Abstract

Artificial Intelligence (AI) is profoundly transforming materials science by accelerating the discovery, design, and optimization of materials. This paper provides an overview of the current applications of AI in materials science, including high-throughput screening for material discovery, optimization of material properties, and integration of data from experiments and simulations. It highlights how machine learning models and generative algorithms are revolutionizing the field by enabling predictive maintenance, enhancing quality control, and fostering innovative material designs. Looking ahead, the paper discusses future prospects such as personalized materials, autonomous research laboratories, and the synergy between AI and quantum computing. It also addresses ethical and sustainability considerations crucial for the responsible advancement of AI-driven materials science. This comprehensive review underscores AI's role in reshaping materials science and outlines the potential for future breakthroughs and interdisciplinary collaboration.