オーセティック材料設計の新しい方法(A New Way of Designing Auxetic Materials)

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2024-05-30 米国国立標準技術研究所(NIST)

オークセティック材料は引っ張ると広がり、圧縮すると縮むという常識を覆す特性を持ちます。NISTの研究者たちは、オークセティック材料の設計を容易にする新しい方法を開発しました。この進展により、より優れたスニーカーのインソールや爆発に耐性のある建物など、新しい世代のオークセティック製品が生まれる可能性があります。新しいアルゴリズムを使用することで、ユーザーは望むポアソン比の値を入力し、最適な構造を提案してもらえます。このツールにより、理論、実験、計算科学が連携し、自然界には存在しない特性を持つオークセティック材料を設計できます。研究者たちはこのアルゴリズムとその実装方法を特許取得しました。

<関連情報>

密度を損なうことなく3次元的に等方的なオーセティックネットワーク構造を実験的に実現する自律的設計アルゴリズム An autonomous design algorithm to experimentally realize three-dimensionally isotropic auxetic network structures without compromising density

Meng Shen,Marcos A. Reyes-Martinez,Louise Ahure Powell,Mark A. Iadicola,Abhishek Sharma,Fabian Byléhn,Nidhi Pashine,Edwin P. Chan,Christopher L. Soles,Heinrich M. Jaeger & Juan J. de Pablo
NPJ Computational Materials  Published:29 May 2024
DOI:https://doi.org/10.1038/s41524-024-01281-y

オーセティック材料設計の新しい方法(A New Way of Designing Auxetic Materials)

Abstract

Auxetic materials have a negative Poisson’s ratio and are of significant interest in applications that include impact mitigation, membrane separations and biomedical engineering. While there are numerous examples of structured materials that exhibit auxetic behavior, the examples of engineered auxetic structures is largely limited to periodic lattice structures that are limited to directional or anisotropic auxetic response. Structures that exhibit a three-dimensionally isotropic auxetic response have been, unfortunately, slow to evolve. Here we introduce an inverse design algorithm based on global node optimization to design three-dimensional auxetic metamaterial structures from disordered networks. After specifying the target Poisson’s ratio for a structure, an inverse design algorithm is used to adjust the positions of all nodes in a disordered network structure until the desired mechanical response is achieved. The proposed algorithm allows independent control of shear and bulk moduli, while preserving the density and connectivity of the networks. When the angle bending stiffness in the network is kept low, it is possible to realize optimized structures with a Poisson’s ratios as low as −0.6. During the optimization, the bulk modulus of these networks decreases by almost two orders of magnitude, but the shear modulus remains largely unaltered. The materials designed in this manner are fabricated by dual-material 3D-printing, and are found to exhibit the mechanical responses that were originally encoded in the computational design engine. The approach proposed here provides a materials-by-design platform that could be extended for engineering of optical, acoustic, and electrical properties, beyond the design of auxetic metamaterials.

1700応用理学一般
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