If one could systematically search the calculated electronic structures of materials, already available on online materials databases, for electronic characteristics that are associated with superconductivity, then the rate of new superconductor discovery could be accelerated. Here we test whether one such proposed characteristic, flat bands in the calculated electronic density of states, can broadly distinguish known superconductors from known non-superconductors. Our data mining exercise, performed on the materials for which the relevant data can currently be downloaded, does not support flat bands as strong predictors of superconductivity in materials. Beyond the specific test, our study's limitations underscore the importance of standardizing digital resources for achieving the accelerated materials discovery paradigm promised by the Materials Genome Initiative.

如果人们可以系统地搜索已计算的材料电子结构（已经在在线材料数据库中找到）与超导性相关的电子特性，那么可以加快发现新的超导体的速度。在这里，我们测试一种这样提议的特性，即计算出的状态电子密度中的平坦带，能否将已知的超导体与已知的非超导体大致区分开。我们对当前可以下载相关数据的材料进行的数据挖掘练习不支持平坦带，因为平坦带是材料超导性的有力预测器。除了特定的测试，我们的研究