Selecting the Appropriate Carbon Source in the Synthesis of SiC Nano-Powders Using an Optimized Fuzzy Model

In this study, different sources of carbon in the synthesis of silicon carbide were evaluated using a multi-attribute group decision-making fuzzy model including IF-MAGDM method. In this model, the aim was to find the carbon precursor which has the minimum price, highest carbon content, good water solubility, lowest synthesis temperature, and the optimum crystallite size. Based on the results obtained from mentioned method, sugar was the best candidate. Therefore, sugar was selected as the efficient carbon source in the synthesis of SiC, also tetraethyl ortho-silicate was used as the source of silicon. The synthesis temperature was 800 degrees C, which is a relatively low temperature for the synthesis of crystalline SiC. To optimize the carbothermal process, microwave heating and just 15 min were enough to form crystalline SiC nanostructures. Various analyses were used for efficient characterize of the products. TGA-DTA were used to investigate thermal behaviours of the samples. XRD results showed that the SiC powder prepared by microwave heating was fully crystalline phases. FE-SEM and TEM analyses showed the nanometric nature in average particle size distributions of products with a flake-like morphology.

Automated summary

In this study, a multi-attribute group decision-making fuzzy model was used to evaluate different carbon sources for the synthesis of silicon carbide. Sugar was identified as the best carbon precursor, leading to the successful synthesis of crystalline SiC nanostructures. Multiple analyses were employed to characterize the products effectively.