Particle agglomeration and interphase interactions affect Young’s modulus of nanobiocomposites: eyes at mathematical modeling

Computational modeling is a new approach to optimize Young’s modulus of scaffolds by performing a minimal number of experiments. However, presenting a modeling algorithm to predict Young’s modulus and characterize the governing parameters is a challenging task. Here, a novel modeling approach has been proposed to estimate Young’s modulus of scaffolds, considering particle agglomeration and interphase interactions. Employing the characteristic parameters of these two phenomena, we modified the Maxwell model using a simple three-step algorithm to determine the optimal value of these parameters and predict Young’s modulus. Interestingly, the model provides a precision of more than 95% for all the studied cases and presents a remarkably better performance compared to the two other models. For instance, the proposed model has reduced the average absolute relative error of Young’s modulus of poly (3-hydroxybutyrate)-keratin/hydroxyapatite nanorods from 25.1% to 0.08%, demonstrating the high efficiency of this model in predicting Young’s modulus of scaffolds. The results of this study could lighten the way of fabricating nanobiocomposites with optimal mechanical properties, spending lower cost and energy.