Fillers dispersion experiment

Experience has shown that optimum pigment and filler dispersion result when the specific volume of the material charged to the mixer falls within a well-defined range (see Figure 4). The specific volume of the formulation is the volume (in liters) occupied by 1.0 kg of molten compound at 150"C. For a mixer with an approximate free volume of 40 liters, optimum results are obtained using specific volumes of 4.2 to 5.0 liters (10.5-12.5% of mixer free volume). Since specific volume of the melt is directly related to the product formulation, output rates vary volumetrically as a function of product density. Idealized output rates for a 40 hter HIDM are shovra in Figure 5. 

The degree of adhesion between the filler and polymer is expected to influence the mechanical properties of the composite. This can be predicted theoretically, although it is much more difficult to prove experimentally. It is a major challenge to change the adhesion between the polymer and the filler without invalidating the experiment by unintentionally altering other parameters [109] such as filler dispersion level or polymer crystallinity. 

The results are reported of a study carried out to optimise the development of the continuous mixing process for various NR powders in a twin-screw extruder equipped with co-rotating screws. The effect of various screw elements on the development of properties, including filler dispersion and Mooney viscosity, along the extruder screw is evaluated and a screw configuration optimised for the performance of continuous compounding experiments on different powdered rubber types is illustrated. 11 refs. 

Typical nonidealities such as polydispersity in filler size and conductivity, filler waviness and entanglements, and impurities impact the measured electrical properties of polymer nanocomposites. Most analytical and simulation studies of these nonidealities have been conducted for highly simplified systems, so that the extent to which these factors can modify composite properties, particularly within the context of more dominant factors such as filler dispersion and network stmcture, is unclear. To clarify the importance of these effects, theoretical analysis or modeling of more complex systems is required. Conducting parallel experiments in model systems can enhance the efficacy of such studies. 

However, controlled shearing experiments using titanium dioxide in PDMS and hnear low density polyethylene demonstrated that with this filler type, particle erosion was the predominant dispersion mechanism [68,119]. 

For reliable application of the free volume concept of disperse systems one must have dependable methods of determination of the maximum packing fraction of the filler tpmax. Unfortunately, the possibility of a reliable theoretical calculation of its value, even for narrow filler fractions, seems to be problematic since there are practically no methods available for calculations for filler particles of arbitrary shape. The most reliable data are those obtained by computer simulation of the maximum packing fraction for spherical particles which give the value associated with possible particle aggregation, so that they are probable for fractions of small particle size. Deviations of particle shape is nearly cubic. At present the most reliable method of determination of [Pg.142]

The selected features in the experiment were flexibility, waterproofness and vapor permeability. The material variables were relative contents polymer to Portland cement ratio (xi = P/C, g/g), polymer to fillers ratio (x2 = P/F, g/g) and hydrophobic agent to Portland cement ratio (xs = H/C, g/g). The variables ranges are given in Table 1. The applied polymer was aqueous dispersion of styrene-acrylic and the fillers included quartzite meal, sand, bentonite and aluminum hydroxide. The hydrophobic agent (commercial product) was added to the mix, not applied on the surface. According to the Box design, in reference to material variables values, fifteen compositions have been determined. Moreover, the composition for the central variable was repeated three times which improved precision of the material model. 

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