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August 17, 2025Advanced Engineering Materials

Machine‐Learning‐Assisted Design and Optimization of Auxetic Structures: A Bioinspired Approach to Mimic Natural Tissues

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Authors

MSMasoud ShirzadMCMorassa Jafari ChashmiSKSaeideh Khakzadkelarijani

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Overview

This analysis reveals how auxetic structures enhance Young's modulus in tissue regeneration, suggesting machine learning optimizes design.

Key Points

  • Young's modulus increased by 135.5% in sharp sinus and curved sinus structures, enhancing their mechanical properties.
  • A comparative analysis showed significant effects of design variables on auxeticity and tensile properties, indicating customization benefits.
  • The methodology integrates finite element method with machine learning for cost-effective structure optimization in biomedical applications.
  • Higher auxeticity in re-entrant designs suggests suitability for tendon tissue engineering and diverse applications in biomedicine.

Cite This Study

Shirzad et al. (2025) studied this question.

synapsesocial.com/papers/68af453aad7bf08b1ead2aa5https://doi.org/10.1002/adem.202500377
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Also Consider

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  1. 1Bioinspired 3D‐Printed Auxetic Structures with Enhanced Fatigue Behavior2024 · 14 citations
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  4. 4State-of-the-art in 3D printing of auxetic structures: recent progress and perspectives2026
  5. 5Design of 2D re-entrant auxetic lattice structures with extreme elastic mechanical properties2024 · 8 citations