Lead halide perovskites have shown great potential for photovoltaic applications during the last decade. However, the stability of perovskite solar cells still restricts commercialization, and lack of properly implemented unified stability testing and disseminating standards makes it difficult to compare historical stability data for evaluating promising routes towards better device stability. Here, we propose a single indicator to describe device stability that normalizes the stability results with respect to different environmental stress conditions which enables a direct comparison of different stability results. Based on this indicator and an open dataset of heterogeneous stability data of over 7000 devices, we have conducted a statistical analysis to assess the effect of different stability improvement strategies. This provides important insights for achieving more stable perovskite solar cells and we also provide suggestions for future directions in the perovskite solar cell field based on big data utilization.
Our idea of designing the indicator comes from the accelerated degradation tests of organic photovoltaic cells and perovskite solar cells, where degradation tests of hundreds of hours under harsh conditions (generally high temperature or concentrated light) are used to predict tens of years of the device lifetime. Acceleration factors, which are the lifetime conversion factors when switching from testing conditions to operating conditions, are used to calculate the predicted device lifetime. We choose TS80 (i.e., the time for power conversion efficiency to decay to 80% of the stabilized efficiency at the end of the burn-in region) as the unnormalized lifetime value and multiply TS80 by the acceleration factors of three main environmental stresses, temperature, humidity, and light intensity. The single indicator TS80m is then given by,
TS80m=TS80*Atemperature*Ahumidity*Alight
Figure 1. Diagrams of perovskite solar cell stability tests. a General device architecture of a perovskite solar cell. b The distribution of stability protocols used for stability data in the Perovskite Database. c Two possible efficiency decay curves of perovskite solar cells illustrating different types of burn-in behaviors followed by a slower exponential decay. (PCE stands for photoelectric conversion efficiency. T80 is the time for PCE to decay to 80% of the initial efficiency. TS80 is the time for PCE to decay to 80% of the stabilized efficiency (marked as 100%(s)).
With TS80m values of all stability results in the database calculated, we tried to explore what strategies and parameters have resulted in improvements in device stability. As an example, the relationship between device stability and perovskite compositions is shown in Figure 2. The distribution of total device numbers and the highest TS80m values with respect to the tolerance factor and the publication date are visualized as heat maps in Figure 2a and b, with which we divided the devices into three tolerance factor regions representing different perovskite composition types. The kernel density estimation (Figure 2c) and the relative stability levels (Figure 2d) calculated with the hypothesis test method are used to assess the influence of tolerance factors on stability. Besides, the device stability depending on the functional layers and device structures is also discussed.
Figure 2. The relationship between device stability and tolerance factors. a A heat map of the total numbers of devices with reported stability data with respect to the tolerance factor and the publication date. b A corresponding heat map of the highest reported TS80m values. c The kernel density estimation of the log(TS80m) values for different tolerance factor regions (large, i.e., sample with tolerance factor α > 0.95; medium, i.e., sample with 0.85 < α < 0.95; small, i.e., sample with α < 0.85.) of three-dimensional perovskite devices without encapsulation. d A bar chart of the TA/TB ratios (representing relative stability level) for the three different tolerance factor regions, where the ratio of the medium tolerance factors is set to 1.
To know more about the work, please refer to the paper “Big Data Driven Perovskite Solar Cell Stability Analysis” published in Nature Communications following the link:
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