Machine learning (ML) from large materials datasets enables accelerated materials discovery. Currently, the most accessible way to generate uniform, well-curated, voluminous datasets is by the application of high-throughput first principles computations. Here, we present the guiding principles of using computational data and ML to drive new materials discovery.

中文翻译：

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计算数据驱动的材料发现

来自大型材料数据集的机器学习（ML）可加快材料发现速度。当前，生成统一，精心策划的大量数据集的最便捷方法是应用高通量第一性原理计算。在这里，我们介绍了使用计算数据和ML来驱动新材料发现的指导原则。