Scaling parameters inter relations

In the fluid-bed granulation process, moisture control is the key parameter that needs to be controlled. Faure et al. (133) have used process control for scale-up of a fluidized bed process. They used infra-red probes to monitor moisture. As there are normally large numbers of inter-related variables, they used computerized techniques for process control, such as fuzzy logic, neural networks, and models based on experimental techniques. 

The many complex molecular processes that simultaneously occur in the drawing/conversion process need to be carefully optimized so that their time scales are in harmony. The critical parameters for process optimization are the degree of pre-conversion, deformation rate, process-temperature profile, conversion-catalyst concentration, and residence time. Obviously, in this initial study of PTV, we have not developed a fully balanced set of processing parameters. This is illustrated by the modest orientation indicated by the X-ray patterns. Nevertheless, the current materials have a Young s modulus of 7 GPa, a tenacity of 0.5 GPa and a conductivity of 2000 S/cm a combination of properties which are adequate for conductive textile applications. It should be clear that further optimization of the inter-related processing variables will undoubtedly result in materials of superior quality. 

A least squares fit to the dispersion relations with 7 exchange parameters (R) and 5 inter-sublattice parameters (R) enabled q), q ) and F, to be determined at any q, enabling the wavevector sums comprising AM and b to be evaluated. The result has to be made self-consistent since the F,(T, H) functions are renormalized by scaling with the reduced magnetization m(T, H). 

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