On the Various Numerical Techniques for the Optimization of Bone Scaffold

Abstract

As the application of bone scaffolds becomes more and more widespread, the requirements for the high performance of bone scaffolds are also increasing. The stiffness and porosity of porous structures can be adjusted as needed, making them good candidates for repairing damaged bone tissues. However, the development of porous bone structures is limited by traditional manufacturing methods. Today, the development of additive manufacturing technology has made it very convenient to manufacture bionic porous bone structures as needed. In the present paper, the current state-of-the-art optimization techniques for designing the scaffolds and the settings of different optimization methods are introduced. Additionally, various design methods for bone scaffolds are reviewed. Furthermore, the challenges in designing high performance bone scaffolds and the future developments of bone scaffolds are also presented.

Keywords: bio-porous structures; bone scaffolds; mechanical properties; numerical techniques; optimized design.

Figure 1

Cell model after optimization at different positions: (a) M15; (b) M16; (c) M17; (d) M18; (e) M19; (f) M20; and (g) M21 (numbers represent different positions) (Adapted with permission from Liu et al., 2021) [24].

Figure 2

(a) Design and manufacturing workflow of stochastic lattice structures. The specimen displayed was designed with connectivity Z = 12, strut density d = 5, and strut thickness t = 230 µm. (b) Sketches of the design parameters (Adapted with permission from Kechagias et al., 2022) [34].

Figure 3

(a) Comparison of the absolute maximum principal strain distribution between the intact bone model, (b) the one implanted with the original stem, and (c) the new design (Adapted with permission from Cilla et al., 2017) [37].

Figure 4

Inverse homogenization iterative process: The combined genetic algorithm and homogenization based scheme identifies inner material architectures that can optimally meet different target macroscale material properties $\left(G,E,\nu ,\eta \right)$, as encapsulated in the compliance homogenized tensor $S_h$, up to convergence with the target compliance tensor $S_t$ (Adapted with permission from Dos Reis et al., 2022) [46].

Figure 5

(a) Nominal stress–strain curves of G05–G13 structures (G represents gyroid). (b) Drop curve between porosities and measured elastic moduli and yield strengths of as-built samples (Adapted with permission from Ma et al., 2020) [75].

Figure 6

(a) Scaffold with different pore shapes and (b) unit cells (Adapted with permission from Jahir-Hussain et al., 2021) [79].