Modeling and Scaling of Hydroxyapatite Synthesis by Combustion Reaction for Biomedical Applications

Abstract

Abstract This work presents a trend-based mathematical model to optimize and control the pilot-scale synthesis of hydroxyapatite (HAp) via solution combustion. The study establishes a predictable relationship between reaction temperature and precursor mass to overcome typical scaling challenges, such as thermal gradients and localized overheating. Using linear regression, the model identified an optimal condition of 497 °C and a 50 g batch, which successfully yielded 49.8 g of nanocrystalline material. Rietveld refinement quantified 65.1 wt.% HAp and 34.9 wt.% β-TCP, confirming a controlled biphasic composition, and verified the reproducibility of crystallinity under scale-up conditions. Biological assays demonstrated excellent cytocompatibility and absence of intrinsic antimicrobial activity. Collectively, the results validate latent combustion as a rapid, reproducible, and scalable route for producing biomedical-grade HAp, and they demonstrate that trend-based mathematical modeling is a practical tool for predicting structural properties and supporting industrial translation.