In this paper, a n-i-p planar heterojunction simulation of Sn-based iodide perovskite solar cell (PSC) is proposed. The solar cell structure consists of a Fluorine-doped tin oxide (FTO) substrate on which titanium oxide (TiO2) is placed; this material will act as an electron transporting layer (ETL); then, we have the tin perovskite CH3NH3SnI3 (MASnI3) which is the absorber layer and next a copper zinc and tin sulfide (CZTS) that will have the function of a hole transporting layer (HTL). This material is used due to its simple synthesis process and band tuning, in addition to presenting good electrical properties and stability; it is also a low-cost and non-toxic inorganic material. Finally, gold (Au) is placed as a back contact. The lead-free perovskite solar cell was simulated using a Solar Cell Capacitance Simulator (SCAPS-1D). The simulations were performed under AM 1.5G light illumination and focused on getting the best efficiency of the solar cell proposed. The thickness of MASnI3 and CZTS, band gap of CZTS, operating temperature in the range between 250 K and 350 K, acceptor concentration and defect density of absorber layer were the parameters optimized in the solar cell device. The simulation results indicate that absorber thicknesses of 500 nm and 300 nm for CZTS are appropriate for the solar cell. Further, when optimum values of the acceptor density (NA) and defect density (Nt), 1016 cm−3 and 1014 cm−3, respectively, were used, the best electrical values were obtained: Jsc of 31.66 mA/cm2, Voc of 0.96 V, FF of 67% and PCE of 20.28%. Due to the enhanced performance parameters, the structure of the device could be used in applications for a solar energy harvesting system.

The applicability of the path planning strategy to robotic manipulators has been an exciting topic for researchers in the last few decades due to the large demand in the industrial sector and its enormous potential development for space, surgical, and pharmaceutical applications. The automation of high-degree-of-freedom (DOF) manipulator robots is a challenging task due to the high redundancy in the end-effector position. Additionally, in the presence of obstacles in the workspace, the task becomes even more complicated. Therefore, for decades, the most common method of integrating a manipulator in an industrial automated process has been the demonstration technique through human operator intervention. Although it is a simple strategy, some drawbacks must be considered: first, the path’s success, length, and execution time depend on operator experience; second, for a structured environment with few objects, the planning task is easy. However, for most typical industrial applications, the environments contain many obstacles, which poses challenges for planning a collision-free trajectory. In this paper, a multiple-query method capable of obtaining collision-free paths for high DOF manipulators with multiple surrounding obstacles is presented. The proposed method is inspired by the resistive grid-based planner method (RGBPM). Furthermore, several improvements are implemented to solve complex planning problems that cannot be handled by the original formulation. The most important features of the proposed planner are as follows: (1) the easy implementation of robotic manipulators with multiple degrees of freedom, (2) the ability to handle dozens of obstacles in the environment, (3) compatibility with various obstacle representations using mathematical models, (4) a new recycling of a previous simulation strategy to convert the RGBPM into a multiple-query planner, and (5) the capacity to handle large sparse matrices representing the configuration space. A numerical simulation was carried out to validate the proposed planning method’s effectiveness for manipulators with three, five, and six DOFs on environments with dozens of surrounding obstacles. The case study results show the applicability of the proposed novel strategy in quickly computing new collision-free paths using the first execution data. Each new query requires less than 0.2 s for a 3 DOF manipulator in a configuration space free-modeled by a 7291 × 7291 sparse matrix and less than 30 s for five and six DOF manipulators in a configuration space free-modeled by 313,958 × 313,958 and 204,087 × 204,087 sparse matrices, respectively. Finally, a simulation was conducted to validate the proposed multiple-query RGBPM planner’s efficacy in finding feasible paths without collision using a six-DOF manipulator (KUKA LBR iiwa 14R820) in a complex environment with dozens of surrounding obstacles.

The effect of using different electrolytes in the physical and optical properties of porous silicon was studied. To do this porous silicon (PS) samples photoluminescent in the visible range from (100) oriented n-type crystalline silicon prepared by anodic etching were obtained. The first electrolyte was composed of a mixture of hydrofluoric acid (HF) and ethanol (CH3-CH2-OH) in a ratio of 1 : 2, respectively. The second was composed of hydrofluoric acid (HF), ethanol (CH3-CH2-OH), and hydrogen peroxide (H2O2) in a ratio of 1 : 1 : 2, respectively. Raman scattering, photoluminescence (PL), gravimetry, scanning electron microscopy (SEM), and energy dispersive spectrometer (EDS) measurements on the PSL were carried out. Raman scattering showed that the disorder in the samples obtained with H2O2is greater than in the samples obtained without this. The PL from PS increased in intensity with the incremental change in the anodization time and showed a blueshift. The blueshift of PL is consistent with the reduction in size of the silicon nanocrystallites. The sizes of nanocrystals were estimated to be 3.08, 2.6, and 2.28 nm. The gravimetric analysis showed that the porosity increased with the incorporation of H2O2. SEM images (morphological analysis) showed an incremental change in the quantity and in the porous size.