Theoretical study of the thermal conduction in Cu2S using machine learning-based interatomic potentials
- Title
- Theoretical study of the thermal conduction in Cu2S using machine learning-based interatomic potentials
- Author(s)
- Sanghui Kim
- DGIST Authors
- Kang, Joongoo ; Kim, Sanghui ; Lee, Dooseok
- Advisor
- 강준구
- Co-Advisor(s)
- Doo Seok Lee
- Issued Date
- 2019
- Awarded Date
- 2019-02
- Type
- Thesis
- Table Of Contents
-
Abstract i
List of contents ii
List of figures iii
1. Introduction
1.1 Methods to calculate thermal conductivity 2
1.2 Solid-liquid hybrid phase Cu2S 3
2. Methods
2.1 Atomic simulation using machine learning 6
2.2 Green-Kubo method 12
3. Results and Discussion
3.1 Atomic energy 15
3.2 Thermal conductivity 18
4. Conclusion
- URI
-
http://dgist.dcollection.net/common/orgView/200000171458
http://hdl.handle.net/20.500.11750/10704
- Degree
- MASTER
- Department
- Emerging Materials Science
- Publisher
- DGIST
- Related Researcher
-
-
Kang, Joongoo
- Research Interests Computational Materials Science ＆ Materials Design; Nanomaterials for Energy Applications; Theoretical Condensed Matter Physics
-
- Files in This Item:
-
There are no files associated with this item.
- Appears in Collections:
- Department of Physics and Chemistry Theses Master
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