Abstract
This introductory chapter presents material modeling, or computational materials science, as a discipline that attempts to computationally predict properties of materials and design materials with given properties, and discusses how machine learning can help in this task. At the center of material modeling is the relationship between the atomic structure and material properties. This relationship is introduced together with the quantum and statistical mechanics as the two main tools for material modeling from first principles, which should also guide the development of new machine learning approaches to computational materials science. Material modeling operates with an abundance of technical terms, and some of these are explained in a glossary at the end of the chapter.
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Hermann, J. (2020). Introduction to Material Modeling. In: Schütt, K., Chmiela, S., von Lilienfeld, O., Tkatchenko, A., Tsuda, K., Müller, KR. (eds) Machine Learning Meets Quantum Physics. Lecture Notes in Physics, vol 968. Springer, Cham. https://doi.org/10.1007/978-3-030-40245-7_2
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DOI: https://doi.org/10.1007/978-3-030-40245-7_2
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