Foundations of Computational Materials Science

Materials science is rapidly evolving, driven by the power of computational methods to accelerate discovery and innovation. Understanding these approaches is crucial for modern materials professionals. This course will guide you through the foundational principles of computational materials science, equipping you with the knowledge to interpret and apply various simulation techniques. By the end, you'll be able to understand how computational tools contribute to materials design, characterization, and property prediction. What you'll learn: - Understand the core concepts and applications of computational materials science. - Learn to distinguish between different simulation methods, including quantum mechanical and classical approaches. - Apply foundational principles of density functional theory (DFT) and molecular dynamics (MD) simulations. - Analyze and interpret simulation results for material properties and behavior. - Explore the basics of integrating data-driven approaches and machine learning in materials discovery. - Practice evaluating the strengths and limitations of various computational models. The course begins with an introduction to the field, covering essential terminology and the role of computation in materials discovery. It then delves into fundamental simulation techniques, explaining their theoretical underpinnings and practical applications. The final sections cover data analysis of simulation output and modern trends in the field, including machine learning applications. This course is designed for absolute beginners in computational materials science. No prior experience with advanced computational tools or materials simulation is required. Begin your journey into the exciting world of computational materials science today.