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Item CuO/ZnO Bi-layered nanoarchitecture for room temperature CO2 sensing at low concentration(2025) Selwa , KebailiBi-layered ZnO/CuO nanostructured films have been examined for CO2 gas sensing applications. X-ray diffrac tion, Fourier transform infrared, and Raman spectroscopy confirm the formation of a hexagonal wurtzite ZnO and a monoclinic CuO. Scanning electron and atomic force microscopies' observations reveal homogeneous, dense, and quasi-porous surfaces with smooth spherical sponge-like (ZnO), rough spherical-like (CuO and ZnO/ CuO), and rough flat plate-like (for CuO/ZnO) grains morphologies with a few cracks. UV–visible spectroscopy shows greater transmittance (45–90 %) in the infrared and visible domains, while the energy bandgap decreases significantly from 3.3 eV for ZnO to 1.5 eV for the remaining films. The measurements of the sensor's electrical characteristics at room temperature, including current-voltage (I–V), sensitivity-concentration (S–C), and current-time (I-t), indicate a sensitivity to the presence of CO2 gas and that the fabricated sensor exhibits excellent sensitivity and faster response/recovery times. Indeed, the ZnO thin-film sensor recorded the highest sensitivity of 44.77 % at 31 ppm carbon dioxide concentration at room temperature. Based on the results ob tained, a sensing mechanism is proposed. The findings demonstrate that metal oxide multilayered nanostructures are promising candidates for applications such as gas sensing, photocatalysis, and UV photodetectionItem Comprehensive study of a novel cobalt(II) complex: Synthesis, X-ray crystal structure, Hirshfeld surface analysis, computational quantum investigations, and molecular docking insights(2025) Yasmina, SabegThe design of metal complexes that combine structural sophistication with biological relevance has become a cornerstone of modern coordination chemistry. In this study, we present the synthesis and comprehensive characterization of a novel cobalt(II) complex, [Co(phen) 2 2 ( η-bz)]⋅2bzH⋅NO 3 (1), featuring a distorted six- coordinate octahedral geometry, stabilized by two 1,10-phenanthroline and one benzoate ligands. The crystal structure was elucidated using single-crystal X-ray diffraction, revealing a robust supramolecular network strengthened by various non-covalent interactions, including C H⋯O, O H⋯O hydrogen bonds, and π π stacking between aromatic rings. Density functional theory (DFT) calculations, employing the B3LYP/3-21G basis set, provided further insight into the optimized geometry and electronic properties, with a close match to experimental observations. Hirshfeld surface analysis quantified the intermolecular interactions, and molec ular electrostatic potential (MEP) maps highlighted the reactive sites of the complex. Additionally, molecular docking studies demonstrated a strong binding affinity between the cobalt complex and Klebsiella pneumoniae receptors (PDB ID: 6RD3), suggesting potential antibacterial properties. This cobalt complex offers new insights into the structure–activity relationships of transition metal complexes and presents promising avenues for the development of novel therapeutic agents targeting multidrug-resistant bacteria. The findings from this study also pave the way for further exploration of cobalt complexes in catalytic and biomedical applicationsItem Effect of sulfur-modified zinc oxide thin layers on structural, morphological, optical, and photocatalytic properties for environmental applications(2025) Khemissi, LahouelThis study investigates the impact of sulfur (S) doping on the structural, surface morphological, and optical properties of zinc oxide (ZnO) thin films, alongside their potential applications in photocatalysis. X-ray diffraction (XRD) analysis confirmed that the films maintained a hexagonal structure without any impurities or additional phases. The incorporation of 2 wt% S into ZnO led to a reduction in crystallite size from 26.71 nm to 24.59 nm. Scanning electron microscopy (SEM) images showed modifications in surface morphology due to the doping process. Energy dispersive X-ray Spectroscopy (EDS) analysis confirmed the presence of S in the films. Atomic force microscopy (AFM) analysis revealed an increase in root mean square (RMS) roughness from 3.321 nm to 3.879 nm following doping. Ultraviolet-visible (UV-VIS) spectroscopy measurements indicated a decrease in the band gap for the 2 % S-doped ZnO sample from 3.26 eV for pristine ZnO to 3.23 eV. The 2 %-doped ZnO sample exhibited enhanced efficacy in degrading methylene blue dye when exposed to UV and sunlight. The trapping test identified • OH and h + as the primary active species in the photocatalytic processes. Additionally, the thin film demonstrated improved stability and reusability after six recycling cycles, suggesting its potential for wastewater treatment. Thus, S-doped ZnO emerges as a promising material for environmental applicationsItem Enhancing Drain Current in Nano‑carbon Transistors: Simulation and Modeling with LaAlO 3 Dielectric Under NH 3 Exposure(2025) Hana, LaouarWe have developed and analyzed an analytical model of a double-gate graphene nanoribbon ield-efect transistor (GNRFET), which is subsequently evaluated through numerical simulations, to investigate its potential as an ammonia (NH ) gas sensor. Using lanthanum aluminate (LaAlO ), known for its high dielectric constant (K = 30), serves as a gate dielectric in the coniguration of GNRFET gas sensors to minimize short-channel efects and leakage current. The study investigates the static characteristics of the device both in the presence and absence of ammonia gas, providing insights into its potential for gas detection. Following the determination of the device structure, the drain current is calculated as a function of gate and drain bias voltages. The general current equation is enhanced by incorporating expressions that account for the inluence of NH 3 3 gas and temperature variations. These mathematical formulations are then utilized to develop a comprehensive simulation program. The simulation is conducted on GNRFET devices with gate lengths ranging from 100 nm to 300 nm, and NH gas concentrations from 300 ppm to 500 ppm. The simulation results provide insight into how various parameters afect the performance of GNRFETs. Our indings demonstrate that GNRFETs exhibit signiicant potential as high-quality NH gas sensors, highlighting their applicability in environmental monitoring and sensor technology.Item INVERSE SOURCE RECOVERY IN A CLASS OF SINGULAR DIFFUSION EQUATIONS VIA OPTIMAL CONTROL(2025) Mahdi, NedjmaThis paper addresses the inverse problem of identifying a space-dependent source term in a singular parabolic equation involving an inverse-square potential, knowing final time measurement data. The problem is reformulated within an optimal control framework, minimizing a Tikhonovregularized functional to ensure stability. Theoretical contributions include existence and uniqueness of weak solutions for the direct problem, along with a stability estimate for the inverse problem under a first-order optimality condition. A Landweber-type iterative algorithm is designed for numerical reconstruction, validated through synthetic examples with both exact and noisy data.Item Deep Learning Prediction of Wildfire Probability Occurrence Using Meteorological Factors from Khenchela Province Forests(2026) Mohamed, LamriAbstract. Wildfire prediction is crucial for mitigating ecological and economic losses during forest management. This study presents a three-phased AI-driven methodology for enhanced wildfire risk assessment in Khenchela Province. First, explainable AI (XAI, LIME, and SHAP) analyzes eight machine-learning models (CatBoost, XGBoost, SVM, RF, AdaBoost, LR, LightGBM, and DT) to identify 12 key wildfire predictors from a historical dataset. Second, deep learning models (LSTM, RNN, and Prophet) forecast meteorological conditions to improve temporal resolution. Finally, a Bayesian model integrates these forecasts with moisture codes (FFMC, DMC, and DC) and indices (ISI, BUI, and NDVI) to predict wildfire likelihood. Validation using Accuracy, Precision, Recall, F1-score, and AUC demonstrated superior performance, with CatBoost achieving a 95.93% accuracy. This integrated approach enhances wildfire prediction reliability, enables proactive mitigation strategies, and shows the synergistic benefits of combining machine learning, deep learning, and Bayesian modeling for improved wildfire risk management.Item Comparative Analysis of Wildfire Prediction Models Across Climatic Regions: Béjaïa and Sidi Bel Abbes (Algeria) vs. Montesinho (Portugal)(2025) Mohamed , LamriClimate change and urban expansion are intensifying the risks of wildfires globally, with Mediterranean regions such as Algeria experiencing increased vulnerability due to escalating droughts and heatwaves. These events exacerbate ecological degradation, threaten human safety, and impose substantial economic costs, which requires advanced risk assessment frameworks and adaptive mitigation strategies. This study addresses these challenges through a comparative analysis of wildfire prediction models in three climatically distinct regions: Béjaïa and Sidi Bel Abbes in Algeria, and Montesinho Natural Park in Portugal. Employing eight machine learning algorithms—CatBoost, XGBoost, Support Vector Machines (SVM), Random Forest (RF), AdaBoost, Logistic Regression (LR), LightGBM, and Decision Trees (DT)—we predict wildfire severity and identify critical drivers using feature selection (Principal Component Analysis (PCA), Genetic Algorithms (GA), Chi-square tests) and explainability techniques (SHapley Additive exPlanations (SHAP), Local Interpretable Model-agnostic Explanations (LIME), Fuzzy Logic). Key findings reveal stark regional contrasts: In arid Algeria, the temperature and drought indices (Drought Code, DC) dominate the fire dynamics, achieving near-perfect model accuracy (AUC-ROC: 0.97–1.00). In contrast, Portugal’s temperate forests prioritize fuel moisture metrics (Duff Moisture Code, DMC) and temporal factors, although complex fire regimes produce a lower discrimination capacity (AUC-ROC: 0.55–0.78). By integrating global (SHAP/PCA) and localized (LIME) insights, we propose region-specific strategies, including IoT-enhanced microclimate regulation, fuel-break networks, and adaptive early warning systems. This work bridges predictive analytics with actionable forest engineering solutions, offering a scalable framework to mitigate wildfire risks in evolving climatic landscapes.Item IB-PSO: an inversed Butterworth particle swarm optimisation algorithm for multi-agent path planning(2024) Ferial, LaassamiAbstract: Path planning has an immense impact on the agents’ coordination. This problem becomes more challenging to solve due to the various constraints. Recently, many optimisation techniques were proposed to solve the multi-agent path planning. However, among the most reliable techniques are those based on metaheuristic principles. In this paper, we propose a novel multi-agent path planning based on an enhanced version of the particle swarm optimisation (PSO). The inertia weight is a PSO parameter allowing the control of the exploration and the exploitation of the search space. Therefore, we propose a new inertia weight calculation method known as the inversed Butterworth particle swarm optimisation (IBPSO). The main objective of this approach is to provide an adequate transition between the exploitation and the exploration of the search space. To reflect the feasibility of this extension, we compared it with different PSO versions. The showcased results prove the efficiency of the proposed approach.Item Noise-suppression method for UAV-OFDM systems by introducing CV-VSS-NLMS algorithm and single-antenna architecture(2025) Walid , LebbouIn this paper, we address the critical challenge of impulsive interference in orthogonal frequency division multiplexing (OFDM)-based unmanned aerial vehicle (UAV) communication systems, which can severely degrade data transmission reliability. Specifically, we propose a novel complex-valued variable step-size normalized least mean square (CV-VSS-NLMS) adaptive filtering algorithm dedicated for adaptive filtering of complex-valued signals, providing real-time, lightweight, and efficient impulsive-noise suppression for UAV-OFDM signals. In contrast, real-valued VSS-LMS filters treat the real and imaginary parts separately, resulting in poorer mean square error (MSE) convergence for complex signals. The algorithm is developed by efficiently adapting LMS-based filtering strategies to impulsive interference scenarios and adequately integrating prior concepts of electromagnetic pulse suppression within a well-designed single-antenna UAV architecture. This new configuration is especially suited for size, weight, and power-constrained UAV platforms, where reducing complexity is highly desirable. In contrast to conventional blind source separation approaches, the proposed solution ensures reliable communication without excessive processing demands, since it efficiently suppresses impulsive noise and greatly reduces the number of matrix operations. Simulation results demonstrate a significant improvement in bit error rate (BER), confirming that the proposed CV-VSS-NLMS technique provides a robust, dependable, and practical solution for modern UAV communication links.Item Copper nitrate for galena activation: A surface chemistry study of xanthate adsorption(2025) Ibtissem, KoricheThe efficient recovery of lead by selective flotation of galena (PbS) is crucial, yet often hindered by its insufficient inherent hydrophobicity, necessitating surface activation. While copper sulfate (CuSO 4 ) is a conventional activator, the potential and mechanistic details of alternative copper salts, particularly copper nitrate (Cu(NO ), remain largely unexplored for galena activation. This study, for the first time, systematically investigates copper nitrate (Cu(NO 3 ) ) as an activator for galena, focusing on its impact on surface chemistry and subsequent potassium ethyl xanthate (KEX) adsorption. Copper sulfate (CuSO 2 ) was employed as a well-established benchmark to evaluate the relative activation power of Cu(NO 3 ) 2 4 . A suite of analytical techniques, including X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray Spectroscopy (EDS), was utilized to characterize the induced surface modifications. Results demonstrate that Cu(NO 3 ) 2 facilitates KEX adsorption, leading to the formation of copper-xanthate complexes. This was supported by characteristic XRD peaks (e.g., at 2θ = 24.37 ◦ , 18.40 ◦ ) and FTIR absorption bands (e.g., at 1197 cm 1 ). SEM imaging revealed moderate surface roughening, and EDS analysis confirmed copper deposition at an atomic concentration of 0.11 %. In comparison, the benchmark CuSO activation resulted in more extensive copper-xanthate formation, indicated by significantly more intense XRD and FTIR signals (e.g., 2θ = 19.63 ◦ , 28.35 ), more pronounced morphological changes, a higher copper deposition of 0.39 %, and a corresponding sulfur enrichment to 50.70 % S. These findings establish Cu(NO 3 ) 2 ◦ as a viable, albeit less potent activator than CuSO 4 under the studied conditions (0.11 % vs. 0.39 % Cu deposition). This research provides the first detailed surface-chemical evidence of this activation, quantifying elemental changes and highlighting the differential impact of the counterion. This work contributes foundational knowledge for optimizing flotation schemes to improve the efficiency and sustainability of lead ore processing.Item Planarity-Driven Structure−Morphology Correlations in a Co(II) Benzoylacetonate: Comparative Insights across the [M(bzac) ] Family 2(2026) Oumaima , Ghodbane,ABSTRACT: Advancing structure−packing−morphology correlations in β-diketonate complexes provides a rigorous framework for how local coordination geometry propagates into supramolecular organization and ultimately governs macroscopic form. Within this context, we report the synthesis, single-crystal and powder X-ray diffraction analysis, targeted CSD mining, BFDH morphology modeling, and complementary quantum calculations of a new cobalt(II) benzoylacetonate, [Co(bzac) 2 ]. Accurate SC-XRD data at 100 K establish a centrosymmetric trans-CoO chromophore in P2 1 4 /n with a quasi square-planar coordination environment, while PXRD confirms phase purity. In the solid state, [Co(bzac) ] forms directionally coherent zigzag stacks consistent with its experimentally observed acicular habit. A comparative CSD-survey across [M(bzac) ] (M= Pb, Sn, Pdtrans, Pdcis, Cu) reveals metal-dependent variations in stereochemistry, chelate planarity, and packing, positioning the cobalt complex at the most planar and structurally coherent limit. BFDH analysis uncovers a monotonic increase in growth anisotropy culminating in [Co(bzac) 2 ], whose short π−π, metal−π, and C−H···π contacts rationalize its needlelike morphology. FTIR confirms enolization and O,O′-chelation, while UV−vis spectra display ligand-centered π → π* and n → π* transitions. DFT reproduces the experimental symmetry and electronic partitioning, and TD-DFT recovers the absorption envelope. Overall, the integrated SC-XRD ↔ CSD ↔ BFDH ↔ DFT workflow establishes [Co(bzac) 2 ] as a crystallographic, morphological, and electronic benchmark within the family.Item Electronic structures and EDA‑NOCV and absorption spectra analysis of Schif base and pyridine derivatives mixed ligands in transition metal complexes(2025) Ghouzala, BoukehilAbstract DFT calculations using BP86, PBE, and B3LYP functionals have been carried out on a series of complexes of the types [M(L1)(L2)] 2+ , [M(L2) 2 ] 2+ , [M(L2)(L3) 2 ] 2+ , and [M((L3) 4 ] 2+ (M = Ni, Pd, Cu, Zn, and L1 = N-(4methoxybenzylidene) isonicotihydrazone bidentate Schif base, L2 = 2,2′-bipyridine, and L3 = pyridine). A complete rationalization of bonding is provided of these kinds of complexes, where the predicted structures provide to the M(II) cations a perfect square planar geometry for Ni(II), Pd(II), and Cu(II) and a tetrahedral one for Zn(II). Large HOMO–LUMO gaps are calculated for all optimized structures of singlet spin state except for Cu(II) with a doublet spin state; suggesting a good kinetic stability. The low singlet spin state for Ni(II), Pd(II), and Zn(II) and the doublet spin state for Cu(II) complexes are characterized by BP86, PBE, and B3LYP functionals as ground states compared to those of high triplet and quartet spin ones, respectively. The TD-DFT theoretical study performed on the optimized geometries permitted us to predict the UV–Vis spectra and to pinpoint accurately the spectral positions and the nature of the diferent electronic transitions according to their molecular orbital localization; hence, the available experimental UV–Vis spectra are compared to our indings. The electronic spectra obtained in ethanol solvent show red shifts for complexed species due to the coordination of free ligands with metal cations characterized by HOMO → LUMO and HOMO-1 → LUMO electronic transitions.Item On modelling of the one dimensional pseudoelastic effect of shape memory alloys(2025) Imade , ZidaneAbstract. Last decades, a qualitative leap in materials engineering was observed, through developing new materials or discovering new properties. The shape memory alloys are a group of materials exhibiting singular behaviour under a coupled thermomechanical loading, and they are widely used in numerous applications because of their properties. To exploit these properties in engineering, several constitutive models of were developed. The aim of this work is to build a constitutive model that could describe the pseudoelastic behaviour of shape memory alloys in a simpler and more accurate way. Based on thermodynamics and mechanics laws and principles, the developed constitutive model was implemented in an algorithm and compared with experimental data in order to assess its accuracy. The obtained results indicated that the agreement between the real and computer-simulated stress-strain curves was good. This reaffirmed the model’s ability to predict the pseudoelastic behaviour of the shape memory materials under various loading states. These results thus validate especially the temperature sensitivity of Nitinol alloys, which should be taken into account when designing devices that need to function reliably. Keywords: Pseudoelasticity / memory / thermomechanical / transformation / fractionItem Global Theoretical Investigation of Diffusion Driven Instability for Three Coupled Equations of a Reaction Diffusion System(2026) Abd Rraouf, AbidAbstract: In this paper, we investigate the mechanism called DDI ( Diffusion Driven Instability) for a full three dimensional matrix of diffusion coefficients. We apply a linear approach in the neighborhood of an arbitrary equilibrium point using the Routh-Hurwitz stability criterion and we study the existence of at least one eigenvalue with positive real part of the matrix A(k). Our main result is the proof of sufficient and necessary condition for the Turing instability. The research is extended to a reaction-diffusion system for three species.Item Comparative assessment of Reactive Black 5 removal from aqueous solution using organically modified montmorillonite clays(2025) Sabiha , HakkarThe discharge of synthetic dyes such as Reactive Black 5 (RB5) into aquatic environments poses a serious environmental challenge due to their persistence, toxicity, and resistance to conventional wastewater treatments. In this study, organoclays were synthesized by modifying natural montmorillonite clays originating from Algeria (Mnt A) and Germany (Mnt G) using hexadecyltrimethylammonium bromide (HDTMA) and hydrochloric acid (HCl), aiming to enhance their adsorption efficiency for RB5 removal. The clays were characterized using granulometry, XRD, FTIR, TGA-DTG, XRF, and zeta potential analysis, confirming successful modification. Batch adsorption experiments showed rapid dye removal within 60 min, with optimal performance at pH 2, an initial dye concentration of 100 mg/L. Kinetic modeling revealed that the adsorption process followed a pseudo-second-order model, while the equilibrium data were fitted to Langmuir, Freundlich, and Temkin isotherm models. Among these, Langmuir provided the best fit, indicating monolayer chemisorption, with Mnt AM exhibiting the highest adsorption capacity (113.4 mg/g) compared to Mnt GM (101.8 mg/g) and the raw montmorillonite. Temkin model analysis further contributed to understanding the energy distribution and adsorbent–adsorbate interactions. Mechanistic insights indicated that the unmodified clays relied mainly on cation bridging, hydrogen bonding, and van der Waals forces, while HDTMA-modified clays benefited from the additional electrostatic attraction, the hydrophobic effects, and π–π stacking. These results underscore the potential of organoclays as efficient, reusable adsorbents for textile wastewater remediation.Item Explainable fault diagnosis using discrete grey wolf optimization algorithm for photovoltaic system(2025) Slimani, HassinaThe present article introduces the discrete grey wolf optimization algorithm (DGWOA), a novel variant of the grey wolf optimizer (GWO). DGWOA integrates discrete optimization techniques with explainable artificial intelligence (XAI) methodologies. This approach aims to overcome limitations associated with traditional fault diagnosis methods, such as limited accuracy in identifying complex patterns and low interpretability. Furthermore, it mitigates early convergence problems commonly encountered in optimization algorithms and enhances adaptability to discrete classification challenges. The DGWOA algorithm is designed to generate interpretable classification rules for fault detection through a stochastic search strategy. The explainability provided by the model not only enhances decision-making transparency but also improves diagnostic efficiency and predictive accuracy. The proposed algorithm was evaluated using a photovoltaic system dataset and benchmarked against established rule-based classifiers. DGWOA consistently achieved a classification accuracy of 99.48% and a precision of 100%, demonstrating its effectiveness in enhancing fault detection. Moreover, the interpretability of the generated classification rules contributes to the generation of outcomes that are both actionable and comprehensible to decision-makers.Item Enhanced structural, optical, electrical, photocatalytic, and scavengers test of Er-doped ZnO thin films via dip coating for optoelectronic and environmental applications under UV and sunlight exposure(2025) Romaissa , AlloucheThis study explores the impact of erbium (Er) doping on the structural, optical, electrical, and photocatalytic properties of ZnO thin films synthesized via the sol-gel dip-coating method. X-ray diffraction (XRD) confirms a hexagonal wurtzite structure, with peak shifts indicating strain induced by Er incorporation. Notably, a secondary Er-related phase emerges at higher doping levels (10 % and 15 %), suggesting the solubility limit of Er in the ZnO matrix. Scanning electron microscopy (SEM) reveals that moderate doping (2–5 %) improves film uniformity, while excessive Er content (10 % and above) leads to porosity and grain boundary defects. Photoluminescence (PL) spectra show enhanced near-band-edge (NBE) emission (405–416 nm) with increasing Er content, peaking at 15 %, while defect-related emissions (486 nm and 528 nm) indicate changes in charge trapping mechanisms. Electrical analysis via impedance spectroscopy demonstrates improved conductivity, with a decrease in parallel resistance (Rp) up to 10 % Er, followed by an increase at 15 % due to excess defect formation. Photocatalytic experiments using methylene blue (MB) under UV and sunlight irradiation reveal enhanced degradation efficiency, with 2 % Er-doped ZnO performing best under UV light and 10 % Er showing optimal performance under sunlight. Kinetic analysis follows a pseudo-first-order reaction model, Scavenger experiments confirm that hydroxyl radicals (•OH) playing a dominant role under UV irradiation. These results highlight the critical role of Er solubility in tuning ZnO’s properties, making Er-doped ZnO a promising material for optoelectronic applications and environmental remediation.Item ON THE ROBUST STABILITY OF POSITIVE DELAY SYSTEMS UNDER TIME-VARYING PERTURBATIONS IN BANACH LATTICES(2017) ASSMA , DERDOUKHAbstract. A generalisation of an explicit robust stability bound from finite to infinite dimensional case is proved. The studied systems are positive linear time delay differential systems (PLTDDS (s)) which are subject to time varying structured perturbations in Banach lattices. The semigroup method, PerronFrobenius Theorem and the principle of comparison are used. In addition, the coincidence of complex, real and positive stability radii for a number of special cases is proved, and an explicit formula for the radius is derived.Item Enhanced photocatalytic efficiency of Mg-doped ZnO thin films: a comparative study of methanol and ethanol-based sol-gel synthesis(2025) Hayet, FartasThis study provides a comprehensive comparison of the structural, optical, and electrical properties of Mg-doped ZnO thin films synthesized using methanol and ethanol as solvents. X-ray diffraction analysis confirmed the hexagonal wurtzite structure for both cases, with a stronger c-axis orientation in ethanol-derived films. Notably, magnesium incorporation led to an increase in crystallite size, reaching 23 nm in methanol-based films. Morphological analysis using scanning electron microscopy (SEM) revealed dense, homogeneous, and smooth surfaces for both solvent-derived films. Optical characterization indicated a reduction in transmittance for ZnO films synthesized in methanol compared to ethanol-based films, alongside an increase in the energy band gap (ranging from 3.23 to 3.34 eV) as Mg concentration increased. Photoluminescence spectroscopy identified UV emission and defect-related peaks in the visible region at room temperature. Magnesium incorporation was further verified by energy-dispersive spectroscopy (EDS) and Fourier-transform infrared spectroscopy (FTIR). Electrical and photocurrent measurements demonstrated n-type semiconducting behavior with enhanced photoresponse sensitivity. The Seebeck coefficient showed a decreasing trend with increasing Mg doping, with methanol-derived films exhibiting a higher coefficient (−525 μV/K) compared to ethanol-derived films (−400 μV/K). Despite this, methanol-based films exhibited a higher carrier concentration at the same Mg doping level. Furthermore, photocatalytic performance was optimized with 9% Mg-doped ZnO films synthesized in methanol, leading to enhanced degradation efficiency under solar irradiation. These findings emphasize the combined influence of Mg doping and solvent choice on the functional properties of ZnO thin films, providing valuable insights for their potential applications in environmental remediation and energy-related technologies.Item Exact Controllability of the Heat Equation with Boundary Control and Boundary Noise(2025) Noudjoud , HamdiWe study an exact controllability problem for a system governed by the heat equation with Neumann boundary control and boundary noise. We reduce the control problem to a moment problem for which we establish sufficient conditions for its resolution. Keywords: heat equation; exact controllability; Neumann boundary control; boundary white noise; moment problem MSC: 93E03; 35K20; 60H15