Computational Materials Theory Group35
Research Interests
Computation is assuming a progressively crucial role in the design of functional materials with practical applications. Employing quantum mechanics and atomic simulations enables us to comprehend and manipulate matter, energy, and information at the fundamental scales of materials physics. Integration with machine learning further opens avenues for innovative approaches in materials science, offering potential breakthroughs in first-principles materials theory.
- Materials by design
- Machine learning
- Simple complexity
Advisor Professor : Kang, Joongoo
Computational Materials Theory Group Homepage
Computation is assuming a progressively crucial role in the design of functional materials with practical applications. Employing quantum mechanics and atomic simulations enables us to comprehend and manipulate matter, energy, and information at the fundamental scales of materials physics. Integration with machine learning further opens avenues for innovative approaches in materials science, offering potential breakthroughs in first-principles materials theory.
- Materials by design
- Machine learning
- Simple complexity
Advisor Professor : Kang, Joongoo
Computational Materials Theory Group Homepage
Subject
- metal-organic frameworks 2
- MODEL 2
- NANOCRYSTALS 2
- Nickel 2
- Partial Dislocations 2
- Recombination Centers 2
- REDUCTION 2
- Repair 2
- SINGLE 2
- STATES 2
Date issued
- 2020 - 2025 17
- 2014 - 2019 16
Co-Author(s)
Related Keyword
Recent Submissions
- 포인트 클라우드 시스템 표현을 위한 디스크립터 생성 방법 및 그 장치
- Topological Machine Learning Unveils Hidden Reaction Pathways in Nanocrystal Synthesis
- Targeted Selenite Adsorption Using Defective Fe-BTC: Effective in Acidic and Alkaline Conditions
- Molecular Surface Doping of Cellulose Nanocrystals: A High-Throughput Computational Study
- Radical-Driven Crystal-Amorphous-Crystal Transition of a Metal-Organic Framework