AI methods in materials design, discovery and manufacturing: A review.

In the advent of the digital revolution, Artificial Intelligence (AI) has emerged as a pivotal tool in various domains, including materials design and discovery. This paper provides a comprehensive review of the AI methodologies integrated within this context, encompassing materials informatics, density functional theory, molecular dynamics, and finite elements analysis. We further delve into the transformative role of AI within process engineering, manufacturing, and industry 4.0, with a focus on manufacturing process optimization techniques. Highlighting the importance of active learning, self-correcting processing, and digital twins in the era of smart manufacturing, this review underscores the impact of big data and data quality. The paper provides an insight into the challenges and future prospects, pointing towards the tremendous potential AI holds for revolutionizing the field of materials science. • Comprehensive exploration of AI methods in Materials Design and Discovery. • Review of the transformative role of AI within process engineering. • Discussion on the importance of data quality and quantity in the era of Big Data. • Insight into challenges and potential of AI in the field of Materials Science. [ABSTRACT FROM AUTHOR]