We provide a review of machine learning (ML) tools for material discovery and sophisticated applications of different ML strategies. Although there have been a few published reviews on artificial intelligence (AI) for materials with an emphasis on a single material system or individual methods, this paper focuses on an application-based perspective in AI-enhanced material discovery. It shows how AI strategies are applied through material discovery stages (including characterization, property prediction, synthesis, and theory paradigm discovery). Also, by referring to the ML tutorial, readers can acquire a better understanding of the exact functions of ML methods in each application and how these methods work to realize the targets. We are aiming to enable a better integration of AI methods with the material discovery process. The keys to successful applications of AI in material discovery and challenges to be addressed are also highlighted.

我们提供了机器学习（ML）工具的概述，以用于材料发现和不同ML策略的复杂应用。尽管已经有一些关于材料的人工智能（AI）的发表评论，重点是单一材料系统或单独的方法，但本文重点关注AI增强材料发现中基于应用程序的观点。它显示了如何在材料发现阶段（包括表征，特性预测，合成和理论范式发现）应用AI策略。此外，通过参考ML教程，读者可以更好地了解每个应用程序中ML方法的确切功能以及这些方法如何实现目标。我们旨在使AI方法与材料发现过程更好地集成。