The elastic response of plate-lattices with cubic symmetry can reach the upper, isotropic Hashin-Shtrikman bound. Here, our primary objective is the design of stiff lattices with tailored properties beyond any symmetry or isotropy. We propose a general construction method of plate-lattices, defined as a sequence of plates. We present the large elastic property space, accessible via the geometric control offered by our construction method. Building upon this general formulation, we provide a large-scale comparison to the property spaces of truss- and shell-lattices. Additionally, we observe a distinct correlation between plate orientation and stiffness. To tailor the properties of plate-lattice, we employ a recurrent neural network mapping from a given property to the corresponding structure. Our results highlight the effectiveness of this inverse model in creating plate-lattices with desired properties. We believe that this work holds a paradigm shift in field of inverse design by enabling the efficient customization of the stiffest family of metamaterials.

中文翻译：

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非对称板晶格：基于循环神经网络的最佳超材料设计


具有立方对称性的板晶格的弹性响应可以达到各向同性的 Hashin-Shtrikman 上界。在这里，我们的主要目标是设计具有超越任何对称性或各向同性的定制特性的刚性晶格。我们提出了一种板晶格的通用构造方法，定义为一系列板。我们展示了巨大的弹性属性空间，可以通过我们的构造方法提供的几何控制来访问。基于这个一般公式，我们对桁架和壳格子的属性空间进行了大规模比较。此外，我们观察到板方向和刚度之间存在明显的相关性。为了定制板晶格的属性，我们采用了从给定属性到相应结构的循环神经网络映射。我们的结果强调了这种逆模型在创建具有所需特性的板晶格方面的有效性。我们相信，这项工作通过实现最硬的超材料系列的高效定制，在逆向设计领域实现了范式转变。