity Distribution for a Two-Fluid Nozzle

Approaches to Understanding the Solution-State Organization of Spray-Dried Dispersion Feed Solutions and Its Translation to the Solid State

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