Perovskite Solar Cells Ageing Dataset

This dataset contains cleaned 2,245 ageing test traces (time vs. MPPT PCE/ maximum power point tracking power conversion efficiency) for perovskite solar cells with various device stacks and architectures in the pickle (.pkl) format. The dataset can be loaded with the following commands on Python. <pre><code class="language-python">import pickle5 as pickle import pandas as pd import numpy as np with open('20230303_mySeriesDrop.pkl', "rb") as fh: mySeriesDrop = pickle.load(fh)</code></pre> The following command can be used to call a specific row (row 0) within the dataset. <pre><code class="language-python">mySeriesDrop[0]</code></pre> The next steps to use the dataset is using scaling/ normalisation (for instance using sklearn.preprocessing.MaxAbsScaler) and smoothing (for instance using Savitzky-Golay filter). The code to run the complete analysis, including self-organising map clustering, can be accessed here: https://doi.org/10.5281/zenodo.8181602.