Figure1

Recent progress in the data-driven discovery of novel photovoltaic materials

Figure 1. (A) Research trends for various types of solar cells from 2013 to 2022. The percentages in the histograms represent the percentages of each cell in the specific year. We used the search patterns "TS=('solar cell*') AND TS=('perovskite solar cell*')" for PSCs, and "TS=('solar cell*') AND TS=('organic solar cell*')" for OSCs, "TS=('solar cell*') AND TS=('dye-sensitized solar cell*')" for DSSCs and "TS=('solar cell*') AND TS=(Si)" for Si solar cells. (B) Research trends for ML and DL techniques for various solar cells from 2013 to 2022. The numbers in the histograms represent the numbers of references for each cell in the specific year. We added the term "TS=('machine learning' OR 'data mining' OR 'deep learning' OR 'QSPR' OR 'QSAR' OR 'quantitative structure-property relationship' OR 'quantitative structure-activity relationship')" to each search pattern in (A) for the respective solar cell.

Journal of Materials Informatics
ISSN 2770-372X (Online)
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