| Summary: | The concept of a unique ceramifiable Ethylene vinyl acetate (EVA) based polymer composite was based on the incorporation of inorganic compounds such as aluminium hydroxide, calcium carbonate, muscovite mica, and calcined kaolinite within a 95 percent EVA/ 5 percent Polydimethylsiloxane (PDMS) polymer matrix such tha t upon heating to elevated temperatures of about 1000 oC, a solid end-product with ceramic-like properties would be formed. The ceramifiable EVA based polymer composite was developed to be used as electric cable insulation or sheath as the formation of a ceramic based material at elevated temperatures would provide flame retardant properties during fire situations. The flame retardant properties at elevated temperatures would ensure that the insulation remains at such temperatures due to some of the properties of the resultant ceramic such as reasonably high flexural strength, high thermal stability, non-reactivity and high melting point. During a fire this would ensure that flames would not be propagated along the length of the cable and also protect the underlying conducting wires from being exposed to the high temperatures of the fire. Its application as a cable insulation also required that the material functions as a cable insulator under ambient temperature conditions where the ceramifiable polymer composite should retain certain polymer properties such as the post-cure tensile strength (MPa), degree of polymer elongation (percent), thermal expansion, thermal slacking, limited oxygen index and electrical insulation. This study made use of a composite experimental design approach that would allow for the optimization of the amounts of the additives in the ceramifiable polymer composite giving both the desired mechanical properties of the material under normal operating temperatures as a polymer and also as a ceramic once exposed to elevated temperatures. The optimization of additives used in the ceramifiable polymer composite was done by using a D-optimal mixture design of experiments (DoE) which was analyzed by multiple linear regression.
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