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Assessment and Optimization of Thermal Stability and Water Absorption of Loading Snail Shell Nanoparticles and Sugarcane Bagasse Cellulose Fibers on Polylactic Acid Bioplastic Films

The optimization and modeling of the parameters, the concentration of polylactic acid (PLA), sugarcane bagasse cellulose fibers (SBCF), and snail shell nanoparticles (SSNP), were investigated for the development of bioplastic films. With the aid of the Box–Behnken experimental design, response surface methodology was used to assess the consequence of the parameters on the water absorption and thermal stability of fabricated bioplastic films. Varied water absorption and thermal stability with different component loading were obtained, evidencing the loading effect of snail shell nanoparticles and sugar bagasse cellulose fibers on bioplastic film’s water absorption and thermal stability. The quadratic polynomial model experiment data offered a coefficient of determination (R2) of 0.8422 for water absorption and 0.8318 for thermal stability, verifying the models’ fitness to develop optimal concentration. The predicted optimal parameters were polylactic acid (99.815%), sugarcane bagasse cellulose fibers (0.036%), and snail shell nanoparticles (0.634%). The bioplastic developed with optimized concentrations of each component exhibited water absorption and thermal stability of 0.45% and 259.7 °C, respectively. The FTIR curves of bioplastic films show oxygen stretching in-plane carbon and single-bonded hydroxyl bending in the carboxylic acids functional group. SEM and TEM images of the bioplastic showed dispersion of the nanoparticles in the matrix, where SSNP is more visible than SBCF, which may be due to the lesser loading of SBCF. The improved properties suggest an optimum concentration of naturally sourced resources for developing bioplastic, which may be used for food and drug packaging for delivery.

Publication date: 21/03/2023

Author: Oluwatoyin J. Gbadeyan

Reference: doi: 10.3390/polym15061557

MDPI (polymers)


This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870292.