AccScience Publishing / IJB / Online First / DOI: 10.36922/IJB025380381
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RESEARCH ARTICLE

Optimal structural characteristics of bone tissue engineering scaffolds from bionics and PSO-BP-NSGA III integrated algorithm

Yuxi Liu1,2†* ,  Aihua Li3† ,  Hong Sun1 ,  Shuge Li1 ,  Song Chen4
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1 School of Smart Health, Chongqing Polytechnic University of Electronic Technology, Chongqing, China
2 College of Mechanical and Vehicle Engineering, Chongqing University, Chongqing 400030, China
3 Department of Gastroenterology, Chongqing University Cancer Hospital, School of Medicine, Chongqing University, Chongqing 400030, China
4 College of Mechanical Engineering, Chongqing University of Technology, Chongqing, China
†These authors contributed equally to this work.
IJB, 025380381 https://doi.org/10.36922/IJB025380381
Received: 15 September 2025 | Accepted: 25 October 2025 | Published online: 27 October 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution 4.0 International License ( https://creativecommons.org/licenses/by/4.0/ )
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Abstract

The repair of large segmental bone defects has always been a significant challenge in clinical practice, with stress shielding being one of the key issues. Here, tree-like fractal biomimetic scaffolds were created based on the morphological similarity between natural trees and bone trabeculae. To optimize the balance between high yield strength and low elastic modulus of the scaffold, an integrated particle swarm optimization-backpropagation-non-dominated sorting genetic algorithm III (PSO-BP-NSGA III) was employed. The scaffolds were fabricated using selective laser melting three-dimensional printing with Ti6Al4V, and their mechanical performance was experimentally evaluated and compared with the algorithm’s predictions. The tree-like fractal scaffold exhibited a radial gradient in porosity, similar to that of natural bone. The second-order fractal scaffold achieved an effective synergy between yield strength and Young’s modulus, demonstrating high yield strength and low Young’s modulus. Additionally, it showed a favorable fluid flow gradient and permeability, with a comprehensive permeability of 3.13 × 10−8 m2. The relative errors between the test and predicted values of yield strength and Young’s modulus were 0.83% and 7.93% respectively, indicating that the PSO-BP-NSGA III integrated algorithm has good predictive ability. These findings establish a validated bionic design framework that integrates advanced optimization algorithms to guide the development of bone tissue engineering scaffolds.  

 

Graphical abstract
Keywords
Integrated algorithm
Multi-objective optimization
Stress shielding
Tree-like fractal scaffold
Young’s modulus
Funding
This work was supported by the Natural Science Foundation of Chongqing Municipality (Grant no: CSTB2023NSCQ-MSX0255), the Key Project of Science and Technology Research Program of Chongqing Education Commission (Grant no.: KJZD-K202203104), and the Science and Technology Research Program of Chongqing Education Commission (Grant no.: KJQN202403112).
Conflict of interest
The authors declare that there is no conflict of interest.
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International Journal of Bioprinting, Electronic ISSN: 2424-8002 Print ISSN: 2424-7723, Published by AccScience Publishing
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