Optimization of chemical synthesis output with topsis

Abstract

The present study focuses on a new application of a decision-making process using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for the optimization of the chemical synthesis output. This investigation is important as many chemical reactions have been performed in labs without any analysis of their optimization. The factors that affect the chemical synthesis output such as catalyst, nanosensor network, and temperature have been considered in this study. Moreover, labor that corresponds to the prices of chemicals that are used in chemical reactions has also been considered. Different chemical synthesis procedures with or without these factors have been analyzed in the current study. In the first series of analyses, the same weight values were considered for all criteria, whereas in the second series of analyses, the weight values for the nanosensor network and labor were more than those of catalyst and temperature. The obtained results showed that the consideration of profit criteria and cost criteria and equal or different weights for the candidates could affect the output of TOPSIS. Therefore, the prediction of the chemical synthesis output using this algorithm for three different conditions for performing chemical reactions. Moreover, it was shown that different considerations of these conditions could help optimize the reactions. In the first series of analysis, the second candidate was ranked in the first position, whereas the third candidate and the first candidates were positioned in the second and third positions, respectively. The ranking of candidates was different in the second series of analysis as the first, second, and third candidates were ranked in the first, second, and third positions, respectively. The results of this investigation can be used for the optimization of chemical reactions and lab procedures.