Droplet size process parameters

The second step is to disperse the core material being encapsulated in the solution of shell material. The core material usually is a hydrophobic or water-knmiscible oil, although soHd powders have been encapsulated. A suitable emulsifier is used to aid formation of the dispersion or emulsion. In the case of oil core materials, the oil phase is typically reduced to a drop size of 1—3 p.m. Once a suitable dispersion or emulsion has been prepared, it is sprayed into a heated chamber. The small droplets produced have a high surface area and are rapidly converted by desolvation in the chamber to a fine powder. Residence time in the spray-drying chamber is 30 s or less. Inlet and outlet air temperatures are important process parameters as is relative humidity of the inlet air stream. 

Atomization, or generally speaking droplet generation, is an extremely complex process that cannot yet be precisely predicted theoretically. The lack of general theoretical treatment of droplet processes has led to the development of numerous empirical correlations for droplet properties as a function of process parameters and material properties. In this chapter, empirical and analytical correlations for the prediction of droplet properties, such as droplet size distribution and droplet deformation characteristics will be summarized from experimental observations and theoretical analyses in available literature. 

To characterize a droplet size distribution, at least two parameters are typically necessary, i.e., a representative droplet diameter, (for example, mean droplet size) and a measure of droplet size range (for example, standard deviation or q). Many representative droplet diameters have been used in specifying distribution functions. The definitions of these diameters and the relevant relationships are summarized in Table 4.2. These relationships are derived on the basis of the Rosin-Rammler distribution function (Eq. 14), and the diameters are uniquely related to each other via the distribution parameter q in the Rosin-Rammler distribution function. Lefebvre 1 calculated the values of these diameters for q ranging from 1.2 to 4.0. The calculated results showed that Dpeak is always larger than SMD, and SMD is between 80% and 84% of Dpeak for many droplet generation processes for which 2left-hand side of Dpeak. The ratio MMD/SMD is... 

In many atomization processes, physical phenomena involved have not yet been understood to such an extent that mean droplet size could be expressed with equations derived directly from first principles, although some attempts have been made to predict droplet size and velocity distributions in sprays through maximum entropy principle.I252 432] Therefore, the correlations proposed by numerous studies on droplet size distributions are mainly empirical in nature. However, the empirical correlations prove to be a practical way to determine droplet sizes from process parameters and relevant physical properties of liquid and gas involved. In addition, these previous studies have provided insightful information about the effects of process parameters and material properties on droplet sizes. 

The process parameters influencing droplet sizes may include liquid pressure, flow rate, velocity ratio of air to liquid (mass flow rate ratio of air to liquid), and atomizer geometry and configuration. It has been clearly established that increasing the velocity ratio of air to liquid is the most important practical method of improving atomization)211] In industrial applications, however, the use of mass flow rate ratio of air to liquid has been preferred. As indicated by Chigier)2111 it is difficult to accept that vast quantities of air, that do not come into any direct contact with the liquid surface, have any influence on atomization although mass flow rates of fluids include the effects of velocities. 

In the following sections, the correlations for droplet sizes generated by different types of atomizers will be summarized, and the effects of process parameters and material properties on droplet sizes will be discussed on the basis of the analytical and experimental studies available in published literature. 

In fan spray atomization, the effects of process parameters on the mean droplet size are similar to those in pressure-swirl atomization. In general, the mean droplet size increases with an increase in liquid viscosity, surface tension, and/or liquid sheet thickness and length. It decreases with increasing liquid velocity, liquid density, gas density, spray angle, and/or relative velocity between liquid and surrounding air. 

The studies on the performance of effervescent atomizer have been very limited as compared to those described above. However, the results of droplet size measurements made by Lefebvre et al.t87] for the effervescent atomizer provided insightful information about the effects of process parameters on droplet size. Their analysis of the experimental data suggested that the atomization quality by the effervescent atomizer is generally quite high. Better atomization may be achieved by generating small bubbles. Droplet size distribution may follow the Rosin-Rammler distribution pattern with the parameter q ranging from 1 to 2 for a gas to liquid ratio up to 0.2, and a liquid injection pressure from 34.5 to 345 kPa. The mean droplet size decreases with an increase in the gas to liquid ratio and/or liquid injection pressure. Any factor that tends to impair atomization quality, and increase the mean droplet size (for example, decreasing gas to liquid ratio and/or injection pressure) also leads to a more mono-disperse spray. 

As described above, a number of empirical and analytical correlations for droplet sizes have been established for normal liquids. These correlations are applicable mainly to atomizer designs, and operation conditions under which they were derived, and hold for fairly narrow variations of geometry and process parameters. In contrast, correlations for droplet sizes of liquid metals/alloys available in published literature 318]f323ff328]- 3311 [485]-[487] are relatively limited, and most of these correlations fail to provide quantitative information on mechanisms of droplet formation. Many of the empirical correlations for metal droplet sizes have been derived from off-line measurements of solidified particles (powders), mainly sieve analysis. In addition, the validity of the published correlations needs to be examined for a wide range of process conditions in different applications. Reviews of mathematical models and correlations for... 

Thus, both the mean droplet size and the size distribution may be predicted using these correlations [Eqs. (26), (27), (28), or (29) and Eqs. (30), (31)] for given process parameters and material properties. For a given atomizer design, the standard deviation of droplet size distribution has been found to increase with the melt flow rate, but appears to be less sensitive to the gas flow rated5 Moreover, the variation of the standard deviation is very atomizer- and melt-specific. An empirical correlation which fits with a wide range of atomization data has the following form ... 

The solution of the gas flow and temperature fields in the nearnozzle region (as described in the previous subsection), along with process parameters, thermophysical properties, and atomizer geometry parameters, were used as inputs for this liquid metal breakup model to calculate the liquid film and sheet characteristics, primary and secondary breakup, as well as droplet dynamics and cooling. The trajectories and temperatures of droplets were calculated until the onset of secondary breakup, the onset of solidification, or the attainment of the computational domain boundary. This procedure was repeated for all droplet size classes. Finally, the droplets were numerically sieved and the droplet size distribution was determined. 

With the above-described heat transfer model and rapid solidification kinetic model, along with the related process parameters and thermophysical properties of atomization gases (Tables 2.6 and 2.7) and metals/alloys (Tables 2.8,2.9,2.10 and 2.11), the 2-D distributions of transient droplet temperatures, cooling rates, achievable undercoolings, and solid fractions in the spray can be calculated, once the initial droplet sizes, temperatures, and velocities are established by the modeling of the atomization stage, as discussed in the previous subsection. For the implementation of the heat transfer model and the rapid solidification kinetic model, finite difference methods or finite element methods may be used. To characterize the entire size distribution of droplets, some specific droplet sizes (forexample,.D0 16,Z>05, andZ)0 84) are to be considered in the calculations of the 2-D motion, cooling and solidification histories. 

Each spray-dried droplet forms a single particle whose size is determined by the droplet size, the dissolved solids of the feed solution, and the density of the resulting solid particle. For a given formulation and process, both the solid content and density of the powder remain constant within a batch and from batch to batch therefore, the distribution of the primary particle size is determined by the droplet size distribution. A narrowly distributed particle size can be achieved with a well-designed atomizer and controlled process parameters. 

Another process which leads to HIPE instability is gravitational syneresis, or creaming, where the continuous phase drains from the thin films as a result of density differences between the phases. This produces a separated layer of bulk continuous phase and a more concentrated emulsion phase. The separated liquid can be located either above or below the emulsion, depending on whether the continuous phase is more or less dense, respectively, than the dispersed phase. This process has been studied by Princen [111] who suggests that it can be reduced by a number of parameters, including a high internal phase volume, small droplet sizes, a high interfacial tension and a small density difference between phases. 

Spray Dynamic Structure. Detailed measurements of spray dynamic parameters are necessary to understand the process of droplet dispersion. Improvements in phase Doppler particle analyzers (PDPA) permit in situ measurements of droplet size, velocity, number density, and liquid flux, as well as detailed turbulence characteristics for very small regions within the spray. 

The conclusions drawn from the different experiments with respect to the effect of RESS process parameters on precipitate size and morphology reflect the importance of specific solute/solvent properties on the process path. This probably results in the apparent contradictions found in experimental results. To date, the theoretical work aimed at gaining a fundamental understanding of the RESS expansion phenomenon and physical processes relevant to droplet, particle or film formation has been quite limited (Debenedetti, 1990 Debenedetti et al., 1993 Kwauk and Debenedetti, 1993 Lele and Shine, 1994). 

The distinguishing feature of membrane emulsification technique is that droplet size is controlled primarily by the choice of the membrane, its microchannel structure and few process parameters, which can be used to tune droplets and emulsion properties. Comparing to the conventional emulsification processes, the membrane emulsification permits a better control of droplet-size distribution to be obtained, low energy, and materials consumption, modular and easy scale-up. Nevertheless, productivity (m3/day) is much lower, and therefore the challenge in the future is the development of new membranes and modules to keep the known advantages and maximize productivity. 

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