2024 Special graduate degree programs Specially Offered Degree Programs for Graduate Students Tokyo Tech Academy for Convergence of Materials and Informatics
Basic Materials Informatics
- Academic unit or major
- Tokyo Tech Academy for Convergence of Materials and Informatics
- Instructor(s)
- Takafumi Ueno / Nobuaki Yasuo / Kazuaki Kuwahata / Gergely Miklos Juhasz / Taro Hitosugi / Yoshitaka Tateyama / Masamichi Shimosaka
- Class Format
- Lecture (Livestream)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 5-6 Mon
- Class
- -
- Course Code
- TCM.A401
- Number of credits
- 100
- Course offered
- 2024
- Offered quarter
- 3Q
- Syllabus updated
- Mar 14, 2025
- Language
- English
Syllabus
Course overview and goals
In this lecture, experts in the fields of materials informatics and materials simulation will outline how to integrate material science and information science and utilize them in research and development, with taking practical examples.
The aim is to acquire basic skills to become "complex human resources" to advance creative material and information research by linking material and information, and thinking from a compound eye viewpoint.
Note) Complex Human Resources: Human resources capable of actively engaging in things concerning materials science, information science, and social services
Course description and aims
By the end of this course, students will be able to:
1) Gain knowledge of trends new methods and ways of thinking across both material and information fields, and to evaluate research.
2) Participate in discussion about research on material and information based on expert knowledge.
3) Draw conclusions from experimental results related to both material and information fields through logical thinking.
Keywords
Materials, Informatics, Interdiscipline
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Topics change every lesson. Lectures will be provided by Zoom.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | (Oct 7 (Mon) Yasuo) Introduction to Materials Informatics: Organic Molecules and Machine Learning | Understand the overview of materials informatics by performing machine learning for small organic molecules as an example. |
| Class 2 | (Oct 17 (Thu) Kuwahata) Introduction to Materials simulation: Ab initio calculations and molecular mechanics methods | Understand the differences between ab initio calculation methods and molecular mechanics methods, and learn how to use various calculation methods to obtain the desired physical quantities. |
| Class 3 | (Oct 21 (Mon) Yasuo) Practical bioinformatics: genome, protein, and drug design | Study about the problems and techniques for informatics targeting biomolecules such as genome and protein. Understand computational drug discovery researches as their application. |
| Class 4 | (Oct 28 (Mon) Juhasz) Practical quantum chemistry calculation: prediction of chemical and electrochemical properties | After a brief introduction on the theory, strength and limitations of different quantum chemical methods, we discuss research-based examples of electrochemical and chemical property prediction. |
| Class 5 | (Nov 11 (Mon) Shimosaka) Introduction to smartphone sensing and its big data analytics | Understand the overview of real-world data collection methods using smartphones, called smartphone sensing. Also, to understand the analysis of large-scale data (big data) obtained from sensed data and its applications. |
| Class 6 | (Nov 18 (Mon) Tateyama) Molecular dynamics : From statistical mechanics to applications to materials science | Study the relationship between MD sampling and statistical mechanics, and the typical applications of MD calculations in materials science and chemical reaction research. |
| Class 7 | (Nov 25 (Mon) Hitosugi) Materials science using AI and robots: from parameter optimization to discovery of scientific principles. | We are now in the era when robots are conducting experiments. Moreover, AI robotic systems are now at the stage of revealing the truth of science. The lecture covers the state-of-the-art in the use of such systems in inorganic, organic, and biotechnology research. |
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)
Not specified.
Reference books, course materials, etc.
Not specified.
Evaluation methods and criteria
Students will be assessed on their understanding by submitting a report selected from among six problems announced in six lessons.
Related courses
- Not specified.
Prerequisites
Not specified.
Other
There are restrictions on the number of students who can take this course, and TAC-MI students and those who have passed the eligibility screening for Graduate Major in Materials and Information Sciences have priority registration. A lottery will be held, if there are many applicants.