Machine Learning in Polymer Science: Emerging Trends and Future Directions

Artificial intelligence (AI) and machine learning (ML) have advanced tremendously in the previous 5 years regarding polymer science. Polymers are materials with enormous versatility that are now widely used. Polymers have found extensive applications in several fields such as energy storage, construction, medical, aerospace, and other industries. This study is presently in the era of the 4.0 industry, a transformative period that is profoundly reshaping both business and society in an unprecedented manner specifically in developing countries. Data-driven strategies for process analysis and control are crucial in expediting the creation of polymer production processes while maintaining product quality and avoiding a rise in production cost. More and more scientists are utilizing polymer informatics and data science to create new materials and understand the connections between their molecular structure and characteristics. The field of polymer informatics is relatively new. Even though there are a lot of helpful databases and tools accessible, not many are used frequently. The application of AI is starting to have an influence on several aspects of human existence, including fields such as science and technology. Polymer informatics is a field that utilizes AI and ML techniques to enhance the process of developing, designing, and discovering polymers. Based on these ideas, it examines the burgeoning fields of ML-assisted polymer informatics in this research. It also looks at these new developments in the polymeric informatics ecosystem and talks about upcoming potential and problems for applications.