Ruizhao Yang

Although perovskite solar cells have achieved excellent photoelectric conversion efficiencies, there are still some shortcomings, such as defects inside and at the interface as well as energy level dislocation, which may lead to non-radiative recombination and reduce stability. Therefore, in this study, a double electron transport layer (ETL) structure of FTO/TiO₂/ZnO/(FAPbI₃)_0.85(MAPbBr₃)_0.15/Spiro-OMeTAD is investigated and compared with single ETL structures of FTO/TiO₂/(FAPbI₃)_0.85(MAPbBr₃)_0.15/Spiro-OMeTAD and FTO/ZnO/(FAPbI₃)_0.85(MAPbBr₃)_0.15/Spiro-OMeTAD using the SCAPS-1D simulation software, with special attention paid to the defect density in the perovskite active layer, defect density at the interface between the ETL and the perovskite active layer, and temperature. Simulation results reveal that the proposed double ETL structure could effectively reduce the energy level dislocation and inhibit the non-radiative recombination. The increases in the defect density in the perovskite active layer, the defect density at the interface between the ETL and the perovskite active layer, and the temperature all facilitate carrier recombination. Compared with the single ETL structure, the double ETL structure has a higher tolerance for defect density and temperature. The simulation outcomes also confirm the possibility of preparing a stable perovskite solar cell.

To broaden the absorption spectrum of cells, enhance the cell stability, and avoid high costs, a novel perovskite solar cell (PSC) with the structure of fluorine-doped tin oxide (FTO)/ZnO/CsPbI₃/FAPbI₃/CuSCN/Au is designed using the solar cell capacitance simulator (SCAPS) software. The simulation results indicate that the CsPbI₃/FAPbI₃ heterojunction PSC has higher quantum efficiency (QE) characteristics than the single-junction CsPbI₃-based PSC, and it outputs a higher short-circuit current density (J_sc) and power conversion efficiency (PCE). In order to optimize the device performance, several critical device parameters, including the thickness and defect density of both the CsPbI₃ and FAPbI₃ layers, the work function of the contact electrodes, and the operating temperature are systematically investigated. Through the optimum analysis, the thicknesses of CsPbI₃ and FAPbI₃ are optimized to be 100 and 700 nm, respectively, so that the cell could absorb photons more sufficiently without an excessively high recombination rate, and the cell achieved the highest PCE. The defect densities of CsPbI₃ and FAPbI₃ are set to 10¹² cm⁻³ to effectively avoid the excessive carrier recombination centering on the cell to increase the carrier lifetime. Additionally, we found that when the work function of the metal back electrode is greater than 4.8 eV and FTO with a work function of 4.4 eV is selected as the front electrode, the excessively high Schottky barrier could be avoided and the collection of photogenerated carriers could be promoted. In addition, the operating temperature is proportional to the carrier recombination rate, and an excessively high temperature could inhibit V_oc. After implementing the optimized parameters, the cell performance of the studied solar cell was improved. Its PCE reaches 28.75%, which is higher than most of existing solar cells. Moreover, the open circuit voltage (V_oc), J_sc, and PCE are increased by 17%, 9.5%, and 25.1%, respectively. The results of this paper provide a methodology and approach for the construction of high-efficiency heterojunction PSCs.

Benzimidazole fungicide residue in food products poses a risk to consumer health. Due to its localized electric-field enhancement and high-quality factor value, the metamaterial sensor is appropriate for applications regarding food safety detection. However, the previous detection method based on the metamaterial sensor only considered the resonance dip shift. It neglected other information contained in the spectrum. In this study, we proposed a method for highly sensitive detection of benzimidazole fungicide using a combination of a metamaterial sensor and mean shift machine learning method. The unit cell of the metamaterial sensor contained a cut wire and two split-ring resonances. Mean shift, an unsupervised machine learning method, was employed to analyze the THz spectrum. The experiment results show that our proposed method could detect carbendazim concentrations as low as 0.5 mg/L. The detection sensitivity was enhanced 200 times compared to that achieved using the metamaterial sensor only. Our present work demonstrates a potential application of combining a metamaterial sensor and mean shift in benzimidazole fungicide residue detection.

In view that a pedometer using zero crossing peak must be worn in the specific parts of human body, a method for realizing pedometer by using the acceleration correlation analysis was proposed. The standard deviation is used to judge whether the pedestrian is walking or not. Besides, the different patterns of personnel's sport station are identified by dynamic threshold. Then, the correlation analysis is used to judge whether the pedestrian is walking or not, because of the periodic characteristics of acceleration when the pedestrian is walking. The test by the proposed method show that, compared with the traditional zero crossing peak method, the method can accurately detect the step frequency under different sport states with an accuracy of 96%~98%.