9th Edition of
International Conference on Materials Science and Engineering
March 23-25, 2026 | Singapore
Artificial Intelligence and Materials Science
Artificial Intelligence (AI) is revolutionizing the field of Materials Science and Engineering by accelerating the discovery, design, and optimization of new materials. By leveraging machine learning algorithms, AI can predict material properties, enabling researchers to identify novel materials with desired characteristics more efficiently than traditional methods. AI-driven simulations and data analysis tools are enhancing the understanding of complex material behaviors, reducing the need for costly and time-consuming experiments. This synergy between AI and materials science is particularly impactful in fields like renewable energy, electronics, and nanotechnology, where innovative materials are crucial. Ultimately, AI is paving the way for breakthroughs in material design, promising faster development of high-performance materials for diverse industrial applications.
Stanislaw Dzwigaj
Sorbonne University, France
Harry Ruda
University of Toronto, Canada
Piotr Gebara
Politechnika Czestochowska, PolandSubmit your abstract Today
Title : Determination of phase stress flow curves in dual phase steels through micromechanical adaptive iteration algorithm
Silvie Maria Tanu Halim , McMaster University, Canada
Title : Failure analysis of 70cr2 steel grinding balls in mineral processing; Microstructural and heat treatment effects on the failure of 70cr2 steel grinding balls
Mohammad Pourgharibshahi, Sirjan University of Technology, Iran (Islamic Republic of)
Title : Modeling phase crystallization in ge-rich ge-sb-te pcrams
Alain Portavoce, IM2NP, France
Title : Advancements of ai & ml in material science
M Vishnu Vardhan, Sri Vasavi Engineering College, India
Title : Process parameters optimization and mechanical properties of additively manufactured ankle-foot orthoses based on polypropylene
Mohamed Yousfi, INSA Lyon, IMP Laboratory, France
Title : Piezoelectric materials for biomedical sensing and actuation
Shradha Saxena, Jaypee Institute of Information Technology, India