2024 Faculty Courses School of Materials and Chemical Technology Undergraduate major in Chemical Science and Engineering
Computational Materials Chemistry
- Academic unit or major
- Undergraduate major in Chemical Science and Engineering
- Instructor(s)
- Sergei Manzhos / Akira Ohtomo
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Tue
- Class
- -
- Course Code
- CAP.N306
- Number of credits
- 100
- Course offered
- 2024
- Offered quarter
- 4Q
- Syllabus updated
- Mar 14, 2025
- Language
- Japanese
Syllabus
Course overview and goals
Computational modeling has taken a critical role in providing mechanistic understanding of materials properties and phenomena, be it mechanical properties or optical properties or electron / ion transport. It has also been gaining importance in predicting / prescreening novel functional materials for technologies ranging from solar cells to jet engines. Specifically computational materials chemistry deals with modeling of properties and phenomena resulting from atomic arrangements and electronic structure, including most optical properties and chemical reactions. In this course you will learn the basics of computational chemistry methods and how to apply them to materials modeling.
Course description and aims
The students will understand the connection between atomistic buildup and structure and properties of materials. The students will understand the principles and methods of computing materials structure and properties ab initio. The students will understand the basics of MD (molecular dynamics) and DFT (density functional theory) and where they are applicable.
Keywords
density functional theory, molecular dynamics, functional materials, materials properties
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Lectures, master-class type computer demonstrations, interractive quizzes
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Principles of computational chemistry and computational materials science | Principles of computational chemistry and computational materials modeling. Students will learn about materials properties and phenomena requiring computational chemistry based approaches for their modeling. |
| Class 2 | Fundamentals of solid-state physics necessary for computational materials chemistry | Students can explain the basics of solid-state physics, which are essential for performing material calculations and understanding the results. |
| Class 3 | Introduction to Density Functional Theory (DFT) | Students understand the principles of density functional theory (DFT) and can explain how the physical properties of materials are calculated using DFT. |
| Class 4 | DFT calculations for solids | Students can explain the structure, magnetic, and electronic states of various solids obtained using density functional theory. |
| Class 5 | Basics of molecular dynamics | Explanation of properties computable with molecular dynamics (MD) and with force fields. Ab initio vs force field MD. Explanation of key approximations and parameters used in force fields and in MD. |
| Class 6 | MD is solid state materials modeling | Explanation of types of force fields used for modeling of materials and phenomena is solid state. Examples from real-life applications. |
| Class 7 | Large scale methods and data-driven materials modeling | Bried introduction to large-scale methods such as DFTB and Orbital-free DFT. Introduction to materials informatics. Ways to deploy data-driven methods in materials modeling and for method improvement. |
Study advice (preparation and review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
David Sholl, Janice A Steckel, “Density Functional Theory” A Practical Introduction”, Cambridge University Press, ISBN: 9781118211045
Efthimios Kaxiras, “Atomic and Electronic Structure of Solids”, Wiley, ISBN: 978-0521523394
D. C. Rapaport, "The Art of Molecular Dynamics Simulation", Cambridge University Press, ISBN: 9780511816581
Reference books, course materials, etc.
David Sholl, Janice A Steckel, “Density Functional Theory” A Practical Introduction”, Cambridge University Press, ISBN: 9781118211045
Efthimios Kaxiras, “Atomic and Electronic Structure of Solids”, Wiley, ISBN: 978-0521523394
D. C. Rapaport, "The Art of Molecular Dynamics Simulation", Cambridge University Press, ISBN: 9780511816581
Evaluation methods and criteria
Tests with elements of computer exercises: 50%
Final exam: 50%.
Related courses
- CAP.O304 ： Computational Molecular Chemistry(Structual Organic Chemistry)
Prerequisites
Nothing special
Contact information (e-mail and phone) Notice : Please replace from ”[at]” to ”@”(half-width character).
Akira Ohtomo: TEL: 03-5734-2145, E-mail: ohtomo.a.aa[at]m.titech.ac.jp *Contact by e-mail is recommended.
Sergei Mazhos: TEL: 03-5734-3918, E-mail: manzhos.s.aa[at]m.titech.ac.jp *Contact by e-mail is recommended.
Office hours
Akira Ohtomo: Weekdays (Advance notice required)
Sergei Mazhos: Weekdays (Advance notice required)
Other
Since this is a lecture that will be held for the first time in 2024, the actual lecture content may differ from the class plan.