We report a systematic study, including synthesis and multi-aspect characterization, of mercury-doped zinc oxide (Zn₁₋ₓHgₓO) thin films prepared by spray pyrolysis for planar waveguiding applications. Structural analysis by XRD reveals an enhancement in preferential orientation of the (002) plane with Hg concentration, accompanied by an expansion in the lattice parameter and crystal matrix stress along the c-axis. Raman microscopy confirms the formation of wurtzite ZnO, which is indicated by the dominant c-axis orientation vibrational modes. UV-Vis measurements show a slight increase in transmittance and in the optical band gap energy by about 0.02eV, owing to Hg-induced lattice distortion and reduced orbital overlap. Urbach energy analysis shows reduced energetic disorder, and photoluminescence spectra reveal defect-mediated transitions modulated by the introduction of Hg. Hall effect measurements show a reduced carrier concentration from 1.462 × 1013 to 2.203 × 1012 cm⁻3 and an approximately 1.5-fold increase in mobility, indicating suppressed phonon-electron coupling. AFM confirms reduced surface roughness and grain size, with subsequent morphologies well suited for low-loss light coupling. M-lines spectroscopy detects bimodal TE/TM waveguiding behavior with refractive indices roughly 1.97-1.98 and tunable birefringence. The behavior of optogeometric parameters was also confirmed by spectroscopic ellipsometry, including increased refractive indices, reduced root-mean-square roughness, and an almost unvaried thickness. These findings qualify Zn₁₋ₓHgₓO as a promising material for integrated photonic devices, offering a synergistic blend of optical transparency, dielectric properties, and waveguide efficiency.
Sharing Tacit Knowledge (TK) is a key objective of Knowledge Management, a critical issue for both academics and professional. In this work, we are interested in Software Tacit Knowledge, a new subfield of TK, which is very widespread, fairly frequent and remains unaddressed by existing TK approaches. We propose an approach to sharing Software TK between an expert and his learners to address a specific need. It is about the sharing of an expert’s TK relating to the mastery of a particular field, but also and especially relating to the control of the management of this field on dedicated software. This software continues to be widely used and even more so with telecommuting. The approach was developed in a conceptual framework and supported by a formal framework. The formal framework is cognitive to support human knowledge and formal to share it. The approach has been tested on a group of 97 first-year master’s students in a high school. Through the case study, the approach enabled our students to get the expected Software TK, i.e. the ability to design a conceptual solution (i.e. spreadsheet models in our case) for any design problem (i.e. linear problem in our case). Our approach database enables the extraction of key learning indicators that improve the sharing quality. The results are very encouraging. Our approach is applicable to any problem for any field and its software requiring both EK and TK. These softwares can run locally or online.
In this paper, we contribute to this growing body of research by studying a class of nonlinear anisotropic elliptic equations with drift terms, where both the diffusion and the lower-order terms exhibit non-standard directional growth. We aim to establish existence, regularity, and integrability results for weak or distributional solutions, even when the source term f belongs to a low Lebesgue space. This level of generality is essential for applications involving irregular data.
We discuss the regularity of solutions to the p_i(x) -Laplacian problems with lower order terms and degenerate coercivity with the data f in L^m(Ω ) . An interesting feature of this problem is the interplay between the two concepts of weak and entropy solutions under weaker hypotheses on the coefficients. The strategy involving anisotropic Sobolev space and weak Lebesgue space with variable exponents
Monitoring of current-voltage (I-V) characteristics in photovoltaic (PV) modules is essential for optimizing energy yield. Typically, manufacturers provide a large number of parameters for PV modules under different measurement conditions. However, these conditions often differ from real-world outdoor environments, where laboratory tests mostly use solar simulators.In this study, we present a precise computational approach for estimating the parameters of a polycrystalline photovoltaic (PV) module, specifically the IF-P155-36 model, using experimental data collected in harsh desert environments. Our method relies on the five-parameter cell model and employs various evolutionary algorithms (EAs) to accurately estimate unknown parameters.A comparison of the observed output I-V characteristics with those produced by computer simulation using MATLAB demonstrates the efficacy and robustness of the suggested approach. The proposed method attains the lowest Mean Absolute Square Error (MASE) value of 0.069267085, highlighting its superior performance in accurately estimating PV module parameters. This finding underscores the potential of our method to enhance the reliability and efficiency of photovoltaic systems in practical outdoor environments.
