AI Article Synopsis
- Long-term stability poses a significant challenge for commercializing perovskite solar cells, made worse by a lack of consistent outdoor testing data.
- This study involved two years of outdoor testing on perovskite mini-modules, analyzing their performance changes throughout each day, including both degradation during the day and recovery overnight.
- Using the XGBoost regression model, the researchers successfully predicted the power output of the mini-modules, achieving a low error rate, which shows promise for estimating the lifespan of perovskite devices based on environmental factors.
Article Abstract
Long-term stability is the primary challenge for the commercialization of perovskite photovoltaics, exacerbated by limited outdoor data and unclear correlations between indoor and outdoor tests. In this study, we report on the outdoor stability testing of perovskite mini-modules conducted over a two-year period. We conducted a detailed analysis of the changes in performance across the day, quantifying both the diurnal degradation and the overnight recovery. Additionally, we employed the XGBoost regression model to forecast the power output. Our statistical analysis of extensive aging data showed that all perovskite configurations tested exhibited diurnal degradation and recovery, maintaining a linear relationship between these phases across all environmental conditions. Our predictive model, focusing on essential environmental parameters, accurately forecasted the power output of mini-modules with a 6.76% nRMSE, indicating its potential to predict the lifetime of perovskite-based devices.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11605806 | PMC |
| http://dx.doi.org/10.1021/acsenergylett.4c01943 | DOI Listing |
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