Novel technologies and new materials are in high demand for future various applications to overcome the fundamental limitations of current techniques. For example, the nanomaterials are in high demand for the miniaturization of electric devices. Spintronics is one of the most viable solutions for green electric devices. The single-atom catalysts can provide a 100% utilization rate. Heterojunctions hold promise for applications in energy conversion and storage. Two-dimensional (2D) materials show promising applications in various applications because they can be tailored to the specific property on which a technology is based and may be compatible with other technologies. Although the number of experimentally discovered 2D materials is growing, the speed is very slow and only a few dozen 2D materials have been synthesized or exfoliated since the discovery of graphene. Recently, a novel computational technique, dubbed high-throughput computational materials design, has become a burgeoning area of materials science, which is a combination of quantum mechanical theory, materials information, and database construction with intelligent data mining. This new and powerful tool can greatly accelerate the discovery, design, and application of 2D materials by creating a database containing a large number of 2D materials with calculated fundamental properties and then intelligently mining (via high-throughput automation or machine learning) the database in the search for 2D materials with the desired properties for particular applications, such as energy conversion/storage, catalysis, water purification, electronics, and optoelectronics.

中文翻译：

---

面向各种应用的二维功能材料的高通量计算发现与智能设计

新技术和新材料对未来各种应用的需求很高，以克服当前技术的基本限制。例如，纳米材料对电子设备的小型化有很高的需求。自旋电子学是绿色电子设备最可行的解决方案之一。单原子催化剂可以提供100%的利用率。异质结有望应用于能量转换和存储。二维 (2D) 材料在各种应用中显示出有前途的应用，因为它们可以根据技术所基于的特定属性进行定制，并且可以与其他技术兼容。尽管通过实验发现的二维材料的数量正在增加，速度非常慢，自发现石墨烯以来，只有几十种二维材料被合成或剥离。最近，一种被称为高通量计算材料设计的新型计算技术已成为材料科学的一个新兴领域，它是量子力学理论、材料信息和数据库构建与智能数据挖掘的结合。这种强大的新工具可以通过创建包含大量具有计算的基本特性的二维材料的数据库，然后智能挖掘（通过高通量自动化或机器学习）数据库，从而大大加快二维材料的发现、设计和应用。寻找具有特定应用所需特性的二维材料，例如能量转换/存储、催化、