2020 Basic Materials Informatics

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Academic unit or major
Tokyo Tech Academy for Convergence of Materials and Informatics
Ueno Takafumi  Hitosugi Taro  Sekijima Masakazu  Aoki Takayuki  Matsushita Yuichiro  Yasuo Nobuaki  Kawauchi Susumu  Tateyama Yoshitaka 
Course component(s)
Lecture    (ZOOM)
Day/Period(Room No.)
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Academic year
Offered quarter
Syllabus updated
Lecture notes updated
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Course description and aims

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

Student learning outcomes

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


Materials, Informatics, Interdiscipline

Competencies that will be developed

Specialist skills Intercultural skills Communication skills Critical thinking skills Practical and/or problem-solving skills

Class flow

Topics change every lesson. Topics change every lesson. Lectures will be provided by Zoom.

Course schedule/Required learning

  Course schedule Required learning
Class 1 Introduction to Materials Informatics: COVID-19 drug discovery and compound generation model Understand the overview of materials informatics, and explain the usefulness of materials informatics for coronavirus drug discovery and compound generation model.
Class 2 Practical quantum chemistry calculation: examples of reaction path search and physical property prediction Study what level of current quantum chemical calculation is, and how quantum chemical calculation is useful for research based on examples of reaction path search and physical property prediction.
Class 3 Solid state physics calculation: Design of electronics devices and materials screening based on the DFT calculations Study how ab initio calculations with the DFT calculations are helpful in designing electronic devices (inorganic materials). Study the materials screening technique based on the DFT and its application to a novel electronic device.
Class 4 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 5 Molecular dynamics sampling: Statistical mechanics of materials at finite temperature Study the relationship between MD sampling and statistical mechanics and the typical applications of MD calculations in materials science and chemical reaction research.
Class 6 GPU-based supercomputing: large-scale computing and application to fluid-particle simulations More than 300 systems equipped with GPU have been ranked in the latest Top500 supercomputer list. Understand the method to use GPU for large-scale computing and how to apply to fluid-particle simulations as real-world problems.
Class 7 Materials science using AI and robots: from parameter optimization to discovery of scientific principles. We are now in an era where robots are conducting experiments. Moreover, AI robotic systems are now at the stage of revealing the truth of science. Understand the state-of-the-art in the inorganic, organic, and biotechnology research fields.

Out-of-Class Study Time (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.


Not specified.

Reference books, course materials, etc.

Not specified.

Assessment criteria and methods

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 (i.e., required knowledge, skills, courses, etc.)

Not specified.


There are restrictions on the number of students who can take this course, and TAC-MI students have priority registration. A lottery will be held, if there are many applicants.

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