A survey of AI-supported materials informatics

The evolution from traditional artificial intelligence (AI) to advanced AI is explored in the predictive and structural analysis in materials informatics, highlighting how advancements in machine learning have revolutionised the discovery and design of new materials and molecular structures. It examines how traditional AI, with its reliance on heuristic models and empirical data, has paved the way for the emergence of generative AI, which leverages advanced machine learning frameworks to predict material properties, structural design and analysis and synthesise new materials. The work highlights key developments, compares the effectiveness of various approaches, relevant databases and software frameworks in material informatics, and discusses the transformative impact of traditional and advanced AI in accelerating materials discovery and innovation. Through a detailed analysis of recent advancements, challenges, and future prospects, this paper aims to offer valuable insights into the evolving landscape of AI-driven materials informatics.