Investigation and optimization of the tensile properties of nanocomposites based on polylactic acid/polyolefin elastomer: Using fuzzy inference system and particle swarm optimization method

Abstract In this paper, tensile properties of polylactic acid/polyolefin elastomer/multiwall carbon nanotubes/carbon black particles (PLA/POE/MWCNT/CB) nanocomposites were investigated. Nanocomposites, including each nano‐filler at 0, 0.5,1, 1.5, 2, and 3 wt% levels were made by an internal mixer. Tensile tests were carried out to extract the tensile properties of samples. Field emission electron microscopy (FESEM) was also performed to observe the dispersion quality of nano‐fillers in the matrix. FESEM images indicate a proper dispersion of all loadings of nanotubes in the matrix, in contrast the presence of more than 2 wt% of carbon black into the matrix is associated with their agglomeration. Based on the tensile tests, the separate and simultaneous addition of nano‐fillers into binary matrix leads to an increase in strength, modulus, and elongation by 72%, 30%, and 22%, respectively. Furthermore, predicted data from the rules section of the fuzzy inference system (FIS) method with the lowest error led to extracting regression models with R ² above 90% for all responses. Finally, the particle swarm optimization (PSO) method showed that to achieve balancing between the strength and elongation at break the nano‐fillers must be set at 0.64 wt% for nanotubes and 0.94 wt% for carbon black particles.