Basic Concepts and Tools of Artificial Intelligence in Polymer Science

Abstract

In recent years, artificial intelligence (AI) has emerged as a transformative force across scientific disciplines, offering new ways to analyze data, predict material properties, and optimize processes. Yet, its integration into polymer science remains a challenge, as the field has traditionally relied on empirical methods and intuition-driven discovery. The complexity of polymer systems, combined with technical barriers and a lack of interdisciplinary training, has slowed AI adoption, leaving many researchers uncertain about where to begin. This perspective serves as an entry point for polymer scientists, introducing AI’s real-world applications, accessible tools, and key challenges. Rather than an exhaustive review for specialists, it aims to lower entry barriers and spark interdisciplinary dialogue, bridging the gap between conventional polymer research and data-driven innovation. As AI reshapes material discovery, those who embrace this transformation today will define the future of polymer science.