What is it about?
We developed a computational protocol to autonomously design three-dimensional isotropic auxetic materials, materials with a negative Poisson's ratio, by directing molecular dynamics simulations with data-driven algorithms. The computational design was reproduced and precisely validated in experiments by dual-material 3D printing.
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Why is it important?
Auxetic materials, characterized by a negative Poisson's ratio, exhibit exceptional compressibility. Traditionally, most auxetic materials demonstrate anisotropic behaviors, meaning they only exhibit auxetic properties in specific stress orientations. Additionally, many of these materials often suffer from compromised mechanical integrity, limiting their practical applications. The development of isotropic auxetic materials is highly desirable for diverse applications such as impact mitigation and soundproofing. However, designing such materials in three dimensions poses a greater challenge compared to two-dimensional designs due to stricter mechanical modulus requirements. Our innovative algorithm overcomes these challenges, enabling the creation of three-dimensional isotropic auxetic materials regardless of the initial structure. This breakthrough has been validated through 3D-printed material experiments, confirming that our designs are not only isotropically auxetic but also retain their mechanical integrity, making them ideal candidates for impact mitigation and other applications.
Perspectives
Our inverse design algorithm stands out for its versatility and robustness, capable of optimizing target properties that are functions of design parameters, whether linear or nonlinear. This adaptability allows the algorithm to be universally applicable to a wide range of materials. It can be employed to design materials with negative thermal expansion, allosteric materials, virus-resistant surfaces, and ion-selective membranes, among others. As long as the target property can be quantified, our algorithm can efficiently tailor the material's design to meet specific performance requirements.
Meng Shen
California State University Fullerton
Read the Original
This page is a summary of: An autonomous design algorithm to experimentally realize three-dimensionally isotropic auxetic network structures without compromising density, npj Computational Materials, May 2024, Springer Science + Business Media,
DOI: 10.1038/s41524-024-01281-y.
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