The power conversion efficiency of lead halide perovskite solar cells has been elevated to 25.2%. However, the toxicity of lead and the complex fabrication process of those cells considerably hinder the commercial application of such solar cells. Therefore, lead-free solar cells with comparable power conversion efficiency with a much lower environmental impact have recently attracted enormous attention in both academia and industry. This paper presents a theoretical study to assess the energy conversion capacity of lead-free perovskite solar cells with MASnI₃ perovskite as its absorber layer using solar cell capacitance simulator (SCAPS). In particular, the effects of materials of the perovskite solar cells’ electron transport layers (ETLs) and hole transport layers (HTLs) on their energy conversion performance are elaborated. Our results show that Cd_0.5Zn_0.5S and MASnBr₃ are the most suitable materials for ETL and HTL, respectively. It is also found from that the solar cell performance can be further enhanced through optimizing the thickness and defect density of its absorber layer. Moreover, the effects of defect densities in interface layers are investigated. In addition, the effects of ETL and HTL doping densities as well as influences of the back-contact work function and operating temperature of the tin-based perovskite solar cells are discussed. Finally, a glass substrate/FTO/Cd_0.5Zn_0.5S (ETL)/MASnI₃/MASnBr₃ (HTL)/back-contact solar cell with a power conversion efficiency of 23.86% is recommended for further optimization.

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.

Deep learning has proven itself to be able to reduce the scanning time of Magnetic Resonance Imaging (MRI) and to improve the image reconstruction quality since it was introduced into Compressed Sensing MRI (CS-MRI). However, the requirement of using large, high-quality, and patient-based datasets for network training procedures is always a challenge in clinical applications. In this paper, we propose a novel deep learning based compressed sensing MR image reconstruction method that does not require any pre-training procedure or training dataset, thereby largely reducing clinician dependence on patient-based datasets. The proposed method is based on the Deep Image Prior (DIP) framework and uses a high-resolution reference MR image as the input of the convolutional neural network in order to induce the structural prior in the learning procedure. This reference-driven strategy improves the efficiency and effect of network learning. We then add the k-space data correction step to enforce the consistency of the k-space data with the measurements, which further improve the image reconstruction accuracy. Experiments on in vivo MR datasets showed that the proposed method can achieve more accurate reconstruction results from undersampled k-space data.

Benefiting from the advantages of a high absorption coefficient, a long charge diffusion length, excellent carrier mobility, and a tunable bandgap, three-dimensional (3D) metal halide perovskites exhibit great potential for application in solar cells. However, 3D perovskite solar cells (PSCs) often suffer from poor long-term stability against moisture, heat, and light. To address this issue, reducing the dimension of perovskite and forming two-dimensional (2D) perovskites can be effective in slowing down the oxidation of the perovskite film and significantly improving device stability. In this study, 2D PSCs were designed with glass/FTO/TiO₂/Dion–Jacobson (DJ) perovskite/NiOx/Au structures, based on the solar cell simulation software SCAPS. The absorption layers employed in the study included PeDAMA₂Pb₃I₁₀, PeDAMA₃Pb₄I₁₃, PeDAMA₄Pb₅I₁₆, and PeDAMA₅Pb₆I₁₉. The influence of the conduction band offset (CBO) variation in the range of −0.5 to 0.5 eV on cell performance was explored through a numerical simulation. The simulation results indicate that the open-circuit voltage and fill factor continue to increase, whereas the short-circuit current density remains almost unchanged when the CBO increases from −0.5 eV to 0 eV. The devices exhibit better performance when the value of the CBO is positive and within a small range. For DJ PSCs, controlling the CBO within 0.1–0.4 eV is conducive to better cell performance.

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.

锡基钙钛矿太阳能电池可避免铅元素对环境带来的污染, 近年来已成为光伏领域的研究热点. 本文以SCAPS-1D太阳能电池数值模拟软件为平台, 对不同电子传输层和不同空穴传输层的锡基钙钛矿太阳能电池器件的性能进行数值仿真对比, 从理论上分析不同载流子传输层的锡基钙钛矿太阳能电池的性能差异. 结果显示, 载流子传输层与钙钛矿层的能带对齐对电池性能至关重要. 电子传输层具有更高的导带或电子准费米能级以及空穴传输层具有更低的价带或空穴准费米能级时, 对电池输出更大的开路电压有促进作用. 另外, 当电子传输层的导带高于钙钛矿层导带或钙钛矿层的价带高于空穴传输层的价带时, 钙钛矿层与载流子传输层界面形成spike势垒, 界面复合机制相对较弱, 促使电池获得更佳的性能. 当Cd_0.5Zn_0.5S和MASnBr₃分别作为电子传输层和空穴传输层时, 与其他材料相比, 获得了更优的输出特性: 开路电压V_oc = 0.94 V, 短路电流密度J_sc = 30.35 mA/cm², 填充因子FF = 76.65%, 功率转换效率PCE = 21.55%, 可认为Cd_0.5Zn_0.5S和MASnBr₃是设计锡基钙钛矿太阳能电池结构合适的载流子传输层材料. 这些模拟结果有助于实验上设计并制备高性能的锡基钙钛矿太阳能电池.