Multivariate regression analysis of the 3D composites with electroconductive properties for sensors

Abstract

This work presents several aspects of the multivariate regression importance in the analysis of the parameters (dependent and independent variables), which characterize the 3D composite materials with electroconductive properties. The experimental part was developed by using fabrics from 100% cotton, 100% polyamide, and 100% polypropylene fabrics to obtain the electroconductive and electromagnetic properties based on classical technologies and 3D digital printing advanced technology. The fabric was printed with paste containing zinc, copper, nickel, iron oxide II, III, silver, and Graphite microparticles content. Initially, the fabric has coated using the standard technologies implemented by padding (Flame Retardants), scraping, and 3D printing advanced technology for submission of the ESD filaments. For flame retardancy properties, the fabric has been impregnated in a solution of 50% Aflamit and dried at a temperature of 120°C for 3 minutes.