In recent years, there has been remarkable progress in the performance of metal halide perovskite solar cells. Studies have shown significant interest in lead-free perovskite solar cells (PSCs) due to concerns about t...In recent years, there has been remarkable progress in the performance of metal halide perovskite solar cells. Studies have shown significant interest in lead-free perovskite solar cells (PSCs) due to concerns about the toxicity of lead in lead halide perovskites. CH3NH3SnI3 emerges as a viable alternative to CH3NH3PbX3. In this work, we studied the effect of various parameters on the performance of lead-free perovskite solar cells using simulation with the SCAPS 1D software. The cell structure consists of α-Fe2O3/CH3NH3SnI3/PEDOT: PSS. We analyzed parameters such as thickness, doping, and layer concentration. The study revealed that, without considering other optimized parameters, the efficiency of the cell increased from 22% to 35% when the perovskite thickness varied from 100 to 1000 nm. After optimization, solar cell efficiency reaches up to 42%. The optimization parameters are such that, for example, for perovskite: the layer thickness is 700 nm, the doping concentration is 1020 and the defect density is 1013 cm−3, and for hematite: the thickness is 5 nm, the doping concentration is 1022 and the defect concentration is 1011 cm−3. These results are encouraging because they highlight the good agreement between perovskite and hematite when used as the active and electron transport layers, respectively. Now, it is still necessary to produce real, viable photovoltaic solar cells with the proposed material layer parameters.展开更多
In this study, organic solar cells (OSCs) with an active layer, a blend of polymer of non-fullerene (NFA) Y6 as an acceptor, and donor PBDB-T-2F as donor were simulated through the one-dimensional solar capacitance si...In this study, organic solar cells (OSCs) with an active layer, a blend of polymer of non-fullerene (NFA) Y6 as an acceptor, and donor PBDB-T-2F as donor were simulated through the one-dimensional solar capacitance simulator (SCAPS-1D) software to examine the performance of this type of organic polymer thin-film solar cell by varying the thickness of the active layer. PFN-Br interfacial layer entrenched in OPV devices gives overall enhanced open-circuit voltage, short-circuit current density and fill factor thus improving device performance. PEDOT: PSS is an electro-conductive polymer solution that has been extensively utilized in solar cell devices as a hole transport layer (HTL) due to its strong hole affinity, good thermal and mechanical stability, high work function, and high transparency in the visible range. The structure of the organic solar cell is ITO/PEDOT: PSS/BTP-4F: PBDB-T-2F/PFN-Br/Ag. Firstly, the active layer thickness was optimized to 100 nm;after that, the active-layer thickness was varied up to 900 nm. The results of these simulations demonstrated that the active layer thickness improves efficiency significantly up to 500 nm, then it decreased with increasing the thickness of the active layer from 600 nm, also notice that the short circuit current and the fill factor decrease with increasing the active layer from 600 nm, while the open voltage circuit increased with increasing the thickness of the active layer. The optimum thickness is 500 nm.展开更多
The photovoltaic performance (efficiency η) of an ITO/CdS/CdTe structure cell is studied in this article according to its electrical properties. The study is carried out by simulation with SCAPS (Solar Cell Capacitan...The photovoltaic performance (efficiency η) of an ITO/CdS/CdTe structure cell is studied in this article according to its electrical properties. The study is carried out by simulation with SCAPS (Solar Cell Capacitance Simulator) whose mathematical model is based on solving the equations of Poisson and continuity of electrons and holes. An electrical conversion efficiency of 23.58% is obtained by optimizing the mobility of the electrons (100 cm2/Vs), that of the holes (25 cm2/Vs), the density of electrons (1015 cm-3), the density of the effective states in the conduction band (7.9 × 1017 cm-3) and the electronic affinity (3.85 eV) of the CdTe absorbent layer.展开更多
The commercialization of perovskite solar cells(PSCs)is hindered by the instability of organic components and the resource-intensive nature of experimental optimization.Machine learning(ML)is revolutionizing the disco...The commercialization of perovskite solar cells(PSCs)is hindered by the instability of organic components and the resource-intensive nature of experimental optimization.Machine learning(ML)is revolutionizing the discovery and optimization of photovoltaic devices by reducing reliance on conventional trial-and-error approaches.This study aims to optimize the performance of CsPbI₃-based all-inorganic PSCs using a combined SCAPS-1D and machine learning(ML)approach.We generated 56,390 unique device configurations via SCAPS-1D simulations,varying layer thicknesses and defect densities.Five ML models were trained,with XGBoost achieving the highest accuracy(R^(2)=0.999).Feature importance was analyzed using SHAP.Optimization increased the PCE from 15.15%to 19.16%,with the perovskite layer thickness(2μm)and defect density(<10^(15)cm^(-3))identified as critical parameters.This study highlights the potential of ML-driven optimization in perovskite solar cells,offering a systematic and data-driven approach to enhancing device efficiency and accelerating the development of next-generation photovoltaics.展开更多
文摘In recent years, there has been remarkable progress in the performance of metal halide perovskite solar cells. Studies have shown significant interest in lead-free perovskite solar cells (PSCs) due to concerns about the toxicity of lead in lead halide perovskites. CH3NH3SnI3 emerges as a viable alternative to CH3NH3PbX3. In this work, we studied the effect of various parameters on the performance of lead-free perovskite solar cells using simulation with the SCAPS 1D software. The cell structure consists of α-Fe2O3/CH3NH3SnI3/PEDOT: PSS. We analyzed parameters such as thickness, doping, and layer concentration. The study revealed that, without considering other optimized parameters, the efficiency of the cell increased from 22% to 35% when the perovskite thickness varied from 100 to 1000 nm. After optimization, solar cell efficiency reaches up to 42%. The optimization parameters are such that, for example, for perovskite: the layer thickness is 700 nm, the doping concentration is 1020 and the defect density is 1013 cm−3, and for hematite: the thickness is 5 nm, the doping concentration is 1022 and the defect concentration is 1011 cm−3. These results are encouraging because they highlight the good agreement between perovskite and hematite when used as the active and electron transport layers, respectively. Now, it is still necessary to produce real, viable photovoltaic solar cells with the proposed material layer parameters.
文摘In this study, organic solar cells (OSCs) with an active layer, a blend of polymer of non-fullerene (NFA) Y6 as an acceptor, and donor PBDB-T-2F as donor were simulated through the one-dimensional solar capacitance simulator (SCAPS-1D) software to examine the performance of this type of organic polymer thin-film solar cell by varying the thickness of the active layer. PFN-Br interfacial layer entrenched in OPV devices gives overall enhanced open-circuit voltage, short-circuit current density and fill factor thus improving device performance. PEDOT: PSS is an electro-conductive polymer solution that has been extensively utilized in solar cell devices as a hole transport layer (HTL) due to its strong hole affinity, good thermal and mechanical stability, high work function, and high transparency in the visible range. The structure of the organic solar cell is ITO/PEDOT: PSS/BTP-4F: PBDB-T-2F/PFN-Br/Ag. Firstly, the active layer thickness was optimized to 100 nm;after that, the active-layer thickness was varied up to 900 nm. The results of these simulations demonstrated that the active layer thickness improves efficiency significantly up to 500 nm, then it decreased with increasing the thickness of the active layer from 600 nm, also notice that the short circuit current and the fill factor decrease with increasing the active layer from 600 nm, while the open voltage circuit increased with increasing the thickness of the active layer. The optimum thickness is 500 nm.
文摘The photovoltaic performance (efficiency η) of an ITO/CdS/CdTe structure cell is studied in this article according to its electrical properties. The study is carried out by simulation with SCAPS (Solar Cell Capacitance Simulator) whose mathematical model is based on solving the equations of Poisson and continuity of electrons and holes. An electrical conversion efficiency of 23.58% is obtained by optimizing the mobility of the electrons (100 cm2/Vs), that of the holes (25 cm2/Vs), the density of electrons (1015 cm-3), the density of the effective states in the conduction band (7.9 × 1017 cm-3) and the electronic affinity (3.85 eV) of the CdTe absorbent layer.
基金supported by the EU Horizon2020 Project Marketplace,No.760173.
文摘The commercialization of perovskite solar cells(PSCs)is hindered by the instability of organic components and the resource-intensive nature of experimental optimization.Machine learning(ML)is revolutionizing the discovery and optimization of photovoltaic devices by reducing reliance on conventional trial-and-error approaches.This study aims to optimize the performance of CsPbI₃-based all-inorganic PSCs using a combined SCAPS-1D and machine learning(ML)approach.We generated 56,390 unique device configurations via SCAPS-1D simulations,varying layer thicknesses and defect densities.Five ML models were trained,with XGBoost achieving the highest accuracy(R^(2)=0.999).Feature importance was analyzed using SHAP.Optimization increased the PCE from 15.15%to 19.16%,with the perovskite layer thickness(2μm)and defect density(<10^(15)cm^(-3))identified as critical parameters.This study highlights the potential of ML-driven optimization in perovskite solar cells,offering a systematic and data-driven approach to enhancing device efficiency and accelerating the development of next-generation photovoltaics.
