International Journal of Photoenergy

In order to reduce current leakage and improve electron transfer in solar cells, charge transport layers (CTL), mainly hybrid electron transport layers (h-ETL), are considered as a solution. In this research contribution, computational analysis using SCAPS-1D software is performed to explore the output photovoltaic parameters of a Sb₂S₃-based solar cell with h-ETL. No theoretical works on this configuration have been previously reported. The main objectives of the present work are to propose a h-ETL with good band alignment with the Sb₂S₃ absorber, high transparency, and Cd free; to mitigate the instability and cost issues associated with using Spiro-OMeTAD HTL; and to optimize the solar cell. Thus, we calibrated the - characteristics and electrical parameters of the FTO/(ZnO/TiO₂)/Sb₂S₃/Spiro-OMeTAD/Au solar cell by numerical simulation and compared them with those of the experiment. Subsequently, our simulations show that to replace the TiO₂ ETL used in the experiment and to form the h-ETL with ZnO, IGZO is found to be a good candidate. It has better band alignment with the Sb₂S₃ absorber than TiO₂ ETL, which reduces the trap states at the ETL/Sb₂S₃ interface; it has high transparency due to its wide bandgap; and an intense electric field is generated at the IGZO/Sb₂S₃ interface, which reduces the recombination phenomenon at this interface. MoO₃, MASnBr₃, Cu₂O, CuI, and CuSCN HTL were also tested to replace the Spiro-OMeTAD HTL. Simulation results show that the cell with MoO₃ HTL achieves higher performance due to its high hole mobility and high quantum efficiency in the visible region; it also allows the solar cell to have better thermal stability (%/K) than the cell with Spiro-OMeTAD HTL (%/K). The parameters that could improve the solar cell efficiency () obtained after these substitutions were also optimized. In particular, the parameters of the Sb₂S₃ absorber layer (thickness, defect density, and doping), ETL and HTL layer thicknesses, h-ETL/Sb₂S₃ interface defect density, and series and shunt resistances have been optimized. Finally, by combining high performance and thermal stability, the results show that the thermal stability of the solar cell depends on the back contact type; thus, nickel (Ni) was found to combine high performance and better thermal stability among the back contacts investigated. After these improvements, the efficiency of the Sb₂S₃-based solar cell increased from 5.08% ( mA/cm²,  V, and %) to 15.43% ( mA/cm²,  V, and %). This study proposes an approach to optimize the Sb₂S₃ upper subcell for tandem solar cells.

In this study, a heterojunction (P⁺ a-SiC/i intrinsic/n-Si) solar cell has been examined and characterized using the Analysis of Microelectronics and Photonic Structures (AMPS-1D) simulator. In this heterojunction solar cell, an intrinsic layer is imposed to enhance the efficiency and performance. The optimum efficiency of 36.52% ( V,  mA/cm², and ) has been achieved with this intrinsic layer. It has also been observed the solar cell without intrinsic layer. In this case, the maximum efficiency of 2.378% has been observed which is very poor. The heterojunction solar cell also has been investigated with electron blocking layer (EBL) and defect layer. In this case, the simulation result shows the lower efficiency (34.357%) than the previous. This research paper introduces an optimized model of a heterojunction solar cell enhanced with an intrinsic layer to improve efficiency. The proposed design shows significant promise in its theoretical framework. Looking forward, the design could be realized in laboratory settings and has the potential to be scaled up for broader applications.

Bi₂O₃-BaTiO₃ heterojunction with high photocatalysis efficiency was directly synthesized by rapid thermal processing (RTP). Bi₂O₃ and BaTiO₃ were mixed in ratio and treated by RTP and conventional thermal processing (CTP), respectively. RTP samples have obvious Bi₂O₃ diffraction peaks, while CTP samples show pure BaTiO₃ tetragonal perovskite. More small particles and layered existed in RTP samples. Photodegradation of MB solutions shows that RTP can promote photocatalytic efficiency. Its main lies in the following points: RTP can remove grain boundary defects by strengthening the bond grains; RTP can limit the solution region of the two substances to a certain range to get the best built-in electric field width; and RTP can strengthen the tetragonal BaTiO₃ phase to hasten ion movement. Therefore, RTP can achieve much higher photocatalytic efficiency by improving the build heterojunction. This work provides a direct and efficient route to get improvement and high performance of heterojunction.

An evolutionary algorithm was employed to locate the global minimum of nanoparticles with . More than 61,000 structures were calculated with a semiempirical method and reoptimized using density functional theory. The exciton binding energy of TiO₂ nanoparticles was determined through the fundamental and optical band gap. Frenkel exciton energy scales as , resulting in strongly bound excitons of 0.132–1.2 eV for about 1.4 nm nanoparticles. Although the exciton energy decreases with the system size, these tightly bound Frenkel excitons inhibit the separation of photogenerated charge carriers, making their application in photocatalysis and photovoltaic devices difficult, and imposing a minimum particle size. In contrast, the exciton binding energy of rutile is 4 meV, where the Wannier exciton energy scales as . Moreover, the Wannier excitons in bulk TiO₂ are delocalized according to the Bohr radii: 3.9 nm for anatase and 7.7 nm for rutile.

Inorganic photocatalytic materials exhibiting a highly efficient response to ultraviolet-visible light spectrum have become a subject of widespread global interest. They offer a substantial prospect for generating green energy and mitigating water pollution. Zinc oxide (ZnO), among various semiconductors, proves advantageous for water-splitting applications due to its elevated reactivity, chemical stability, and nontoxic nature. However, its efficacy as a photocatalyst is hindered by limited light absorption capacity and swift charge carrier recombination. To improve charge separation and enhance responsiveness to ultraviolet-visible light photocatalysis, the formation of a heterojunction with another suitable semiconductor is beneficial. Thus, we employed hydrothermal route for the synthesis of the samples, which is a high-pressure method. The formations of ZnO/NiO heterostructures were revealed by scanning electron microscopy, X-ray diffraction analysis, energy-dispersive X-ray spectroscopy, and Fourier transform infrared spectroscopy. The nanocomposites were discovered to have a substantially higher photocatalytic activity for the generation of H₂. The H₂ production rates show that ZnO (i.e., 168.91 molg^-1 h^-1) exhibits good H₂ production rates as compared to NiO (i.e., 135.74 molg^-1 h^-1). The best production rates were observed for ZN-30 (i.e., 247.56 molg^-1 h^-1) which is 1.46 times greater than ZnO and 1.82 times greater than NiO. This enhanced photocatalytic activity for ZN-30 is because of the good electron-hole pair separation due to the formation of depletion layer, suppression of fast charge recombination, and overcoming resistance corrosion.

In recent years, solar photovoltaic (PV) energy, as a clean energy source, has received widespread attention and experienced rapid growth worldwide. However, the rapid growth of PV power deployment also brings important challenges to the maintenance of PV panels, and in order to solve this problem, this paper proposes an innovative algorithm based on PA-YOLO. First, we propose to use PA-YOLO’s asymptotic feature pyramid network (AFPN) instead of YOLOv7’s backbone network to support direct interactions of nonadjacent layers and avoid large semantic gaps between nonadjacent layers. For the occlusion problem of dense targets in the dataset, we introduce a repulsive loss function, which successfully reduces the occurrence of false detection situations. Finally, we propose a customized convolutional block equipped with an EMA mechanism to enhance the perceptual and expressive capabilities of the model. Experimental results on the dataset show that our proposed model achieves excellent performance with an average accuracy (mAP) of 94.5%, which is 6.8% higher than YOLOv7. In addition, our algorithm also succeeds in drastically reducing the model size from 71.3 MB to 48.4 MB, which well demonstrates the effectiveness of the model.