2024 Special graduate degree programs Specially Offered Degree Programs for Graduate Students Tokyo Tech Academy of Energy and Informatics program
Computational chemistry for energy technologies
- Academic unit or major
- Tokyo Tech Academy of Energy and Informatics program
- Instructor(s)
- Sergei Manzhos
- Class Format
- Exercise (HyFlex)
- Media-enhanced courses
- -
- Day of week/Period
(Classrooms) - 1-2 Mon
- Class
- -
- Course Code
- ENI.I402
- Number of credits
- 010
- Course offered
- 2024
- Offered quarter
- 3Q
- Syllabus updated
- Mar 14, 2025
- Language
- English
Syllabus
Course overview and goals
The course teaches methods and tools of computational materials science that are required for computational modeling of and mechanistic insight into the properties of functional materials used in renewable energy generation and storage technologies such as solar cells, fuel cells, and batteries. The focus is on density functional theory (DFT) based modeling of key phenomena in them such as molecular adsorption, ion transport, vibrational spectra etc. The students will acquire an understanding of the appropriateness of different approximations, will learn to use the DFT method and software to perform simulations. The course includes the following topics:
1) Summary of key properties of and phenomena in functional materials used in technologies such as solar cells, fuel cells, batteries etc. Understanding the importance of modeling of such phenomena for the understanding and design of functional materials.
2) Introduction of the ab initio view of matter and of different methods stemming from it, such as electronic structure and force-field based methods. Understanding what these methods can and cannot do.
3) Introduction of the basics of DFT theory and computational approaches. Introduction of DFT software used for materials modeling. DFT calculations of structures, diffusion barriers, band structures, adsorption properties, optical spectra, and vibrational properties.
4) Gaining mechanistic insight from DFT calculations with examples from solid state ionics and heterogeneous catalysis.
5) Understanding the basics of molecular dynamics on the example of AIMD (ab initio molecular dynamics)
The students will perform simulations on their own computers in a master-class regime.
The course enrolment is limited to 40 students, with priority given to the students belonging to Tokyo Tech Academy of Energy and Informatics.
Course description and aims
Students will understand the role of materials modeling within the fields of materials science and renewable energy generation and storage technologies. They will understand the basics of DFT simulations. They will learn to use DFT software to practically compute key properties of functional materials and to gain mechanistic insight.
Keywords
Density functional theory, functional material, optical properties, vibrational properties, transport properties, renewable energy
Competencies
- Specialist skills
- Intercultural skills
- Communication skills
- Critical thinking skills
- Practical and/or problem-solving skills
Class flow
Each class lasting about 100 min will feature a presentation period (about 1/3 to 1/2 of the class time), an exercise period (about ½ to 2/3 of the class time), and an assessment/feedback period (about 15 min). Most of the lectures will be given as masterclasses (i.e. with students repeating on their computers the procedures performed by the professor on their computer). Exercises will involve materials property calculations using methods and tools introduced in the lectures. Each lecture will have a brief quiz to provide constant feedback to the professor and to the student about the degree of absorption of the material and to reveal any need for review or adjustments.
Course schedule/Objectives
| Course schedule | Objectives | |
|---|---|---|
| Class 1 | Summary of key properties of and phenomena in functional materials used in technologies such as solar cells, fuel cells, batteries etc. Understanding the importance of modeling of such phenomena for the understanding and design of functional materials. Introduction of the ab initio view of matter and how it gives rise to particular modeling methods such as ab initio or force fields. Explanation of what these methods can and cannot do. Exercise 1: Introduction of DFT software and related GUI software used in materials modeling . | Students will learn about the connection between several key technologies (such as fuel cells, solar cells, batteries) and properties of materials. They will learn the limits of experiment-based understanding and the role of and need for computation of properties such as molecular adsorption, optical absorption, band edges, vibrations, charge and ion transport etc. They will learn what properties can be modelled at the force field level and when electronic structure level of insight is required. |
| Class 2 | Introduction of the basics of DFT theory and key types of computational approaches to DFT. Basics of DFT calculations in solid state / periodic systems. Brillouin zone sampling and bandstructure; plane wave calculations and pseudopotentials, and other computational approaches and settings specific to solid state Exercise 2: Students use Materials Studio for generation of model systems and initiation of DFT calculations. | Students learn the basics of DFT theory and key approximations, and how to choose reasonable calculations parameters including functionals and basis sets. Students learn to prepare models for DFT calculations, such as generation of simulation cells, interfaces etc. |
| Class 3 | Calculations of structures with DFT: molecules, periodic solids, surfaces, and molecule-surface systems. Exercise 3: Students perform DFT simulations of structures, energies, and interaction energies and analyze the results. | Students learn the workflow of simulations for different applications, choices of parameters such as appropriate model sizing, Brillouin zone sampling, calculation of adsorption energies etc. |
| Class 4 | Elements of AIMD (ab initio molecular dynamics). Use of DFT calculations to gain mechanistic insight into phenomena on the example of ion-host material interaction. Exercise 4: using the calculations results from the previous exercise, students will use PDOS (partial density of states) and charge analysis to analyze the mechanisms of an ion interaction with an electrode material. The students will learn to set up AIMD calculations. | Students will learn how to use densities of state and charge analyses to understand the mechanism of ion-host interaction in materials used in batteries and fuel cells. Students will learn to relate the computed quantities to device performance. Students will also learn the basics of AIMD. |
| Class 5 | Use of DFT calculations to gain mechanistic insight into phenomena on the example of catalytic materials. Exercise 5: using the calculations results from exercise 3, students will use PDOS (partial density of states) and charge analysis to analyze the mechanism of molecular bond weakening by a catalytic surface. | Students will learn how to use densities of state and charge analyses to understand the mechanisms of catalytic action of a surface, and how to relate such mechanistic insight to device performance. |
| Class 6 | Calculations of vibrational and optical properties. Elements of theory behind such calculations. Exercise 6: Students perform calculations of vibrational and optical spectra with DFT and analyze the results. | Students will learn how vibrational and optical spectra arise and basics of theory to model them. They will acquire hands-on experience in computing them. |
| Class 7 | Summary and finishing computer exercises | Students will overview how various properties and computational approaches relate to each other. |
Study advice (preparation and review)
For 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 books and other course materials.
Textbook(s)
Chapters from:
Fundamentals of Materials for Energy and Environmental Sustainability, Eds. D. S. Ginley, D. Cahen, Cambridge University Press, 2011, ISBN:9781107000230
Density Functional Theory: A Practical Introduction, David S. Sholl, Janice A. Steckel, Wiley 2023, ISBN: 978-1-119-84086-2
Articles from research literature.
Reference books, course materials, etc.
To be distributed on a case-by-case basis by T2SCHOLA.
Evaluation methods and criteria
Students' understanding will be assessed by quizzed and computing exercises.
Related courses
- ESI.B431 ： Recent technologies of fuel cells, solar cells butteries and energy system
- ENI.I401 ： Big Data in Energy: a practical introduction
Prerequisites
N/A