Periodic topology on solar cell material analysis
胡全燊教授新加坡南洋理工大學 15:30 – 17:00 鴻經館 M107
Abstract：
With its extraordinary efficiency, cost-effectiveness, and impressive stability, 2D perovskite holds immense promise for transforming photovoltaic technology, particularly in solar cell development. However, the limitations of current material structure representations have significantly impeded AI-based perovskite design and discovery. In this presentation, we introduce a novel framework that integrates topological data analysis (TDA), periodic geometry, and machine learning to effectively represent 2D perovskite structures and predict their bandgaps. This innovative approach enables the detection of the inherent periodic geometry and topology within the material's atomic system, surpassing the traditional focus on chemical interactions among atoms and unit cell periodicity. We employ mathematical tools such as persistent homology, quotient complexes, and density fingerprints to encode this essential periodicity in the topological and geometric aspects of the crystalline structure. Additionally, we provide a comprehensive and concise introduction to these tools in the context of TDA and periodic geometry.