Highly efficient flexible perovskite solar cells with vacuum-assisted low-temperature annealed SnO2 electron transport layer

The demand for lightweight, flexible, and high-performance portable power sources urgently requires high-efficiency and stable flexible solar cells. In the case of perovskite solar cells(PSCs), most of the common electron transport layer(ETL) needs to be annealed for improving the optoelectronic properties,while conventional flexible substrates could barely stand the high temperature. Herein, a vacuumassisted annealing SnO_(2) ETL at low temperature(100℃) is utilized in flexible PSCs and achieved high efficiency of 20.14%. Meanwhile, the open-circuit voltage(V_(oc)) increases from 1.07 V to 1.14 V. The flexible PSCs also show robust bending stability with 86.8% of the initial efficiency is retained after 1000 bending cycles at a bending radius of 5 mm. X-ray photoelectron spectroscopy(XPS), atomic force microscopy(AFM), and contact angle measurements show that the density of oxygen vacancies, the surface roughness of the SnO_(2) layer, and film hydrophobicity are significantly increased, respectively. These improvements could be due to the oxygen-deficient environment in a vacuum chamber, and the rapid evaporation of solvents. The proposed vacuum-assisted low-temperature annealing method not only improves the efficiency of flexible PSCs but is also compatible and promising in the large-scale commercialization of flexible PSCs.

Data-driven design of high-performance MASnxPb1-xI3 perovskite materials by machine learning and experimental realization

The photovoltaic performance of perovskite solar cell is determined by multiple interrelated factors,such as perovskite compositions,electronic properties of each transport layer and fabrication parameters,which makes it rather challenging for optimization of device performances and discovery of underlying mechanisms.Here,we propose and realize a novel machine learning approach based on forward-reverse framework to establish the relationship between key parameters and photovoltaic performance in high-profile MASnxPb1-xI3 perovskite materials.The proposed method establishes the asymmetrically bowing relationship between band gap and Sn composition,which is precisely verified by our experiments.Based on the analysis of structural evolution and SHAP library,the rapid-change region and low-bandgap plateau region for small and large Sn composition are explained,respectively.By establishing the models for photovoltaic parameters of working photovoltaic devices,the deviation of short-circuit current and open-circuit voltage with band gap in defective-zone and low-bandgap-plateau regions from Shockley-Queisser theory is captured by our models,and the former is due to the deep-level traps formed by crystallographic distortion and the latter is due to the enhanced susceptibility by increased Sn4+content.The more difficulty for hole extraction than electron is also concluded in the models and the prediction curve of power conversion efficiency is in a good agreement with Shockley-Queisser limit.With the help of search and optimization algorithms,an optimized Sn:Pb composition ratio near 0.6 is finally obtained for high-performance perovskite solar cells,then verified by our experiments.Our constructive method could also be applicable to other material optimization and efficient device development.