| Academic Year |
2026Year |
School/Graduate School |
Graduate School of Advanced Science and Engineering (Master's Course) Division of Advanced Science and Engineering Applied Chemistry Program |
| Lecture Code |
WSE21901 |
Subject Classification |
Specialized Education |
| Subject Name |
計算化学特論 |
Subject Name
（Katakana） |
ケイサンカガクトクロン |
Subject Name in
English |
Advanced Computational Chemistry |
| Instructor |
KANEMATSU YUSUKE |
Instructor
(Katakana) |
カネマツ ユウスケ |
| Campus |
Higashi-Hiroshima |
Semester/Term |
1st-Year, Second Semester, 4Term |
| Days, Periods, and Classrooms |
(4T) Tues3-4,Fri3-4 |
| Lesson Style |
Lecture |
Lesson Style
(More Details) |
Face-to-face |
| |
| Credits |
2.0 |
Class Hours/Week |
4 |
Language of Instruction |
J
:
Japanese |
| Course Level |
6
:
Graduate Advanced
|
| Course Area（Area） |
25
:
Science and Technology |
| Course Area（Discipline） |
08
:
Chemical Engineering |
| Eligible Students |
|
| Keywords |
Molecular orbital theory, density functional theory, materials informatics |
| Special Subject for Teacher Education |
|
Special Subject |
|
Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students) | |
|---|
Class Objectives
/Class Outline |
After briefing the theoretical background of computational methods used in chemistry, practical knowledge about computational chemistry will be provided through hands-on exercises using quantum chemistry calculation programs and various Python modules.
Students will also learn what information to extract from articles to reproduce previous studies. |
| Class Schedule |
lesson1 Guidance
lesson2 Overview of computational chemistry
lesson3 Basic mathematics for computational chemistry
lesson4 Basis sets and self-consistent field
lesson5 Approximations and models for quantum chemistry
lesson6 Electronic density analysis
lesson7 Calculation of molecular spectra
lesson8 Molecular motion on potential energy surface
lesson9 Practice on quantum chemical calculations I
lesson10 Practice on quantum chemical calculations II
lesson11 Basic Python programming for chemical analysis
lesson12 Analysis of spectra
lesson13 Application of machine learning
lesson14 Replication of previous computational studies
lesson15 Report guidance |
Text/Reference
Books,etc. |
Materials will be provided on Moodle.
References:
- Physical Chemistry: A Molecular Approach
- Atkins' Physical Chemistry
- Introduction to Computational Chemistry
- The Elements of Statistical Learning |
PC or AV used in
Class,etc. |
Handouts, Other (see [More Details]), moodle |
| (More Details) |
Gaussian 16 and Google Colab will be used. |
| Learning techniques to be incorporated |
Post-class Report |
Suggestions on
Preparation and
Review |
Review and preview based on the materials on Moodle. |
| Requirements |
|
| Grading Method |
Exercise, Quiz, and report. |
| Practical Experience |
|
| Summary of Practical Experience and Class Contents based on it |
|
| Message |
Solid-state electronic calculations and molecular dynamics calculations will not be covered in the exercises. |
| Other |
|
Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching. |