Optimization of preparation parameters of palm oil-based nanofuel with MWCNT for stability using Taguchi-grey relation analysis (GRA) combination

Abstract

This research optimizes the preparation parameters of palm oil-based nanofuel and Multi Wall Carbon Nanotube (MWCNT) to produce stable nanofuel. The parameters optimized include stirrer speed, sonication time, sonication power, and surfactant ratio, with stability measured through absorbance and sedimentation ratio (SR). The Taguchi method, using an L9 orthogonal array designed with minitab 19.0 software, was employed for single-objective optimization, while Grey Relation Analysis (GRA) is applied for multi-objective optimization. Experimental results show that the optimal conditions for absorbance are stirrer speed of 1000 rpm, sonication time of 30 minutes, sonication power of 200 watts, and surfactant ratio of 1, whereas for sedimentation ratio the optimal conditions are stirrer speed of 1000 rpm, sonication time of 30 minutes, sonication power of 150 watts, and surfactant ratio of 1. ANOVA analysis reveals that surfactant concentration contributes the most to nanofuel stability, with contributions of 79.63% for absorbance and 82.60% for sedimentation ratio. Multi-objective GRA optimization results also show that surfactant concentration is the most dominant factor, contributing 71.5% to the Grey Relational Grade (GRG). The consistency of optimal parameters yielded by both Taguchi and GRA methods reinforces the validity and consistency of this study's results. This research provides a strong foundation for the development of more stable nanofuels, potentially enhancing energy efficiency and sustainability. These findings offer practical guidelines for real-world applications and make significant contributions to nanofuel technology.