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School of Engineering
- Undergraduate major in Mechanical Engineering
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- Undergraduate major in Electrical and Electronic Engineering
- Undergraduate major in Information and Communications Engineering
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- Common courses
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
- School of Environment and Society
- 工学院，物質理工学院，環境・社会理工学院共通科目
- Liberal arts and basic science courses
- First-Year Courses
- School of Science
- School of Engineering
- School of Materials and Chemical Technology
- School of Computing
- School of Life Science and Technology
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School of Environment and Society
- Department of Architecture and Building Engineering
- Department of Civil and Environmental Engineering
- Department of Transdisciplinary Science and Engineering
- Department of Social and Human Sciences
- Department of Innovation Science
- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Graduate major in Physics
- Instructor(s)
- Miyake Takashi
- Class Format
- Lecture (Livestream)
- Media-enhanced courses
- Day/Period(Room No.)
- Intensive ()
- Group
- -
- Course number
- PHY.P687
- Credits
- 1
- Academic year
- 2022
- Offered quarter
- 2Q
- Syllabus updated
- 2022/3/16
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
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Course description and aims
First-principles calculation is a powerful tool for materials research. Topics of this course include (1) the basic theory of first-principles calculation, (2) understanding of material properties based on first-principles electronic structure calculation, and (3) materials informatics.
Students will learn how to understand and predict properties of real materials.
Student learning outcomes
By the end of this course, students will be able to explain (i) basic theory of first-principles calculation, and (ii) electronic structures of several real materials, such as permanent magnet.
Keywords
computational physics, machine learning, electron correlation, magnetism
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
The contents will be explained through lectures.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | First-principles calculation | Understand density functional theory. |
| Class 2 | Band structure of materials | Understand electronic structures of several materials. |
| Class 3 | Electronic states of correlated materials | Derivation of first-principles low-energy model and its applications |
| Class 4 | Permanent magnet | Understand rare-earth magnets based on electronic states. |
| Class 5 | Computational materials design | Crystal structure prediction, materials exploration by high-throughput calculation |
| Class 6 | Machine learning | Understand basic techniques of AI (regression, classification, clustering). |
| Class 7 | Materials informatics | Data-driven materials research |
Textbook(s)
None
Reference books, course materials, etc.
Course materials are provided during class.
Assessment criteria and methods
Students’ course scores are based on assignments.
Related courses
- PHY.C340 ： Basic Solid State Physics
- PHY.C341 ： Condensed Matter Physics I
- PHY.C342 ： Condensed Matter Physics II
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Knowledge of Basic solid state physics.
