Particle size distribution variability

The characteristics of a powder that determine its apparent density are rather complex, but some general statements with respect to powder variables and their effect on the density of the loose powder can be made. (/) The smaller the particles, the greater the specific surface area of the powder. This increases the friction between the particles and lowers the apparent density but enhances the rate of sintering. (2) Powders having very irregular-shaped particles are usually characterized by a lower apparent density than more regular or spherical ones. This is shown in Table 4 for three different types of copper powders having identical particle size distribution but different particle shape. These data illustrate the decisive influence of particle shape on apparent density. (J) In any mixture of coarse and fine powder particles, an optimum mixture results in maximum apparent density. This optimum mixture is reached when the fine particles fill the voids between the coarse particles. 

In their study of the effect of particle-size distribution on mass-transfer in dispersions, Gal-Or and Hoelscher (G5) show that when the variable particle size is replaced by the surface mean radius a32, the error introduced is usually very small (see Section IV, J). Consequently if a in Eq. (144) is replaced by a32, that equation can be compared with the experimental correlations [Eq. (10) and (11)] proposed by Calderbank and Moo-Young (C4) for mass transfer in dispersions (see Fig. 9). 

In order to calculate particle size distributions in the adsorption regime and also to determine the relative effects of wavelength on the extinction cross section and imaginary refractive index of the particles, a series of turbidity meas irements were made on the polystyrene standards using a variable wavelength UV detector. More detailed discussions are presented elsewhere (23) > shown here is a brief summary of some of the major results and conclusions. 

Figure 24. Plot of the particle-size distribution versus the transition temperature Tross, which describes the crossover point between an activated transport mechanism (ln(A) oc EJT and variable range hopping (VRH) (ln(R)ocT ). Note that Tdoss has a OK value at a finite (3%) particle-size distribution. (Reprinted with permission from Ref. [56], 2002, American Chemical Society.)...

For code R8 it commences with a solid with the help of AFNOR standards NF T 20-035 . Handling consists in preparing mixtures of variable compositions of an oxidant to be classified as cellulose. Both substances have to have a definite particle size distribution. The composition which gives the fastest combustion on a moulding of the mixture at a distance of 20 cm is established. This speed is compared with the one of the mixture used as a reference, which has an imposed composition of barium nitrate and cellulose. If the combustion speed of the particular substance is higher than that of the reference, it will bear R8. 

The other state variables are the fugacity of dissolved methane in the bulk of the liquid water phase (fb) and the zero, first and second moment of the particle size distribution (p0, Pi, l )- The initial value for the fugacity, fb° is equal to the three phase equilibrium fugacity feq. The initial number of particles, p , or nuclei initially formed was calculated from a mass balance of the amount of gas consumed at the turbidity point. The explanation of the other variables and parameters as well as the initial conditions are described in detail in the reference. The equations are given to illustrate the nature of this parameter estimation problem with five ODEs, one kinetic parameter (K ) and only one measured state variable. 

One of the most difficult parenteral dosage forms to formulate is a suspension. It requires a delicate balance of variables to formulate a product that is easily resuspended and can be ejected through an 18-to 21-gauge needle through its shelf life. To achieve these properties it is necessary to select and carefully maintain particle size distribution, zeta potential, and rheological properties, as well as the manufacturing steps that control wettability and surface tension. The requirements for, limitations in, and differences between the design of injectable suspensions and other suspensions have been previously summarized [17b, 18,19]. 

Research on the modelling, optimization and control of emulsion polymerization (latex) reactors and processes has been expanding rapidly as the chemistry and physics of these systems become better understood, and as the demand for new and improved latex products increases. The objectives are usually to optimize production rates and/or to control product quality variables such as polymer particle size distribution (PSD), particle morphology, copolymer composition, molecular weights (MW s), long chain branching (LCB), crosslinking frequency and gel content. 

The effects of the changes in the preparation methods were assessed by measuring the colour of the pigments in draw-downs and the particle size distributions of the powders. It was found that changes in all the listed variables could produce changes of several NBS... 

In these cases, the values of w are used as a probing measure, and vsR2 for the spherical molecules radius of R. As a result, nm -R D2. The second method by Pfeifer and Anvir is symmetric to the first one in the sense that instead of adsorbing a set of molecules on samples with a constant particle size distribution, one adsorbs a single adsorbate (e g., N2) on a set of samples with variable particles sizes, Ra. The corresponding equations for this method are... 

Raman spectroscopy s sensitivity to the local molecular enviromnent means that it can be correlated to other material properties besides concentration, such as polymorph form, particle size, or polymer crystallinity. This is a powerful advantage, but it can complicate the development and interpretation of calibration models. For example, if a model is built to predict composition, it can appear to fail if the sample particle size distribution does not match what was used in the calibration set. Some models that appear to fail in the field may actually reflect a change in some aspect of the sample that was not sufficiently varied or represented in the calibration set. It is important to identify any differences between laboratory and plant conditions and perform a series of experiments to test the impact of those factors on the spectra and thus the field robustness of any models. This applies not only to physical parameters like flow rate, turbulence, particulates, temperature, crystal size and shape, and pressure, but also to the presence and concentration of minor constituents and expected contaminants. The significance of some of these parameters may be related to the volume of material probed, so factors that are significant in a microspectroscopy mode may not be when using a WAl probe or transmission mode. Regardless, the large calibration data sets required to address these variables can be burdensome. 

Toxicology. Epidemiological evidence suggests that workers intimately exposed to the products of combustion or distillation of bituminous coal are at increased risk of cancer at many sites, including lungs, kidney, and skin. The chemical composition and particle size distribution of coal tar pitch volatiles (CTPV) from different sources are significant variables in determining toxicity. ... 

The particle light scattering coefficient has been continuously measured at this location since 1976. Measurements of the particle size distribution have been made daily since 1978, providing the data base necessary to assess the variability of the normalized aerosol volume distribution. 

Once the analytical method is validated for accuracy at the laboratory scale, it can be used to obtain extensive information on process performance (blend homogeneity, granulation particle size distribution, and moisture content) under various conditions (blender speed, mixing time, drying air temperature, humidity, volume, etc.). Statistical models can then be used to relate the observable variables to other performance attributes (e.g., tablet hardness, content uniformity, and dissolution) in order to determine ranges of measured values that are predictive of acceptable performance. 

In the present paper the chemistry of plutonium is reviewed, with particular reference to the ambient conditions likely to be encountered in natural waters. In addition, experimental work is presented concerning the effects of such variables as pH, plutonium concentration, ionic strength, and the presence of complexing agents on the particle size distributions of aqueous plutonium. In subsequent papers it will be shown that these variables, as they influence the particle size distribution of the aqueous plutonium, greatly affect its interaction with mineral surfaces. The orientation of these studies is the understanding of the likely behavior and fate of plutonium in environmental waters, particularly as related to its interaction with suspended and bottom sediments. 

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