Materials design has entered the well-applauded machine learning era. In the near future, artificial systems would be able to predict materials with desired properties without human intervention and may outperform humans in various aspects. It is foreseen that many routine computational studies will be replaced by machines, which brings us a serious question, how can we <i>survive</i> in the machine learning era?<br/>In this talk, I will present some lessons learned from our recent computational design of 2D Frustrated Lewis pair catalysts and nanosheets containing hyprcoordinate atoms. If well adapted, we should be able to benefit from machine learning, which enables us to focus on more high-value and creative research. Meanwhile, we also need to prepare ourselves and retrain our students to welcome the emerging new materials prediction paradigm.

How to survive in machine learning era: Some recent lessons on 2D materials

256th National Meeting (2018)

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