Dataset for: Identification of the Dominant Recombination Process for Perovskite Solar Cells Based on Machine Learning

Published: 25 November 2020| Version 2 | DOI: 10.17632/xbzw29tjz4.2
Contributor:
Vincent Le Corre

Description

Code and data used in the publication "Identification of the Dominant Recombination Process for Perovskite Solar Cells Based on Machine Learning" The dataset saved in the .csv files "balanced_dataset.csv" consist of over 10<sup>6</sup> simulated perovskite solar cells with their performance (V<sub>OC</sub>,J<sub>SC</sub> and FF) at (0.1,0.18,032,0.56,1) sun illuminations as well as the ideality factor (n) . This dataset was built using drift-diffusion open-source code SIMsalabim. (https://github.com/kostergroup/SIMsalabim)

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Institutions

Rijksuniversiteit Groningen

Categories

Solar Cell, Machine Learning, Perovskite Solar Cell

Licence