The Rise of Machine Learning in Polymer Discovery

In the recent decades, with rapid development in computing power and algorithms, machine learning (ML) has exhibited its enormous potential in new polymer discovery. Herein, the history of ML is described and the basic process of ML accelerated polymer discovery is summarized. Next, the four steps in this process are reviewed, that is, dataset selection, fingerprinting, ML framework, and new polymer generation. Finally, a couple of main challenges for ML accelerated polymer discovery is presented and the outlooks in this field are prospected. It is expected that this review can service as a useful tool for the people who just step into this field and deepen the understanding for the people who are already in this field.

Automated summary

With the rapid development of computing power and algorithms, machine learning has shown its great potential in new polymer discovery. This article provides a history of machine learning and summarizes the basic process of machine learning accelerated polymer discovery. It also reviews the four steps involved in this process, which include dataset selection, fingerprinting, machine learning framework, and new polymer generation. The challenges and future prospects in machine learning accelerated polymer discovery are discussed.