Flat band systems are currently under intense investigation in quantum materials, optical lattices, and metamaterials. These efforts are motivated by potential realization of strongly correlated phenomena enabled by frustration-induced flat band dispersions; identification of candidate platforms plays an important role in these efforts. Here, we develop a high-throughput materials search for bulk crystalline flat bands by automated construction of uniform-hopping near-neighbor tight-binding models. We show that this approach captures many of the essential features relevant to identifying flat band lattice motifs in candidate materials in a computationally inexpensive manner, and is of use to identify systems for further detailed investigation as well as theoretical and metamaterials studies of model systems. We apply this algorithm to 139,367 materials in the Materials Project database and identify 63,076 materials that host at least one flat band elemental sublattice. We further categorize these candidate systems into at least 31,635 unique flat band crystal nets and identify candidates of interest from both lattice and band structure perspectives. This work expands the number of known flat band lattices that exist in physically realizable crystal structures and classifies the majority of these systems by the underlying lattice, providing additional insights for familiar (e.g., kagome, pyrochlore, Lieb, and dice) as well as previously unknown motifs.

平带系统目前正在量子材料、光学晶格和超材料领域进行深入研究。这些努力的动机是由挫折引起的平带色散所实现的强相关现象的潜在实现；确定候选平台在这些努力中发挥着重要作用。在这里，我们通过自动构建均匀跳跃近邻紧束缚模型来开发高通量材料搜索块状晶体平带。我们表明，这种方法以计算成本低廉的方式捕获了与识别候选材料中的平带晶格图案相关的许多基本特征，并且可用于识别系统以进行进一步的详细研究以及模型系统的理论和超材料研究。我们将此算法应用于材料项目数据库中的 139,367 种材料，并识别出至少包含一个平带元素子晶格的 63,076 种材料。我们进一步将这些候选系统分类为至少 31,635 个独特的平带晶体网，并从晶格和能带结构的角度识别感兴趣的候选系统。这项工作扩展了物理上可实现的晶体结构中存在的已知平带晶格的数量，并通过底层晶格对大多数这些系统进行了分类，为熟悉的（例如，kagome、烧绿石、Lieb 和 dice）以及以前的系统提供了额外的见解未知的图案。