Momordica augustisepala L. stem fibre reinforced thermoplastic starch: Mechanical property characterization and fuzzy logic artificial intelligent modelling

Abstract

Understanding the effect of reinforcement scales on the properties of fibre reinforced composite and establishment of suitable material property predictive model are important for successful composite development. This study investigated the effect of micro and nano scale Momordica augustisepala stem natural fibre (MASNF) on the mechanical properties of cassava starch thermoplastic (CSTP). Thereafter, fuzzy logic artificial intelligent method (FLAIM) was utilized to predict the mechanical properties. Micro and nano MASNF reinforcements were extracted through alkalization, bleaching and acid hydrolysis methods. For environmental preservation purposes, starch was extracted from cassava processing factory's liquid waste. Micro and nano MASNF reinforced CSTP film samples at different fibre weight fraction were developed by casting method. The morphological, crystallinity and mechanical properties of the samples were established using SEM, XRD and Instron Universal Machine, respectively. The experimental data were modelled and predicted with FLAIM using Matlab software. SEM and TEM showed that used chemical treatments were sufficient to extract suitable MASNF reinforcements. Crystallinity of raw, alkalized, and bleached and nano MASNF were 24.00, 36.96 and 45.00 and 62.00, respectively. Nano and micro MASNF improved the mechanical properties of CSTP film; however, nano MASNF had the highest tensile strength and modulus of 6.35 ​MPa and 245.22 ​MPa, respectively at 9 ​wt % fibre weight fraction. FLAIM was effective to predict the observed mechanical properties with average model accuracy and coefficient of determination that ranged between 92.08 – 97.18 and 0.7981–0.9969, respectively. It is concluded that these results have prospect in technical and economic development of composite.