Influence of Geometric Design on Mechanical Performance of Auxetic Metastructure
Source abstract
Abstract
Auxetic metamaterials, characterized by a negative Poisson's ratio, offer superior mechanical properties such as enhanced energy absorption and indentation resistance. This study investigates the influence of geometric design on the performance of three 3D‐printed polylactic acid (PLA) arrowhead auxetic structures: Classic, Curved, and Modified. Each configuration was subjected to quasi‐static compression testing and evaluated against a finite element analysis (FEA) model based on key metrics including specific energy absorption ( S E ), Young's modulus (E), and Poisson's ratio ( ν ). Results indicate that geometric variation significantly dictates mechanical response. The Classic arrowhead exhibited strong auxeticity (ν = −1.06) but suffered from stress concentration and early fracture, limiting its S E to 43.92 J/kg. The Curved arrowhead demonstrated improved deformation uniformity and flexibility, yet at the expense of reduced stiffness and lower energy absorption ( S E = 35.12 J/kg). In contrast, the Modified arrowhead, which incorporates a reinforcing ring at the stress concentration zone, outperformed both counterparts. It achieved the highest S E (50.88 J/kg), maintained substantial auxetic behavior (ν = −1.04), and showed exceptional agreement between experiment and simulation, with a discrepancy of only 0.16%. Despite FEA convergence limitations at high displacements, this research validates the Modified arrowhead design as the most structurally efficient, effectively balancing auxetic response with high energy absorption. The findings underscore the critical role of targeted geometric reinforcement in tailoring auxetic metamaterials for advanced applications in impact protection and energy‐dissipative systems.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cellular and Composite Structures · Calcium Carbonate Crystallization and Inhibition · Structural Response to Dynamic Loads
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Civil Engineering College of Engineering and Architecture University College Dublin Dublin Ireland
School of Materials Science and Engineering Beijing Institute of Technology Beijing China
School of Mathematical and Statistical Sciences University of Galway Galway Ireland
Funding
Enterprise Ireland
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