[10a-Z09-1~9] 23.1 Joint Session N "Informatics"

[10a-Z09-8] Inverse design of PbS quantum dot / Perovskite intermediate band solar cell by AI based prediction and optimization method

〇(M2)Kodai Shiba^1,3, Katsuyoshi Sakamoto¹, Koichi Yamaguchi¹, Qing Shen¹, Yoshitaka Okada⁴, Tomah Sogabe^1,2,3,4 (1.Univ. of Electro-Comm, 2.i-PERC, 3.Grid inc., 4.RCAST, Univ. of Tokyo)

Keywords:intermediate band solar cells, quantum dot, machine learning

Recently, solution-based perovskite/PbS quantum dot mid-band solar cells have been demonstrated and have attracted much attention. However, the conversion efficiency of the solution-based intermediate band solar cells is only about 3%, which is much lower than the theoretical conversion efficiency of 47% for non-focused intermediate band solar cells. This study aims to construct an AI prediction optimization method that integrates state-of-the-art machine learning techniques and quantum dot solar cell device simulations that take into account optical interference in order to reverse design for higher efficiency perovskite/PbS quantum dot intermediate band solar cells.