Perovskite solar cells (PSCs) have substantially increased their power conversion efficiency (PCE) to more than 25% in recent years. However, the instability of these devices is still a strong obstacle for their commercial applications. Recently, all-inorganic PSCs based on CsPbI₃ and CsPbI₂Br as the perovskite layer have shown enhanced long-term stability, which makes them potential candidates for commercialization. Currently, all-inorganic PSCs with inverted p-i-n configuration have not yet reached the high efficiency achieved in the normal n-i-p structure. However, the inverted p-i-n architecture has recently drawn attention of researchers because it is more suitable to prepare tandem solar cells. In this work, a theoretical study of inverted p-i-n all-inorganic PSCs based on CsPbI₃ and CsPbI₂Br as the perovskite layer was carried out using SCAPS-1D software (ver. 3.3.09). The performance of different architectures of PSC was examined and compared by means of numerical simulations using various inorganic materials as the hole transport layer (HTL) and the electron transport layer (ETL). The results reveal that CuI and ZnO are the most suitable as HTL and ETL, respectively. In addition, the performance of the devices was significantly improved by optimizing the hole mobility in CuI as well as the thickness, doping density, and defect density in the absorber layer. Maximum efficiencies of 26.5% and 20.6% were obtained under optimized conditions for the inverted all-inorganic CsPbI₃- and CsPbI₂Br-based PSCs, respectively. These results indicate that further improvements in the performance of such devices are still possible.

In this paper, a theoretical study of the electrical parameters degradation of different n-type GaAs sub-cells for InGaP/GaAs/Ge triple junction solar cells irradiated with 1 and 5 MeV electrons has been performed by means of computer simulation. Effects of base carrier concentration upon the maximum power point, short-circuit current, open circuit voltage, diffusion current, recombination current and series resistance of these devices have been researched using the displacement damage dose method, the one-dimensional PC1D device modeling program and a home-made numerical code based on genetic algorithms. The radiative recombination lifetime, damage constant for minority-carrier lifetime and carrier removal rate models for GaAs sub-cells have been used in the simulations. An analytical model has been proposed, which is useful to describe the radiation-induced degradation of diffusion current, recombination current and series resistance. Results obtained in this work can be used to predict the radiation resistance of solar cells over a wide range of energies.

All species of scorpions can inject venom, some of them even with the possibility of killing a human. Therefore, early detection and identification are essential to minimize scorpion stings. In this paper, we propose a novel automatic system for the detection and recognition of scorpions using computer vision and machine learning (ML) approaches. Two complementary image-processing techniques were used for the proposed detection method to accurately and reliably detect the presence of scorpions. The first is based on the fluorescent characteristics of scorpions when exposed to ultraviolet light, and the second on the shape features of the scorpions. Also, three models based on ML algorithms for the image recognition and classification of scorpions are compared. In particular, the three species of scorpions found in La Plata city (Argentina): Bothriurus bonariensis (of no sanitary importance), Tityus trivittatus, and Tityus confluence (both of sanitary importance) have been researched using a local binary-pattern histogram algorithm and deep neural networks with transfer learning (DNNs with TL) and data augmentation (DNNs with TL and DA) approaches. A confusion matrix and a receiver operating characteristic curve were used to evaluate the quality of these models. The results obtained show that the model of DNN with TL and DA is the most efficient at simultaneously differentiating between Tityus and Bothriurus (for health security) and between T. trivittatus and T. confluence (for biological research purposes).

In this paper, a quick and accurate method for extraction of the minority carrier transport properties of p-n or n-p junction solar cells, such as diffusion lengths and surface recombination velocities, is presented. The knowledge of these parameters is essential to investigating factors that limit the performance of photovoltaic devices. The proposed method, based on genetic algorithms and the analytical Hovel model, is used to fit the external quantum efficiency (EQE) curves of solar cells with different emitter thicknesses. As a demonstrative example of application of the procedure carried out in this work, theoretical and experimental EQE curves of n-p GaAs solar cells under the standard AM1.5G spectrum have been used in order to extract the desired parameters. Errors less than 2.4% have been obtained, which shows the capability of the developed tool. An analysis of the total number of iterations is presented. The results obtained can be used to improve the design, optimization, and manufacturing process of high-efficiency photovoltaic devices.

Las celdas solares de perovskita han alcanzado eficiencias superiores al 26 por ciento en una década, consolidándose como una alternativa a las tecnologías fotovoltaicas convencionales. Sin embargo, la inestabilidad y la toxicidad asociadas al plomo limitan su aplicación. En este trabajo se estudian compuestos inorgánicos de cesio, bromo y yodo con sustituciones parciales de plomo por estaño o germanio, orientados a reducir el contenido de plomo. Las propiedades estructurales y electrónicas se calcularon mediante teoría del funcional de la densidad, mostrando buena concordancia con resultados experimentales. El desempeño fotovoltaico de arquitecturas tipo n–i–p se evaluó con el programa SCAPS-1D, considerando óxido de titanio y yoduro de cobre como capas de transporte de electrones y huecos, respectivamente. Las composiciones con hasta un 25 por ciento de plomo alcanzaron eficiencias cercanas al 15 por ciento, destacándose las basadas en estaño sobre las de germanio. Este enfoque integra diseño de materiales y simulación para el desarrollo de celdas solares de perovskita más estables y sostenibles.