Abstract
Sintering is the process of making materials from powder form by heating the powder below its melting point until the particles fuse to each other. Field assisted sintering technology (FAST), also sometimes known as spark plasma sintering (SPS), uses a pulsed and/or continuous electric current along with the simultaneous application of compressive pressure which leads to extremely high heating rates and short processing durations. A high relative density and small grain size promote superior properties such as greater hardness and electrical breakdown. Hence, selection of the proper sintering parameters is of paramount importance and a predictive model would be extremely useful in narrowing the range of experimental parameters. This will drastically reduce the number of extra attempts at obtaining certain properties in a material and save experimentation time, effort and material to name a few. Four of the most important FAST parameters: target temperature, holding time, heating rate and initial particle size, have been reviewed to assess their effect on the densification, hardening and grain growth of Alumina, Copper, Silicon Carbide, Tungsten and Tungsten Carbide through extensive literature survey. The relationship between each has been incorporated in a Microsoft Excel program which acts as a predictive tool to determine an estimate of the final properties based on the initial parameters chosen. This is done by curve fitting a polynomial onto the existing data points as closely as possible and using the polynomial to obtain final properties as a function of the initial parameters. The model was verified against an existing paper which sought to obtain the optimum sintering parameters for Copper. While the actual experimentation range was 400°C to 800°C, the program would have suggested a much narrower range from 650°C to 800°C and hence saved unnecessary additional efforts.
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