doi: 10.1038/s41467-021-22472-x.
Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning
Affiliations
- PMID: 33850155
- PMCID: PMC8044090
- DOI: 10.1038/s41467-021-22472-x
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Discovery of temperature-induced stability reversal in perovskites using high-throughput robotic learning
Nat Commun.
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Abstract
Stability of perovskite-based photovoltaics remains a topic requiring further attention. Cation engineering influences perovskite stability, with the present-day understanding of the impact of cations based on accelerated ageing tests at higher-than-operating temperatures (e.g. 140°C). By coupling high-throughput experimentation with machine learning, we discover a weak correlation between high/low-temperature stability with a stability-reversal behavior. At high ageing temperatures, increasing organic cation (e.g. methylammonium) or decreasing inorganic cation (e.g. cesium) in multi-cation perovskites has detrimental impact on photo/thermal-stability; but below 100°C, the impact is reversed. The underlying mechanism is revealed by calculating the kinetic activation energy in perovskite decomposition. We further identify that incorporating at least 10 mol.% MA and up to 5 mol.% Cs/Rb to maximize the device stability at device-operating temperature (<100°C). We close by demonstrating the methylammonium-containing perovskite solar cells showing negligible efficiency loss compared to its initial efficiency after 1800 hours of working under illumination at 30°C.
Conflict of interest statement
The authors declare no competing interests.
Figures
a Crystal structure of perovskite with multiple cations, including potassium (K+), rubidium (Rb+), caesium (Cs+), methylammonium (MA+), and formamidinium (FA+). b Schematic of the workflow of HTRobot for automatic synthesis and characterization. The red circles in the bottom panel indicate the five different positions tested on each sample. c Detailed workflow chart of the high-throughput operation to evaluate perovskite stability. d Photograph of the HTRobot system, including (1) robot arm with four pipettes; (2) camera and humidity meter; (3) spectrometer to record the absorbance and photoluminescence; (4) 96-well microplates to mix the precursors; (5) hotplate; (6) stock solution of PbI2, FAI, MAI, CsI, etc.; (7) sample stage; (8) pipette tips; (9) waste container; and (10) heat sealer to optionally fuse microplates with aluminum foil. I/II/III show panoramic views of the setup, top view of the film fabrication and solution preparation, respectively.
a The colormap of T80 lifetime for the 64 perovskites aged in climate chambers preset at 85 °C (top) and 140 °C (middle) with 10% RH in the dark, and under 120 mW cm−2 metal-halide light illumination with N2 flow at 60 °C (bottom). b The ranking of feature importance using GBT regression and SHAP assessment, showing the impact of each cation and processing condition in descending order of importance (rank). The purple and orange color indicates low and high values of a given feature, respectively. Note that aging_temp., dep_method, Ost, α−δ indicates aging temperature, deposition method (drop-cast = 1), over-stoichiometric with excess iodide (OSt), the probability of phase transition in humid air (>30%RH), respectively. c The correlation plot of T80 at 85 °C against T80 at 85 °C, 100 °C, and 140 °C. Linear fitting was used to fit all the statistical data to obtain the Pearson correlation coefficients. d The correlation plot of T80 under light illumination against T80 aged at 85 °C, 100 °C, and 140 °C. e
-1000/T plot of No. 49 (MA0.08Rb0.02FA0.9PbI3) and No. 63 (Cs0.15MA0.05FA0.9PbI3). The data are fitted using Eq. (2), indicated by blue and red lines. f
-1000/T plot of MAPbI3 and FAPbI3. g, h
T80 lifetime versus ageing temperature for a series of CsxMAyFA1-x-yPbI3 perovskites, with x + y = 15% (g) and x + y = 20% (h).
a Schematic of the decomposition processes for perovskite with multiple steps, including proton adsorption (1st step), HI desorption (2nd step), MA/FA desorption (3rd step) and subsequent structure reconfiguration to form PbI2. b The kinetic energy barrier of MA/FA molecular splitting. c, d The potential energy curve vs. reaction coordinate for iodide desorption on the intact surface of MAPbI3/FAPbI3 and HI desorption on the surface of MAPbI3/FAPbI3 with an adsorbed proton. e, f The potential energy curve vs. reaction coordinate for MA/FA desorption on the surface of MAPbI3/FAPbI3 with iodide vacancies (e) and on the surfaces of Cs0.125 FA0.875PbI3 (12.5% Cs), MA0.125 FA0.875PbI3 (12.5% MA) with iodide vacancies (f). The orange circles indicate iodide vacancies. The two red curves represent MA desorption, and the three blue curves represent FA desorption.
a Schematic of the solar cell architecture and the corresponding cross-sectional SEM image of the device. b Current density–voltage (J–V) curves for FAPbI3 and CsxMA0.15–xFA0.85PbI3 (x = 0, 5, 10, and 15%) perovskite solar cells with a scanning rate of 20 mV s−1 from −0.1 to 1.2 V. c Statistical PCE of 12 devices for each FAPbI3 and CsxMA0.15–xFA0.85PbI3 (x = 0, 5, 10, and 15%) perovskite solar cell. d Statistic PCE evolution under 140 °C/35%RH conditions in ambient air. The device was aged before depositing the hole transporting layer and Au. e Statistic PCE evolution under 85 °C/85%RH conditions in a climate chamber. f Long-term stability for CsxMA0.15–xFA0.85PbI3 (x = 0, 5, 10, and 15%) perovskite solar cells tested under 100 mW cm−2 white LED illumination. The efficiency was recorded with a scanning rate of 20 mV s−1 from 1.2 to −0.1 V as the reverse scan. The MPP tracking for 10% MA is based on the stabilized efficiency biased at the maximum power point in reverse-scan mode. The device temperature is controlled at ~30 °C by a cooling stage.
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