2021 Basic Materials Informatics

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Academic unit or major
Tokyo Tech Academy for Convergence of Materials and Informatics
Instructor(s)
Ueno Takafumi  Matsushita Yuichiro  Yasuo Nobuaki  Kawauchi Susumu  Hitosugi Taro  Sekijima Masakazu  Tateyama Yoshitaka 
Course component(s)
Lecture    (ZOOM)
Day/Period(Room No.)
Mon5-6()  
Group
-
Course number
TCM.A401
Credits
1
Academic year
2021
Offered quarter
3Q
Syllabus updated
2021/8/2
Lecture notes updated
-
Language used
English
Access Index

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.

Keywords

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. Lectures will be provided by Zoom.

Course schedule/Required learning

  Course schedule Required learning
Class 1 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 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 3 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 4 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 5 Materials simulation: Significance of materials simulation and its perspective Understand the significance of learning materials simulation and how materials simulation is useful for device development and design showing some examples. Also understand the future perspectives of materials simulation.
Class 6 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 7 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.

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.

Textbook(s)

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.

Other

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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