M. BENNACER Hamza

Using density functional theory (DFT) with the GGA-PBESol, LDA, and TB-mBJ approximations, this paper thoroughly examines the structural, elastic, optoelectronic, and thermoelectric properties of chalcogenide-double perovskites Ba2NbBiS6 and Ba2TaSbS6, with the view to their potential use in optoelectronic and photovoltaic devices. Based on the calculation results, both compounds achieve the Born stability criteria and negative formation energy values, confirming their thermodynamic stability. Additionally, the elastic criteria analysis shows that the materials exhibit strong resistance to volume deformation while remaining ductile and demonstrate anisotropic characteristics, as seen through the ELATools software. Furthermore, the electronic band structure and density of states were investigated. The Ba2NbBiS6 compound exhibits an indirect band gap (L–X) of 1.58 eV (mBJ-GGA) and 1.45 eV (mBJ-LDA), while the Ba2TaSbS6 compound shows an indirect band gap (L–Γ) of 1.45 eV (mBJ-GGA) and 1.28 eV (mBJ-LDA). Analysis of the (DOS) and the electronic band structure revealed the contribution of 4d_Nd for Ba2NbBiS6 and 5d_Ta for Ba2TaSbS6. Furthermore, optical parameters derived from the dielectric function, including reflectivity, absorption coefficient, and refractive index were predicted. As a result, both compounds exhibit strong photon absorption extending from the visible to ultraviolet regions, with absorption coefficients of 342.03 × 104/cm for Ba2NbBiS6 and 333.92 × 104/cm for Ba2TaSbS6, indicating their high potential for optoelectronic devices. In addition, thermoelectric properties such as the Seebeck coefficient, electrical conductivity, thermal conductivity, ZT merit, and power factor were evaluated. The results provide valuable insights that may guide future experimental studies on these promising materials.

Predicting lattice constants is critical to advancing the discovery of functional materials. When dealing with highly nonlinear data, traditional techniques, such as Density Functional Theory (DFT), frequently suffer from restricted generalization and high computational cost. This study presents a hybrid predictive framework that merges an Autoregressive Type-3 Fuzzy Logic System with the Extended Kalman Filter (AR-T3FLS-EKF) to overcome these constraints and address the issue of restricted and scarce data. The autoregressive technique incorporates physical dependencies among compositional descriptors, whereas the Type-3 fuzzy system improves uncertainty modeling using three-dimensional membership functions. The extended kalman filter adaptively tunes the fuzzy model parameters, improving robustness and convergence. The proposed model is validated on three datasets of perovskite and double perovskite structures using features such as ionic radii, electronegativity, and tolerance factor. Compared with conventional machine learning methods, the AR-T3FLS-EKF achieves superior performance (R2 = 0.9999, MAE = 0.0015 Å, RMSE = 0.0012 Å). These results confirm the model's reliability for accurate lattice constant prediction, especially under limited and scarce data conditions.

This research paper analyzes the structural, elastic, electronic, optical, and thermoelectric properties under partial atomic substitution of the chalcogenide perovskite CaSnX3 (X = S or Se) in the orthorhombic phase (Pnma, N. 62). It adopts the PBE-GGA for initial structure and energy assessments and employs TB-mBJ potential for more accurate electronic characteristics, using ab-initio DFT calculations. The study finds that substituting S with Se increases the lattice constant values while reducing the band gap, which reaches 1.27 eV when X = Se, as calculated using mBJ-GGA method. Furthermore, a new high band gap of 2.47 eV is reported for CaSnS3, significantly higher than that previous research. The negative formation energy indicates that both compounds are thermodynamically and structurally stable. Elastic analysis shows they possess high stiffness, ductility, and notable anisotropy. Partial density of states analysis reveals that X_p (X = S or Se) states are related to the conduction band, while the Sn_5s/5p states are linked to the valence bands, with both compounds exhibit strong ultraviolet absorption. The thermoelectric response predicted by the BoltzTraP2 algorithm demonstrates its potential for thermoelectric and renewable energy applications.

Monitoring environmental data to ensure the safety and reliability of public resources has become a crucial task in data-driven systems. One key aspect of this monitoring is the detection of anomalies—data points or behaviors that significantly diverge from the norm. This study explores the use of a density-based clustering method, DBSCAN, to identify such anomalies within datasets collected from drinking water treatment facilities. DBSCAN's capability to recognize dense regions and isolate noise makes it well suited for flagging irregularities in complex, real-world data. By applying this method to extensive datasets with diverse attributes, the research aims to enhance the consistency and safety of drinking water production processes, contributing to improved public health outcomes and operational resilience in water management systems.

Investigating structural factors: substitution of Ge and Se in Cu2ZnSnS4 solar cell material

This paper employs the density functional theory to investigate the structural, elastic, and optoelectronic properties of chalcogenide-based perovskite CaSiX3 (X = S, Se, and Te) for potential optoelectronic applications. Using PBE-GGA and TB-mBJ approaches, the study examines lattice parameters, bulk modulus, formation energy, phonon frequencies, tolerance factor, and elastic properties to assess material stability. Optical characteristics such as complex dielectric function, absorption coefficient, refractive index, and refractivity are analyzed, along with the density of states and electronic band structure. Indirect band gap values are determined as 3.02 eV for CaSiS3, 1.71 eV for CaSiSe3, and 0.0 eV for CaSiTe3. Both CaSiS3 and CaSiSe3 exhibit high absorption in the ultraviolet spectrum (412–665 nm), indicating potential optoelectronic applications, especially as perovskite-based solar cells. These findings provide insight for future experimental research in this field.

An improves artificial neural network-framework for chalcopyrites energy band gap prediction

This study investigates the physical properties of the novel mixed metal oxide Mg₃ZnO₄, emphasizing its potential in optoelectronic manufacturing. We provide a comprehensive analysis of its structural, optoelectronic, mechanical, and thermodynamic characteristics, focusing on the ternary compound, which crystallizes in a rocksalt phase similar to the mineral Caswellsilverite. Using advanced density functional theory (DFT) and the Full-Potential Linearized Augmented Plane Wave (FP-LAPW) method within the WIEN2k package, we predict the material's properties in detail. Our structural analysis confirms the stability of Mg₃ZnO₄ in the cubic Pm3̅m space group, revealing key crystallographic parameters. The electronic structure calculations indicate a well-defined energy band gap, confirming its semiconducting nature and suitability for optoelectronic applications. Optical properties, including the dielectric function, absorption, and reflection spectra, demonstrate significant light interaction, highlighting the material's potential for UV photodetectors and photovoltaic solar cells. The investigation of elastic properties provides critical insights into the mechanical strength and durability of Mg₃ZnO₄, further supporting its viability for demanding applications. Additionally, our thermodynamic analysis reveals the material's behavior under varying environmental conditions, reinforcing its potential in high-performance optoelectronic devices. These findings establish Mg₃ZnO₄ as a promising candidate for advanced thin-film solar cells and pave the way for future experimental and theoretical studies to explore its unique properties for innovative technological applications.

Impact of dust storms on the performance of grid-connected photovoltaic systems in Adrar, Algeria

Chalcopyrites demonstrate compelling features for optoelectronic and photovoltaic devices, attributed to their valuable properties. Their remarkable light-absorption capabilities and well-suited band gap render them so attractive for applications in these fields. By allowing low-energy sub-bandgap photons to pass through and reducing the thermalisation loss from high-energy photons, intermediate-band materials address the primary problems in solar cells. This approach allows for more efficient use of the solar spectrum, helping solar cells exceed the traditional efficiency limits defined by the Shockley-Queisser limit. The objective of this study was to evaluate the electronic and optical characteristics of CuAlS2 systems doped with transition metals (TM = Mn, Fe) using the Full Potential Linearized Augmented Plane Wave approach within the framework of Density Functional Theory. A stable phase within the systems was observed upon replacing the Al atom with TM. The functionality of the intermediate band was governed by the 3d electronic characteristics of the TM3+ ion and its electronic configuration. The optical properties of CuAlS2 doped with Mn and Fe were analysed by calculating the dielectric function, refractive index, reflectivity, and absorption coefficient. Furthermore, the introduction of Mn and Fe through doping led to the creation of an intermediate band, enhancing visible light absorption and power conversion efficiency. Consequently, the optical spectrum of Mn-doped CuAlS2 and Fe-doped CuAlS2 compounds exhibits additional absorption peaks, accompanied by a significant improvement in absorption intensity. Our findings highlighted the need for continued and futuristic research into the scalability of these materials for practical applications in solar cells, optoelectronics, and spintronic devices. This investigation suggests that Mn-doped CuAlS2 holds the highest potential due to its high charge carriers and low recombination rate, indicating enhanced performance in CuAlS2-based intermediate band solar cells.

This paper presents a new scheme for dynamical systems and time series modeling and identification. It is based on artificial neural networks (ANN) and metaheuristic algorithms. This scheme combines the strength of ANN with the dexterity of metaheuristic algorithms. This fusion is renowned for its ability to detect complex patterns, which considerably improves accuracy, computational efficiency, and robustness. The proposed scheme deals with the curve fitting and addresses ANN's local minima problem. This approach introduces the identification concept using a fresh novel identification element, referred to as the error model. The proposed framework encompasses a parallel interconnection of two models. The principal sub-model is the elementary model, characterized by standard specifications and a lower resolution, designed for the data being examined. In order to address the resolution limitation and achieve heightened precision, a second sub-model, named the error model, is introduced. This error model captures the disparities between the primary model and considered data. The parameters of the proposed scheme are adjusted using metaheuristic algorithms. This technique is tested across many benchmark data sets to determine its efficacy. A comparative study along with benchmark approaches will be provided. Extensive computer studies show that the suggested strategy considerably increases convergence and resolution.

Examining the Structural, Electronic, and optical properties of cubic perovskites PbTiO3 using the First-Principles Calculations.

Insight into the Electronic Properties of SrTiO3 Through First- Principles Calculations.

This study aims to examine the equilibrium Kesterite structure of Cu2BeSnS4, Cu2BeSnSe4, and Cu2BeSnTe4 by the application of density functional theory (DFT) and the Full-Potential Linearized Augmented Plane Wave (FP-LAPW) method. The study demonstrates that both Cu2BeSnS4 and Cu2BeSnSe4 compounds are semiconductors with direct band gaps at the Γ point, while Cu2BeSnTe4 has an indirect band gap (Γ→X). The electronic and optical characteristics of these materials indicate their potential utility in optoelectronic, photonic, and photovoltaic applications. Furthermore, a thorough comparison has been conducted between the obtained results and other experimental and theoretical data from the same chalcogenide family. In summary, the findings offer valuable information on the possible photovoltaic uses of these compounds.

Through experimental exploration, diverse phases—tetragonal and orthorhombic—have been observed within the Cu2ZnGexSn1−xS4 region (0 ≤ x ≤ 1), hinting at potential miscibility gaps. To complement these findings, our computational investigation, employing density functional theory (DFT), delves into the Ge substitution-induced phase transition in Cu2ZnGexSn1−xS4. Contrary to a single-phase behavior, our FP-LAPW at zero temperature results reveal a compelling shift from stannite (Sn-rich) to Wurtzite-Stannite (Ge-rich) at xGe ≈ 80%. Negative enthalpy of formation values indicates the inherent stability of these structures. The calculations reveal an estimated 8.884 meV per atom difference in enthalpies of formation between the Stannite and Wurtzite-Stannite phases for Cu2ZnSnS4. For Cu2ZnGeS4, the Wurtzite-Stannite structure emerges as the most stable, closely trailed by the Stannite structure, with enthalpies of formation at − 4.833 eV·atom−1 and − 4.804 eV·atom−1, respectively. Furthermore, our quasi-harmonic Debye model facilitates the analysis of phase transitions triggered by the introduction of germanium. This is achieved by calculating the Gibbs energy, which remains unaffected by variations in temperature and pressure. As the tin cation is replaced by the smaller germanium cation, there is an observable decrease in the cell parameters. The corresponding reduction in cell volume adheres to the principles of Vegard's Law. Exploring the behavior of these materials in diverse conditions can significantly contribute to enhancing the performance and stability of devices built upon Cu2ZnGexSn1−xS4.

HgSe is a mercury chalcogenide material of the HgX family (where X = S, Se, Te) which crystallises in the zincblende crystal phase. The electronic band structure of HgSe is indicative of a new state of matter in the condensed phase that is of great interest for fundamental physics and possibly new applications. This paper reports ab-initio calculations of the structural, electronic, magnetic, and optical properties of zincblende mercury selenide (HgSe) doped with manganese (Mn) in the inter sites HgMnxSe, with x = 0, 0.058, and 0.117, using the framework of spin-polarized density functional theory. The aim of our investigation is to discuss the different properties of this doped material in order to improve the promising new domain of spintronics with topological systems. Both the GGA+U+mBJ approach and spin-orbit coupling are used for band structure calculations and density of states. The results show a nontrivial topological semimetal order for HgSe and a ferromagnetic topological and metallic behaviour for HgMnxSe. The frequency response of optical properties shows interesting characteristics. Furthermore, the variation with concentration x of the critical point for each of the optical parameters is similar to that of the inverted band gap.

Predicting Lattice Constant for Complex Cubic Perovskite X2YY’O6 using LSTM machine learning method.

This study focuses on investigating the phase transitions in two materials, Cu 2 ZnSnS 4 (CZTS) and Cu 2 ZnGeS 4 (CZGS), which are important for understanding their structural and functional properties. The temperature and pressure-induced tetragonal-orthorhombic phase transitions in these materials are analyzed using density functional theory (DFT) and the quasi-harmonic Debye model. The research aims to examine the changes in the material's structure and the associated thermodynamic properties during these phase transitions. The results reveal that both compounds exhibit a negative value of δH mix , indicating the release of energy during the mixing process, which suggests an exothermic nature. The DFT calculations at zero temperature and pressure demonstrate that the stannite structure represents the ground state configuration of the Cu 2 ZnSnS 4 system (with x Ge = 0%), compared to the wurtzite-stannite structure. The calculations also show that the difference in enthalpies of formation (δH) between the stannite and wurtzite-stannite phases for CZTS is estimated to be 8.884 meV per atom. Regarding Cu 2 ZnGeS 4 , the wurtzite-stannite structure is found to be the most stable, closely followed by the stannite structure, with enthalpies of formation of −4.833 eV·atom −1 and −4.804 eV·atom −1 , respectively. Notably, there are no definitive reports on enthalpy studies for the Cu 2 ZnGeS 4 system in the existing literature. Understanding the behavior of these materials under different conditions can contribute to the development of improved performance and stability of devices based on CZTS and CZGS.

Investigation of the structural and electronic characteristics of SrTiO3 using first principles calculations

In this work, we investigated the optoelectronic properties of MgZnO using density functional theory based on linear augmented plane wave (FP-LAPW) method. To deal with the exchange-correlation potential for total energy calculations, the LDA and GGA approximations were used. In addition, the modified Becke Johnson (TB-mBJ) approach, which successfully corrects the band gap problem, was used for the band structure calculations. The calculated lattice constants and band gap values for this compound are in good agreement with available theoretical data. As well as the dielectric function and the absorption coefficient are calculated to get the optical parameters. The achieved results indicate that this material is particularly interesting for photovoltaic conversion applications.

This study focuses on investigating the phase transitions in two materials, Cu 2 ZnSnS 4 (CZTS) and Cu 2 ZnGeS 4 (CZGS), which are important for understanding their structural and functional properties. The temperature and pressure-induced tetragonal-orthorhombic phase transitions in these materials are analyzed using density functional theory (DFT) and the quasi-harmonic Debye model. The research aims to examine the changes in the material's structure and the associated thermodynamic properties during these phase transitions. The results reveal that both compounds exhibit a negative value of δH mix , indicating the release of energy during the mixing process, which suggests an exothermic nature. The DFT calculations at zero temperature and pressure demonstrate that the stannite structure represents the ground state configuration of the Cu 2 ZnSnS 4 system (with x Ge = 0%), compared to the wurtzite-stannite structure. The calculations also show that the difference in enthalpies of formation (δH) between the stannite and wurtzite-stannite phases for CZTS is estimated to be 8.884 meV per atom. Regarding Cu 2 ZnGeS 4 , the wurtzite-stannite structure is found to be the most stable, closely followed by the stannite structure, with enthalpies of formation of −4.833 eV·atom −1 and −4.804 eV·atom −1 , respectively. Notably, there are no definitive reports on enthalpy studies for the Cu 2 ZnGeS 4 system in the existing literature. Understanding the behavior of these materials under different conditions can contribute to the development of improved performance and stability of devices based on CZTS and CZGS.

Insights into structural and electronic properties of CaTiO3 perovskite: Density functional calculations

Structural, elastic, and electronic properties of cubic perovskite compound BaTiO3 : ab initio study

As an alternative to traditional photovoltaic semiconductors, perovskite materials like ABX3 have recently caught the interest of researchers. These materials' unique physical traits and specific gap value, which have a significant impact on their overall effectiveness and performance, are what essentially led to this shift in attention. Using the ab initio method calculations. The structural and electrical characteristics of CaSiO3, a tetragonal compound, are investigated in this work using first-principles calculations based on the full potential-linearized augmented plane wave technique (FP-LAPW) within the density functional theory (DFT). Our study thoroughly examines electrical properties, such as band structure and density of states (DOS), in order to predict CaSiO3 viability as a potential photovoltaic material. CaSiO3 is a promising candidate for future exploration because preliminary results indicate that it exhibits semiconductor properties.

Perovskites have gained significant attention in recent years due to their unique and versatile material properties. The lattice parameters of the perovskite compounds play a crucial role in the engineering of layers and substrates for heteroepitaxial thin films. As an essential parameter in the cubic perovskite structure, the lattice constant, plays a significant role in the development of materials for specific technological applications and serves as a distinctive identifier of the crystal structure of the material. In the field of materials science, advanced Computational Intelligence (CI)-based techniques have become increasingly important for simulating the relationship between the physicochemical parameters of chemical elements and the physical properties of materials and compounds. Hence, this paper presents efficient techniques based on artificial neural network (ANN) and fuzzy logic to predict the lattice constants of pseudo-cubic and cubic perovskites. The identification of optimized parameters for the ANN and fuzzy logic models is accomplished using innovative metaheuristic algorithms such as, Particle Swarm Optimization (PSO), Invasive Weed Optimization (IWO) and Imperialist Competitive Algorithm (ICA). In the first part, the study assessed, the effectiveness of various metaheuristic algorithms (PSO-IWO-ICA) in tuning the parameters of the ANN prediction structure in order to get the optimal parameter of the ANN. Whereas in the second part, once we extracted the best optimization algorithm, we combined it with the fuzzy logic technique and then we compared the effectiveness of the two techniques, ANN and Fuzzy logic. On the basis of root mean square error (RMSE), mean absolute error (MAE) and the coefficient of determination (R2), the proposed PSO-ANN and PSO-Fuzzy based models are compared with existing and recent models such as Ubic, Sidey, and Owolabi. The proposed PSO-Fuzzy model performs better than our PSO-ANN model, the Ubic, Sidey, and Owolabi models, with performance improvement of 70.90%, 90.36%, 89.74% 84.46%, respectively on the basis of RMSE. Similarly, it attains performance improvement of 71.26%, 90.31%, 89.58%, and 85.02% on the basis of MAE. Furthermore, the developed PSO-ANN based model outperforms the Ubic, Sidey and Owolabi models with performance improvement of 66.86%, 64.74% and 46.60% respectively, on the basis of RMSE and percentage enhancement of 66.27%, 63.75%, and 47.90% when compared on the basis of MAE. Although the PSO-Fuzzy model has the best performance of all the compared models, the developed PSO-ANN based model possesses the advantage of easy implementation in addition to its moderate performance.

Classification and prediction of water quality index using deep learning techniques

Dispositif de mesure non invansive et de prediction de la glycemie

Computational prediction of structural, electronic, and elastic characteristics of the cubic perovskite CaSiO3: ab-initio calculation

Double perovskite oxides have received a lot of interest in the last ten years because of their distinctive and adaptable material properties. Among the six parameters in the cubic structure, the lattice constant is the sole changeable parameter, which plays an important role in developing materials for particular technological applications and distinctively identifies the crystal structure of the material. In this paper, the extreme learning machine (ELM) is used to correlate the lattice constant of A+22BCO6 cubic perovskite compounds, such as their ionic radii, electronegativity, oxidation state, and lattice constant. We investigated 147 compounds with lattice constants between 7.700 and 8.890Å. The prediction method has a high level of accuracy and stability and provides accurate estimates of lattice constants.

Electrocardiogram (ECG) is one of the main tools to interpret and identify cardiovascular disease. ECG signals are frequently submitted to various noises, which alter the original signal and reduce its quality. ECG signal filtering enables cardiologists to assess heart health accurately. The present paper presents a newfound approach for ECG signal denoising built on two techniques which are EMD (Empirical Mode Decomposition) and AWC (Average Wavelet Coefficient method). The basic idea behind the suggested technique initially consists of deconstructing noisy ECG signal data on a restricted number of IMFs (Intrinsic Mode Functions) and then using the AWC technique to compute each IMF’s Hurst exponent. Finally, after a thresholding operation, the clean ECG signal is recovered by adding all IMFs, excluding those considered parts of noise. The suggested approach is assessed over experiments using the MIT-BIH databases. The experimental results reveal that the suggested method efficiently extracts ECG signals from noisy data samples.

Lattice Constant Prediction of Complex Cubic Peroveskite A2BCO6 using Extreme learning Machine

Soft Sensing Modeling Based on Support Vector Machine and Self-Organaizing Maps Model Selection for Water Quality Monitoring

Sensor Anomaly Detection using Self Features Organizing Maps and Hierarchical-Clustring for Water Quality Assessment

EMD Based Average Wavelet coefficient method for ECG Signal Denoising

The electronic band gap energy is an essential photo-electronic parameter in the energy applications of engineering materials, particularly in solar cells and photo-catalysis domains. A prediction model that can correctly
predict this band gap energy is desirable. A new approach for predicting a band gap energy is suggested in this
paper. The proposed structure is based on artificial neural networks (ANN) and the particle swarm optimization
algorithm (PSO); this structure can solve the artificial neural network’s local minima issue while preserving the
fitting quality. Our technique will hasten the identification of novel chalcopyrite in photovoltaic solar cells with
improved resolution. The suggested model combines two sub-systems in a parallel configuration. A conventional
prediction system with a low resolution for the training data being considered makes up the first ANN subsystem. A second ANN sub-system, labelled the error model, is introduced to the primary system to address
the resolution quality issue, representing uncertainty in the primary model. The particle swarm optimization
algorithm is used to identify the parameters of the proposed neural system. The method’s effectiveness is assessed
in terms of several criteria, and the output of our system shows good performance compared to experimental and
other calculated results. Several benchmark approaches were compared with the proposed system in detail.
Numerous computer tests show that the suggested strategy can significantly enhance convergence and resolution.

Realisation d'un systeme automatique de regulation de l'ammoniac dans un aquarium

Realisation d'un appareil de mesure de l'indice de qualite de l'eau propre

Numerical study of ZnO/CdS/CdSnP2 solar cells

Structural and electronic properties of silar cell compound CuAlX2(X=Se, Te): an ab-initio approach

In this investigation a novel PSO-ANN scheme for composite materials properties prediction is presented. It is based on neural networks which are used in many applications such as image recognition, classification, control and system identification. This approach will deal with local minima problem of the neuronal networks architecture and simultaneously preserve the fitting quality. The proposed scheme comprises a parallel interconnection of tow sub-ANN prediction systems. The first sub-ANN prediction system is the primary system, which represents an ordinary system with a low resolution for the trainig data under consideration (composite materials properties). To overcome resolution quality problem, and obtain a prediction system with higher resolution, we will introduce a second ANN sub model called Error model which will represent a model for the error between the primary prediction system and the real training data. ANN scheme Identification is achieved by innovative metaheuristic algorithm such as particle swarm optimization (PSO). The method’s effectiveness is evaluated through testing on the composite materiels to predicte thier physical propreties. Intensive computer experimentations confirm that the proposed approach can significantly improve convergence and resolution

In this work, optoelectronic and magnetic properties of Co-doped and (Co, Sm) co-doped ZnS have been studied using the first principles calculation based on density functional theory (DFT) and FP-LAPW method with GGA and GGA + U approximations in zinc blende structure. The lattice parameter will increase by (Co, Sm) co-doping ZnS. The difference in total energy is calculated and confirms the stability of ZnS: Co in ferromagnetic states (FM) and ZnS: (Co, Sm) in antiferromagnetic states (AFM). The total magnetic moment is found to be more interesting by (Co, Sm) co-doping. The band structure, the total density of states (TDOS) and partial density of states (PDOS) show that ZnS: Co has a semiconducting character. While ZnS: (Co, Sm) has half-metallic character behavior with 100% spin polarization at the Fermi level provided by the RE-4f states. Moreover, optical properties such as dielectric functions and absorption coefficients for ZnS: Co and ZnS: (Co, Sm) were also discussed and found to be more interesting in the visible region by (Co, Sm) co-doping. The improved optical and magnetic results indicate that (Co, Sm) co-doped ZnS can be used as a promising candidate for optoelectronic and spintronic devices in the future.

In this study, we have investigated physical ground-state properties of three novel semiconductors to address many problems related to the photovoltaic (PV) industry. A computational package (wien2k) based on Density Functional Theory (DFT) is used to study the optical, structural, as well as electronic properties of delafossite transparent conducting oxides CuMO2 (M= Al, Sc and Y). The Full-Potential Linearized Augmented Plan Wave method (FP-LAPW) which is based on DFT has also been employed in this study. To compute the structural and electronic parameters the Local Density Approximation (LDA), Perdew, Burke and Ernzerhof Generalized Gradient Approximation (PBE-GGA) have been utilized as the exchange-correlation term. Furthermore, Tran-Blaha modified Beck–Johnson potential (TB-mBJ) has been utilized to achieve better degree of accuracy in computing the electronic and optical characteristics. The results of the study have also been compared to the previous theoretical and experimental ones. The ternary delafossite transparent conducting oxide compounds can be considered as an alternative material in photovoltaic applications.

Due to their useful physical properties, copper-based chalcogenides materials are recently promising for numerous emerging technological fields. In photovoltaics, discovering and designing suitable materials for solar cells is a primary technical challenge. The structural, electrical, optical, and thermoelectric properties for both CuYSe2 and CuYTe2 in the hexagonal phase, as well as CuYS2 in the orthorhombic phase have been investigated using a numerical Full Potential-Linearized Augmented Plane Wave (FP-LAPW) technique based on Density Functional Theory (DFT).

To compute the structural properties, both, the local density approximation (LDA) and the generalized gradient approximation (PBE-GGA) were used as exchange-correlation potentials. On the other hand, the modified Becke-Johnson (mBJ) was used to compute the optoelectronic, properties with higher degree of precision. Our calculations revealed that these three compounds have indirect band gaps in the range of 0.6 eV–2.1 eV. Moreover, numerous thermoelectric qualities of the investigated compounds estimated as a function of chemical energy at different temperatures using the semi-local Boltzmann transport theory, whereby the findings exhibit a higher Seebeck coefficient for CuYS2 compared to CuYZ2(Z = Se and Te) up to 2.7 mV/K for CuYS2 at 300 K, with acceptable values of thermal and electronic conductivity. The quasi-harmonic model is used to examine thermodynamic properties such as heat capacity at constant pressure and volume, entropy, Debye temperature, and thermal expansion coefficient under both pressure and temperature influences. As a result of this study, CuYS2, CuYSe2 and CuYTe2 are promising materials for optoelectronic devices, especially as photovoltaic materials in solar cells.

Structural, electronic, thermoelectric and optical properties of CuAlS2 chalcopyrite material

Recently, II-IV-V2 ternaries have received much concentration due to their valuables properties using in potential applications in optoelectronic, nonlinear optic, and photovoltaic absorber material in solar cells. The main aspects of interest for a material to be used in optoelectronic: emission of light and photovoltaic effect. The optoelectronic properties of BeGeP2 ternary has been theoretically investigated from ab-initio calculation by using the density functional theory within FP-LAPW method integrated in the Wien2k code. Our calculations within TB-mBJ approach indicate optimal bandgap energy and a very high optical absorption coefficient above 105 cm-1, making this compound suitable for solar cell absorbers.

We present a theoretical study of the electronic structure, magnetic and optical properties of RE-doped zinc sulphide (RE = Sm, Eu, Gd, and Er) in a zinc blende phase, which is investigated using the spin-polarized spin density functional theory (spin-DFT). The First-principles calculations based on density functional theory and the full-potential linearized augmented plane wave method (FP-LAPW) are performed by employing the GGA + U (U is the Hubbard term of the Coulomb repulsion correlation) approximation. The lattice parameter will increase by RE doping ZnS. The total density of states (TDOS) and partial density of states (PDOS) show that all the systems have half-metallic character behaviour with 100% spin polarization at the Fermi level provided by the RE-4f states except ZnS: Eu it has a semiconductor character. The values of differences in total energy ΔE indicate that ZnS: Sm, ZnS: Eu, and ZnS: Er are stable in the ferromagnetic phase. However, ZnS: Gd favours the AFM phase. The total magnetic moment of all systems is very interesting. All systems showed significant redshift except ZnS: Eu, and all exhibited broad absorption in the UV region. Doping by RE is a feasible method to enhance the electronic, magnetic, and optical properties of ZnS for the new generation of optoelectronic and spintronic applications.

In this study, 1D Photonic Crystal (PhC) with Nematic Liquid Crystal (N-LC) central microcavity is analyzed and discussed using Rigorous Coupled Wave Analysis (RCWA) method. A microcavity is inserted into the 1D PhC by the Air Defect, making it ideal for measuring the properties of an N-LC contained inside the microcavity. Here simulation is considered for N-LC (E7) as a thermal sensor. The principle of photonic crystal thermal sensor operation is studied in the TE mode of the incident beam. We conduct a detailed study of the thermal sensor with differences in the width of central microcavity of N-LC. The sensitivity and quality factor are evaluated. Compared to other photonic crystal sensors mentioned previously, this thermal optical sensor has a much simpler structure and higher sensitivity.

In this work, we studied the magnetic stability, electronic and optical properties of Gd doped CdS and (Gd, Mn) co-doped CdS, in a zinc blend structure, using first-principles calculations based on the full-potential linearized augmented plane wave method (FP-LAPW) with the GGA + U approximation. The lattice parameter increases by Gd doping and decreases by (Gd, Mn) co-doping. The calculations of the differences in total energies ΔE prove that the CdS: Gd is stable in the antiferromagnetic state (AFM). While, the co-doped system CdS: (Gd, Mn) is stable in the ferromagnetic states (FM). The CdS: (Gd, Mn) has an interesting magnetic moment compared to the CdS: Gd. The total densities of states show the metallic character of the CdS: Gd and the half-metallic character of CdS: (Gd, Mn). The real and imaginary parts of the dielectric function, the absorption coefficient, and the refractive index are calculated. Both systems have a significant redshift and have a strong light absorption in the visible and UV regions. Co-doping CdS by Gd and Mn gives interesting results compared to the CdS: Gd. These make CdS: (Gd, Mn) an important material for different applications. This work provides the possibility to fabricate new optoelectronic and spintronic devices.

A numerical full-potential linearized augmented plane method within density functional theory is performed to study the electronic structure include, energy band gap, total and partial density of states and chemical bonding as well as optical constants of Ba1−xSrxTiO3 (BST) (0≤ x ≤ 1) crystalizes in the paraelectric and ferroelectric phases. Results obtained using the improved [Koller-Tran-Blaha]-mBJ potential show excellent agreement with the experimental data. It is observed that the band gap in BST crystals increases with increasing Sr dopants due to the resonant interaction of O_2p orbitals mixed with co-doping Sr_4d states with the top of the valence band. BST exhibits a direct band gap at x range ~0.04–0.88 covering the wavelengths range ~397–436 nm within the visible spectrum region. The dielectric functions and optical constants such as refractive index, reflectivity and absorption coefficient are computed for radiation range 0–10 eV in comparison with measured data. The critical-point energies in various optical spectra are due to interband transitions from occupied O_2p states and little admixture of Sr_4p/d and Ba_4p orbitals localize in the top of the valence band to unoccupied Ti_3d, Sr_4p, and Ba_4d orbitals localize in the bottom of the conduction band. Excellent ultraviolet absorption (~4–8 eV) and visible regime transparency are achieved. BaSrTiO3 (BST) perovskite is a promising candidate for manufacturing low-cost high-efficiency solar cells and designing of novel sources of light operating in the visible spectrum region.

The main aim of this work is to determine and explain the relationships between optoelectronic properties and the sulfur anion content in Cu2ZnSn(SxSe1−x)4 solid solution. Band gap and absorption coefficient are of primary interest to the engineers and scientists researcher worked in optoelectronic field. Herein, the electronic and optical properties are calculated based on 128 conventional atoms within lattice parameters obtained at 300 K by using the FP-LAPW method combined with quasi-harmonic Debye model. The composition dependent band gaps of CZTSSe solid solutions are investigated by TB-mBJ+U. As results, all materials are semiconductors with a direct band gap ranging from 0.614 to 0.99 eV. The band gap variation increases as a function of sulfur anion content and showed a positive deviation from Vegard's law with a very small downward bowing parameter of + 0.079 eV. The density of state (DOS) calculations indicate that the energy bands of VBM involve Cu_d/anion(S/Se)_p hybridized antibonding-like states. Based on band alignment, the Ec offset between CZTS and CZTSe is larger than the Ev offset. These results are reported previously in other work and are confirmed in this study. Our work included a systematic comparison of the influence of S/(S+Se) atomic ratios on optical quantities. The dielectric function tensors show remarkable anisotropy. In addition, the static dielectric constants are found to decrease with sulfur anion content. The CZTSSe is proved to be suitable for good solar cells with high absorption coefficient (> 104 cm−1). Such deep optical studies would be helpful for future optoelectronic applications of these compounds with different S/(S+Se) atomic ratios.

Optoelectronics properties of Cu2ZnSn(SxSe1-x)4: DFT calculation

The physical properties of the ZnSnP2 compound semiconductors in chalcopyrite phase have been investigated by employing full potential linearized augmented plane wave (FP-LAPW) method to solve the Kohn-Sham equations within framework of Density Functional Theory (DFT) using Wien2k tool. The atomic configuration of cell structure is crystalized in the chalcopyrite phase. For this, the Local Density Approximation (LDA) and Wu–Cohen Generalized Gradient Approximation (WC–GGA) were employed as the exchange–correlation term to calculate the structural and electronic properties. Moreover, the Engel–Vosko GGA (EV-GGA) and the recently modified semi–local Becke–Johnson (mBJ) functional were also used to calculate the electronic and optical properties in order to get some better degree of precision. The obtained results are in a good agreement with the experimental data, which indicate that the studied compound is among promising material for thin films solar cells manufacturing.

The performance of copper indium gallium selenium (CIGS) based solar cells with cadmium sulfide (CdS) and magnesium zinc oxide (MgxZn1-xO) buffer layers has been investigated comparatively with the new version of a one-dimensional device simulation program for the analysis of microelectronic and photonic structures (wxAMPS-1D). The structures of solar cells have been analysed keeping in view the effect of doping as well as of thickness of buffer and absorber layers. It is observed that the conversion efficiency and external quantum efficiency (EQE) are improved using Mg0.125Zn0.875O compound buffer layer for ZnO/Mg0.125Zn0.875O/CIGS structure to 22.01% and 89.7%, respectively, whereas the obtained conversion efficiency and EQE for ZnO/CdS/CIGS structure are 21.06% and 88.78%, respectively. The obtained results are in good agreement with the recently published work and the proposed structure of solar cells would have potential regarding improvements in the existing solar cell technology.

We used density functional theory based calculations to investigate the structural and optic properties of copper-based ternary chalcogenide Cu-M-X (M : Sb, Bi & X : S, Se). These form orthorhombic crystallographic structure with Pnma space group. The calculated electronic band structure is indirect for all these compounds in conjunction with a close direct band gap transition. Interestingly, a very high optical absorption coefficient above 105 cm-1 above band gap values is noticed for these materials, making them suitable for ultrathin solar cell absorbers.
 

There are two main aspects of interest for a material to be used in optoelectronic: emission of light and photovoltaic effect. Currently, chalcopyrite compounds have received much concentration because of their potential applications in the field of light-emitting diodes, nonlinear optic applications, and photovoltaic sensitive material in solar cells. The optoelectronic properties of ZnSnP2 chalcopyrite-type ternary have been theoretically investigated from first principles. In this work we try to calculate and to study the optical properties using the FP-LAPW method within TB-mBJ approximation, to explore their competence and ability in photovoltaic applications.

The main aspects of interest for a material to be used in optoelectronic: emission of light and photovoltaic effect. Recently, II-IV-V2 compounds have received much concentration due to their potential applications in nonlinear optic, and photovoltaic absorber material in solar cells. The optoelectronic properties of BeSiAs2 ternary have been theoretically investigated from first-principles calculation. In this work, we try to calculate and to study the optoelectronic properties using FP-LAPW method by the Wien2k code within TB-mBJ approximation, to detect their competence and ability in photovoltaic applications.

This paper is dedicated to the ab initio study of the structural and thermodynamic properties of Cu2ZnSn(SxSe1−x)4 bulk alloys. The calculations are conducted using full-potential linear-augmented-plane-wave plus local-orbital (FP-LAPW + lo) method within the revised generalized gradient approximation of Perdew–Burke–Ernzerhof (GGAPBEsol). This method is used to find more valuable equilibrium structural parameters than the simplest approximations of PBE and local density approximation (LDA). The obtained structural properties appear to be affected by the relaxation effect, and all alloys are thermodynamically favorable to the process according to the enthalpy of formation calculations. We find here a nonlinear dependence of lattice parameters a and c with respectively a small downward bowing parameter b of + 0.09 Å and + 0.19 Å for relaxed structures. The thermodynamic quantities, namely the entropy, the constant volume, the pressure heat capacity (Cv and Cp) and Debye temperature, are computed for different S/(S + Se) atomic ratios by varying temperature from 0 K to 1000 K. These quantities are successfully obtained by using the combined approach of FP-LAPW and a quasi-harmonic model. Overall, there is good agreement between our calculated quantities and other results.

A Biometrics identification system is refers to the automatic recognition of individual person based on their characteristics. Basically biometrics system has two broad areas namely unimodal biometric system and multimodal biometric system. However, a reliable recognition system requires multiple resources [1].
Although multimodality improves the accuracy of the systems, it occupies a large memory space and consumes more execution time considering the collected information from different resources. Therefore we have considered the feature selection[2], that is, the selection of the best attributes that enhances the accuracy and reduce the memory space as a solution. As a result, acceptable recognition performances with less forge and steal can be guaranteed. In this work we propose an identification system using multimodal fusion of finger-knuckle-print, fingerprint and palmprint by adopting several techniques in feature level for multimodal fusion[3]. A feature level fusion and selection is proposed for the fusion of these three biological
traits. The proposed system has been tested on the largest publicly available PolyU [4] and Delhi FKP[5] databases. It has shown good performance.

First-principles calculations and numerical modeling on the structural and optoelectronic properties of chalcopyrite materials for solar cell application.

Experimental investigation and first-principles calculations on the physical properties of CuGaTe2 for solar cells application

The all electrons full potential linearized augmented plane waves (FP-LAPW) method with GGA, LDA and mBJ approximation is used to study BaThO3 perovskite in cubic and orthorhombic phases. The structural parameters are found consistent with the experimental results. The electronic band structures and density of states demonstrate that BaThO3 is a wide band gap insulator in both phases. Furthermore, the optical properties demonstrate that the optical gap of the material is 5.8 eV, which lies in the UV region of the electromagnetic spectrum and hence the compound can be used in optoelectronic devices.