The development of hybrid materials that integrate bioactive and antimicrobial properties within a biodegradable and biocompatible polymer matrix is a key focus in current biomedical research and applications. A significant research gap exists in the field of PHBV nanocomposites, particularly concerning those that simultaneously incorporate both ZnO and HAP particles. This study focuses on the fabrication and characterization of innovative hybrid bionanocomposites composed of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) combined with zinc oxide (ZnO) and silicon-doped hydroxyapatite (SiHAP) nanocrystals. The hybrid nanocomposite with 5 wt% ZnO and 0.1 wt% SiHAP exhibited the highest storage modulus, suitable for load-bearing applications. DMA analysis at 20 °C showed significant increases in storage (50.8 %) and loss (92 %) moduli for this composition. This particular group demonstrated cellular viability of approximately 100 %. Our results suggest that these newly developed novel composites demonstrate exceptional biocompatibility, bioactivity, and antimicrobial properties. As a result, they show significant potential as tissue engineering tools for addressing bone tissue disorders. Various Machine learning (ML) algorithms were applied to model the dynamic mechanical properties of nanocomposites based on experimental data. The study shows that these models provide accurate insights into the dynamic mechanical behavior of nanocomposites, offering a reliable method for optimizing their properties.
Keywords: Biocompatible polymers; Biocomposites; Machine learning; Mechanical properties; Reinforcements.
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