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

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 106 simulated perovskite solar cells with their performance (VOC,JSC 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)

搜集汇总

背景与挑战

背景概述

该数据集包含超过106个模拟钙钛矿太阳能电池样本，用于基于机器学习识别主导复合过程，数据包括在不同光照强度下的性能参数（VOC、JSC、FF）和理想因子（n），通过开源代码SIMsalabim构建。