We present a simple yet effective method for structure prediction of two-dimensional structures. The method is based on a combination of neural networks and evolutionary techniques. It allows finding pristine 2D structures as well as structures grown on a substrate. Conducted tests show, that the method is efficient and the calculations, based only on the information of stoichiometry, can lead to stable structures. Since the algorithm is able to address structures on a given substrate, it can be useful from the experimental point of view.

中文翻译：

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基于神经网络驱动进化技术的二维材料结构预测

我们提出了一种简单而有效的二维结构预测方法。该方法基于神经网络和进化技术的结合。它允许找到原始的 2D 结构以及在基板上生长的结构。进行的测试表明，该方法是有效的，并且仅基于化学计量信息的计算可以导致稳定的结构。由于该算法能够对给定衬底上的结构进行寻址，因此从实验的角度来看它是有用的。