Analysis of Nanoparticles Characteristics with TOPSIS for Their Manufacture Optimization | Journal of Engineering Sciences

Analysis of Nanoparticles Characteristics with TOPSIS for Their Manufacture Optimization

Author(s): Javanbakht T.

Affiliation(s):
Department of Chemistry and Biochemistry, Department of Physics, Concordia University, Richard J. Renaud Science Complex, 7141 Sherbrooke St. West, Montreal, Quebec, Canada H4B 1R6;
Department of Computer Science, University of Quebec in Montreal, 201 President Kennedy St., Montreal, Quebec H2X 3Y7, Canada

*Corresponding Author’s Address: [email protected]

Issue: Volume 9, Issue 2 (2022)

Dates:
Submitted: April 7, 2022
Accepted for publication: July 27, 2022
Available online: August 2, 2022

Citation:
Javanbakht T. (2022). Analysis of nanoparticles characteristics with TOPSIS for their manufacture optimization, Vol. 9(2), pp. C1-C8, doi: 10.21272/jes.2022.9(2).c1

DOI: 10.21272/jes.2022.9(2).c1

Research Area:  MANUFACTURING ENGINEERING: Materials Science

Abstract. The present study focuses on the comparative analysis of superparamagnetic iron oxide nanoparticles (SPIONs) characteristics with the TOPSIS method. The prediction of the characteristics of SPIONs is required for better manufacturing of these nanoparticles. Although the characteristics of these nanoparticles have been investigated, no research has been done on their comparison in order to determine which one of their surface functionalities would be more appropriate for their diverse applications. The objective of this study was to analyze the characteristics of SPIONs without or with surface charge with a prediction model and TOPSIS in order to determine the best nanoparticles. Moreover, the effect of inappropriate consideration of their cost criterion on their ranks was explored with the modified TOPSIS. This analysis showed that the characteristics of SPIONs such as antibiofilm activity, hemocompatibility, activity with hydrogen peroxide, rheological properties, and the labour of their chemical synthesis could affect their ranking. Neutral SPIONs, negatively charged SPIONs, and positively charged SPIONs were ranked as the first, second, and third candidates, respectively. However, the improvement of the activity of positively charged SPIONs with hydrogen peroxide showed an increase to 0.3 instead of 0.2, which resulted in a better rank of these nanoparticles in comparison with that of the same nanoparticles in the first analysis series. One of the advantages of this study was to determine the impact of the characteristics of SPIONs on their ranking for their manufacturing. The other advantage was getting the information for further comparative study of these nanoparticles with the others. The results of this work can be used in manufacturing engineering and materials science.

Keywords: SPIONs, chemical activity, biological properties, rheological properties, TOPSIS, industrial growth, manufacturing engineering.

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