Course Syllabus

Course Information：

Year-Semester	Course Number	Course Name	Phase	Credits	Hours	Required/Elective	Instructor	Class	Student NO.	Withdraw	Note
Fall Semester Year 2026	364421	Materials for Energy Storage	1	3.0	3	★	Shao-Sian Li	GMMR	10	0

Course Plan：

Instructor	Shao-Sian Li　Office Hours
Email	ssli@ntut.edu.tw
Last Updated	2026-06-26 18:07:44
Course Objective	本課程內容含有: (1)簡介。(2)光電能源物理(3)太陽能電池材料與原理(4)光電化學能源技術(5)儲能材料與元件(6)先進能源材料分析技術(optional) The class includes :1.Course Introduction, 2.solar energy,3. solar cell materials and devices 4. photo-electrochemical reactions for energy harvesting,5. energy storage technology, 6. advanced characterization tools for energy material research
Course Schedule (Week 1-16)	1. introduction 2. fundamental physics of energy materials 3. photovoltaic materials 4. nano materials and nano science for energy application 5. fundamental of electrochemistry for energy application 6. mid term exam. 7. artificial photosynthesis (solar to fuel) 8. energy storage (batteries) 9. hydrogen energy: hydrogen generation and storage 10.advanced characterization tools for energy material research 11. final report
Flexible Learning (Week 17-18)	Category 　 Content 　 Hours 　 Learning Outcomes 　 Assessment Percentage
Evaluation and grading policy	report 40% mid term exam 30% final exam 30%
Materials	All right reserved. Do not reproduce without permission. Foreign-language textbooks:No no
The access to curricular consultation	email: ssli@ntut.edu.tw office: Building of Material, R403
Expanding teaching and resources	● 混成學習 (Blended Learning) 課程結合實體授課與線上學習（同步視訊／非同步活動）。 Combines face-to-face instruction with online learning (including synchronous video sessions or asynchronous activities).
The course corresponds to the SDGs	SDG4：優質教育（Quality Education） SDG7：可負擔的潔淨能源（Affordable and Clean Energy） SDG9：產業創新與基礎設施（Industry, Innovation and Infrastructure） SDG11：永續城市與社區（Sustainable Cities and Communities） SDG13：氣候行動（Climate Action）
Does the course incorporate AI	● 鼓勵學生使用生成式AI工具（Encourage students to use generative AI tools）
Note	the virtual class will be on Teams