Tandem solar cells efficiency prediction and optimization via deep learning

Optical design plays an important role in improving the performance of opto-electronic devices. However, conventional design processes using finite difference time domain (FDTD) or finite element methods are usually time and computing resource consuming, and often result in sub-optimal solutions due...

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Bibliographic Details
Published in:Physical chemistry chemical physics : PCCP 2021-02, Vol.23 (4), p.2991-2998
Main Authors: Yi, Chuqiao, Wu, Yuliang, Gao, Yayu, Du, Qingguo
Format: Article
Language:English
Subjects:
Algorithms
Artificial neural networks
Circuits
Computer simulation
Deep learning
Efficiency
Electronic devices
Energy conversion efficiency
Finite difference time domain method
Finite element method
Machine learning
Neural networks
Optical design
Optimization
Optoelectronic devices
Perovskites
Photovoltaic cells
Short circuit currents
Silicon
Solar cells
Thickness
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Summary:Optical design plays an important role in improving the performance of opto-electronic devices. However, conventional design processes using finite difference time domain (FDTD) or finite element methods are usually time and computing resource consuming, and often result in sub-optimal solutions due to an incomplete search of the parameter state space. In this paper, we propose a deep learning approach to predict and optimize the cell performance of perovskite/crystalline-silicon (c-Si) tandem solar cells. In particular, a deep neural network is established to predict the achievable short-circuit current for tandem solar cells with a given cell structure. After training on a FDTD numerical simulation data set, the proposed deep neural network achieves an accuracy of 98.3% and micro-second grade simulation time, which is an ultra-fast, highly accurate and computing resource-saving solution to investigate the current properties of tandem solar cells. Heuristic algorithms are further adopted to inversely optimize the device structure, where the optimal set of layer thicknesses is obtained to maximize the achievable short-circuit current. According to the calculated projected efficiency, the expected experimental short-circuit current and power conversion efficiency of tandem solar cells with the optimal selection of layer thickness can reach 15.79 mA cm-2 and 23.24%, which is improved by 14.42% and 28.4%, respectively, compared to the benchmark cells.
ISSN:1463-9076
1463-9084
DOI:10.1039/d0cp05882c