Machine Learning-Enabled Optical Architecture Design of Perovskite Solar Cells-Reference-Cited by-同舟云学术

Machine Learning-Enabled Optical Architecture Design of Perovskite Solar Cells

Published:2024-04-01 Issue:14 Volume:15 Page:3835-3842
ISSN:1948-7185
Container-title:The Journal of Physical Chemistry Letters
language:en
Short-container-title:J. Phys. Chem. Lett.

Author:

Li Zong-Zheng¹²^ORCID,Guo Chaorong²^ORCID,Lv Wenlei²,Huang Peng²^ORCID,Zhang Yongyou¹^ORCID

Affiliation:

1. Beijing Key Laboratory of Nanophotonics & Ultrafine Optoelectronic Systems, School of Physics, Beijing Institute of Technology, Beijing 100081, China

2. Research Institute of Frontier Science, Southwest Jiaotong University, Chengdu 610031, China

Funder

Southwest Jiaotong University

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Sichuan Province Science and Technology Support Program

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jpclett.4c00320

Reference59 articles.

1. Thin-film semiconductor perspective of organometal trihalide perovskite materials for high-efficiency solar cells

2. Electron-Hole Diffusion Lengths Exceeding 1 Micrometer in an Organometal Trihalide Perovskite Absorber

3. High Charge Carrier Mobilities and Lifetimes in Organolead Trihalide Perovskites

4. Unusual defect physics in CH3NH3PbI3 perovskite solar cell absorber

5. Organometal Halide Perovskites as Visible-Light Sensitizers for Photovoltaic Cells

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