Prediction of tensile strength of biochar filled polylactic acid composites via box-behnken design

Abstract

Most studies on tensile strength of agricultural residue biochar fiber-reinforced PLA composites make use of the one-factor at a time method, which involves changing one of the independent factors at a time while keeping others constant. A shortcoming with this technique is that it cannot consider possible interactions between parameters and does not provide the optimum combination of factors to predict the maximum tensile strength of composites. In this study, Response Surface Methodology (RSM) was applied to optimize the tensile strength of rice husks biochar fiber reinforced polylactic acid composites. Biochar loading (10, 20, and 30 wt%), magnesium hydroxide (Mg(OH)₂) loading (5,7.5, and 10 wt%), and biochar length (0.3,1.8, and 3.3 mm) were used to design the experiments using the Box-Behnken design (BBD). PLA composites were prepared using compression molding. Experimental results were analyzed by analysis of variance and fitted to a quadratic model by using multiple regression analysis. The desirability function revealed that the values of process variables leading to optimized tensile strength (25.46 MPa) were 30 wt%, 5 wt% and 2.50 mm for biochar loading, Mg(OH)₂ loading, and biochar length, respectively. Analysis of Variance results revealed Mg(OH)₂ content and biochar content as the most significant model terms. From validation experiments, a high degree of correlation was found between the actual values and the predicted values of tensile strength, with an R² value of 0.9943. TGA results showed the combustion process took place in three main stages. Coats-Redfern method had a 0.9522 coefficient of determination value, signalling satisfactory fit of the TG data. The optimized composite was favored to format activated complex due to low energy barrier (<7 kJ/mol) between activation energy and enthalpy values.