Comparison of the design maps of TPMS based bone scaffolds using a computational modeling framework simultaneously considering various conditions

Abstract

In recent years, the triply periodic minimal surface (TPMS)-based scaffolds have been served as one of the crucial types of structures for biological replacements, the energy absorber, etc. Meanwhile, the development of additive manufacturing (AM) has facilitated the production of TPMS scaffolds with complex microstructures. However, the design maps of TPMS scaffolds, especially considering the AM constraints, remain unclear, which has hindered the design and application of TPMS scaffolds. The aims of the present study were to develop an efficient computational modeling framework for investigating the design maps of TPMS scaffolds simultaneously considering the AM constraints, the biological requirements, and the structural anisotropy. To demonstrate the computational framework, five widely-used topologies of the TPMS-based scaffolds (i.e. the Diamond, the Gyroid, the Fischer-Koch S, the F-RD, and the Schwarz P) were used, whose design maps for the surface-to-volume ratio and the effective elastic modulus were also investigated. The results showed that as the porosities increase, the design ranges of the surface-to-volume ratios decreases for all the structures. Compared with the effect of the constraint for the pore size, the minimal structural thickness for AM constraint has a greater effect on the surface-to-volume ratio. Regarding the elastic modulus, in the region of low porosity (approximately 0.5–0.7), the range for the effective elastic modulus of Schwarz P is the widest (approximately 2.24–32.6 GPa), but the Gyroid can achieve both high porosity and low effective elastic modulus (e.g. 0.61 GPa at the porosity of 0.90). These results and the method developed in the present study provided important basis and guidance for the design and application of the TPMS-based porous structures.

Inverse design of anisotropic bone scaffold based on machine learning and regenerative genetic algorithm

“…The stress distribution under compression is shown in Figure 10 . The proposed supporting reaction force can be obtained through formula calculation ( Feng et al, 2021 ; Lu et al, 2022 ), and the partial stiffness matrix of the structure was compared with the target value. The comparison between the results and the target value is as shown in Figure 11 .…”

“…The FE method was used to calculate the equivalent stiffness matrix of the human bone from computed tomography (CT) images ( Figure 3 ). The 2D image is re-established as a 3D model by superposition, and then the finite element method is utilized to solve the , with 1,2,3 in the parameters corresponding to the x , y , and z directions, respectively, as detailed in the literature ( Xiao et al, 2021 ; Lu et al, 2022 ). The stiffness matrix was then compared with those in the existing literature to verify its rationality ( Kalouche et al, 2010 ; Wang et al, 2016 ).…”

Customized Artificial Implants: Bionic Design and Multiscale Evaluation

“…The FE method was used to calculate the equivalent stiffness matrix of the human bone from computed tomography (CT) images (Figure 3). The 2D image is re-established as a 3D model by superposition, and then the finite element method is utilized to solve the C ij , with 1,2,3 in the parameters corresponding to the x, y, and z directions, respectively, as detailed in the literature Frontiers in Bioengineering and Biotechnology frontiersin.org (Xiao et al, 2021;Lu et al, 2022). The stiffness matrix was then compared with those in the existing literature to verify its rationality (Kalouche et al, 2010;Wang et al, 2016).…”

Novel 3D printed TPMS scaffolds: microstructure, characteristics and applications in bone regeneration

“…This is because the preparation process has not yet reached the ideal requirements, which requires us to continuously improve the technology and overcome the process limits of 3D printing. 72 , 76 , 100 – 102 …”