2025 (Current Year) 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 / Yasunobu Ando
- Class Format
- Lecture (Face-to-face)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 3-4 Tue (W9-327(W936))
- Class
- -
- Course Code
- CAP.N306
- Number of credits
- 100
- Course offered
- 2025
- Offered quarter
- 4Q
- Syllabus updated
- Sep 30, 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 DFT (density functional theory) and how it is used to simulate properties of materials and gain mechanistic insight into phenomena.
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 (1) "general concept of translational symmetry in crystals on solid state physics" |
Students can explain the basics of solid-state physics, which are essential for performing material calculations and understanding the results. In particular, they need to explain about crystal descriptions and construction of the reciprocal lattice. |
| Class 3 | Fundamentals of solid-state physics necessary for computational materials chemistry (2) "Electron waves in crystals" |
Students can explain the basics of solid-state physics, which are essential for performing material calculations and understanding the results. In particular, they need to explain about density of states, band structures and Fermi surface for two- and three-dimensional crystals. |
| Class 4 | Fundamentals of solid-state physics necessary for computational materials chemistry (3) "Elastic wave propagation in periodic media and phonons" |
Students can explain the basics of solid-state physics, which are essential for performing material calculations and understanding the results. In particular, they need to explain about elastic waves in materials and descriptions of phonon. |
| Class 5 | Basics of density functional theory (DFT) |
Student will learn the principles of density functional theory, key equations, and approaches used to solve them. |
| Class 6 | DFT for solid state materials modeling |
Using examples from real-life applications, the stundets will learn how DFT is used to model structures and properties of solid materials and interfaces and to gain mechanistic insight into phenomena. |
| 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
Evaluation methods and criteria
Tests: 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).
Sergei Mazhos: TEL: 03-5734-3918, E-mail: manzhos.s.aa[at]m.titech.ac.jp *Contact by e-mail is recommended.
Yasunobu Ando: TEL: 045-924-5428, E-mail: yasunobu.ando[at]cls.iir.isct.ac.jp *Contact by e-mail is recommended.
Office hours
Sergei Mazhos: Weekdays (Advance notice required)
Yasunobu Ando: Weekdays (Advance notice required)