Water absorption of industrial high-density polyethylene biocomposites reinforced with Washingtonia filifera fibers: optimization using Fick’s, RSM, and ANN models

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Abstract The present study aims to investigate the phenomenon of water absorption scattering mechanisms and biocomposite kinetics by the immersion of different HDPE matrix reinforced with different amounts of Washingtonia filifera (WF) fibers (10, 20, and 30% by mass) in distilled water at room temperature. The response surface methodology (RSM) and artificial neural network (ANN) models were examined by considering WF fiber content and immersion time in the water absorption of HDPE/WF biocomposite. In this study, the central composite design (CCD) model of RSM was used to perform test design, modelling, and optimization. The process of water absorption was revealed to be tracking the diffusion mode of Fickian. The results obtained show that the addition of WF fibers to HDPE matrix reduced diffusivity. The results also reveal that ANN models were highly accurate in the prediction of water absorption with the training, validation, and test correlation coefficients of 0.9955, 0.9999, and 0.9915, respectively. The optimal conditions for maximum absorption were a fiber content of 29.88% and an immersion time of 752 hours. Moreover, a highly appropriate model to predict HDPE/WF biocomposites water absorption suitable for various industrial applications is proposed.

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