Exergy, exergoeconomic optimization and exergoenvironmental analysis of a hybrid solar, wind, and marine energy power system: A strategy for carbon-free electrical production.

In this research, aligned with global policies aimed at reducing CO2 emissions from traditional power plants, we developed a holistic energy system utilizing solar, wind, and ocean thermal energy sources, tailored to regions optimal for ocean thermal energy conversion (OTEC). The selected site, characterized by favorable wind and solar conditions close to areas with high OTEC potential, is designed to meet the electricity needs of a coastal community. The system's core components include an Organic Rankine Cycle, turbines, thermoelectric elements, pumps, a heat exchanger, a wind turbine, and a solar collector. A detailed system analysis and thermodynamic evaluation based on thermodynamic principles were carried out using the Engineering Equation Solver (EES) software. Key factors such as wind speed, solar radiation, and collector area were critical in determining system performance. To enhance the system's effectiveness, we conducted a comprehensive comparison of optimization algorithms, incorporating the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and utilizing a Pareto front for value optimization. This approach significantly outperformed other algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Simulated Annealing (SA) in terms of system efficiency and cost-effectiveness. The developed system achieved an exergy efficiency of 14.46 % and a cost rate of $74.98 per hour, demonstrating its suitability for its intended functions. Moreover, exergoenvironmental evaluation was conducted for the proposed plant. The findings revealed that key component HEX has a high exergoenvironmental factor due to their use of hot water, which has zero unit exergoenvironmental impact. Additionally, pumps demonstrated a zero exergoenvironmental impact factor, indicating negligible component-related environmental impacts. Sensitivity analysis further evaluated critical performance parameters, revealing that increases in solar irradiation lead to decreased total system cost rates, while higher turbine temperatures resulted in a remarkable 14.08 % reduction in the system's cost rate. These results underscore the economic viability of operating the system at higher temperatures and strengthen the argument for its adoption from a financial perspective.

The effect of constant electric field on the crack growth process of aluminum nanosheet using molecular dynamics simulation.

Aluminum nanosheets are a form of Al nanoparticle that have been recently manufactured on an industrial scale and have a variety of uses. Al nanoparticles are extensively used in a variety of sectors, including aerospace, construction, medical, chemistry, and marine industries. Crack propagation in various constructions must be investigated thoroughly for structural design purposes. Cracks in nanoparticles may occur during the production of nanosheets (NSs) or when different mechanical or thermal pressures were applied. In this work, the effect of a continuous electric field on the fracture formation process of aluminum nanosheets was investigated. For this study, molecular dynamics simulation and LAMMPS software were used. The effects of various electric fields on several parameters, including as stress, velocity (Velo), and fracture length, were explored, and numerical data were retrieved using software. The results show that the amplitude of the electric field parameter affected the atomic development of modeled Al nanosheets throughout the fracture operation. This effect resulted in atomic resonance (amplitude) fluctuations, which affected the mean interatomic forces and led the temporal evolution of atoms to converge to certain specified initial conditions. The crack length in our modeled samples ranged from 22.88 to 32.63 Å, depending on the electric field parameter (0.1-1 V/Å). Finally, it was determined that the crack growth of modeled Al nanosheets may be controlled using CEF parameters in real-world situations.

Investigation of mechanical behavior of porous carbon-based matrix by molecular dynamics simulation: Effects of Si doping.

Understanding the mechanical properties of porous carbon-based materials can lead to advancements in various applications, including energy storage, filtration, and lightweight structural components. Also, investigating how silicon doping affects these materials can help optimize their mechanical properties, potentially improving strength, durability, and other performance metrics. This research investigated the effects of atomic doping (Si particle up to 10 %) on the mechanical properties of the porous carbon matrix using molecular dynamics methods. Young's modulus, ultimate strength, radial distribution function, interaction energy, mean square displacement and potential energy of designed samples were reported. MD outputs predict the Si doping process improved the mechanical performance of porous structures. Numerically, Young's modulus of the C-based porous matrix increased from 234.33 GPa to 363.82 GPa by 5 % Si inserted into a pristine porous sample. Also, the ultimate strength increases from 48.54 to 115.93 GPa with increasing Si doping from 1 % to 5 %. Silicon doping enhances the bonding strength and reduces defects in the carbon matrix, leading to improved stiffness and load-bearing capacity. This results in significant increases in mechanical performance. However, excess Si may disrupt the optimal bonding network, leading to weaker connections within the matrix. Also, considering the negative value of potential energy in different doping percentages, it can be concluded that the amount of doping added up to 10 % does not disturb the initial structure and stability of the system, and the structure still has structural stability. So, we expected our introduced atomic samples to be used in actual applications.

Investigating the effect of welding tool length on mechanical strength of welded metallic matrix by molecular dynamics simulation.

The welding process and the properties of welding instruments may improve the mechanical performance of an item. One of these properties is the length of the welding tool. This approach has a substantial effect on the mechanical strength of the metallic matrix. The current study used molecular dynamics modeling and LAMMPS software to evaluate the effect of welding tool length on the mechanical properties of a welded Cu-Ag metallic matrix. This simulation makes use of the Lennard-Jones potential function and the embedded atom model. First, the equilibrium phase of modeled samples was verified by changing the computation of kinetic and total energies. Next, the mechanical properties of the welded matrix were studied using the stated Young's modulus and ultimate strength. The stress-strain curve of samples demonstrated that the mechanical strength of atomic samples increased as the length of the welding tool (penetration depth) increased. Numerically, by increasing the tool penetration depth of Fe tools from 2 Å to 8 Å, Young's modulus and ultimate strength of the matrixes sample increase from 34.360 GPa to 1390.84 MPa to 38.44 GPa and 1510 MPa, respectively. This suggested that the length of the Fe welding tool significantly affected the mechanical properties of the welded metallic matrix. The longer the length of Fe welding tools, the more particles were involved, and consequently, more bonds were formed among the particles. Bonding among the particles caused changes in mechanical properties, such as greater ultimate strength. This method can optimize mechanical structures and be useful in various industries.

A DFT study on effective detection of ClCN gas by functionalized, decorated, and doped nanocone strategies.

Density Functional Theory (DFT) was employed to investigate the interaction between cyanogen chloride (ClCN) and the surface of a carbon nanocone (CNC). The findings of this research revealed that pristine CNC is not an ideal material to detect ClCN gas due to its minimal alterations in electronic properties. In order to enhance the properties of carbon nanocones, multiple methods were implemented. These included functionalizing the nanocones with pyridinol (Pyr) and pyridinol oxide (PyrO) as well as decorating them with metals such as boron (B), aluminium (Al) and gallium (Ga). Additionally, the nanocones were also doped with the same third-group metal (B, Al and Ga). The simulation results indicated that doping it with aluminium and gallium atoms yielded promising results. After a comprehensive optimization process, two stable configurations were obtained between the ClCN gas and the CNC-Al, and CNC-Ga structures (configurations S21, and S22) with E ads values of -29.11, and -23.70 kcal mol-1 respectively, using M06-2X/6-311G(d) level. The adsorption of ClCN on CNC-Al and CNC-Ga surfaces leads to a marked alteration in the electrical properties of these structures. Calculations reveal that the energy gap between the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) levels (E g) of these configurations increased in the range of 9.03% and 12.54%, respectively, thereby giving off a chemical signal. An analysis conducted by the NCI confirms that there is a strong interaction between ClCN and Al and Ga atoms in CNC-Al and CNC-Ga structures, which is represented by the red color in the RDG isosurfaces. Additionally, the NBO charge analysis reveals that significant charge transfer is present in S21 and S22 configurations (190 and 191 |me|, respectively). These findings suggest that the adsorption of ClCN on these surfaces impacts the electron-hole interaction, which subsequently alters the electrical properties of the structures. Based on the DFT results, the CNC-Al and CNC-Ga structures, which have been doped with aluminium and gallium atoms, respectively, have the potential to serve as good candidates for detecting ClCN gas. Among these two structures, the CNC-Ga structure emerged as the most desirable one for this purpose.

Improving the efficiency of dye-sensitized solar cells based on rare-earth metal modified bismuth ferrites.

This study reports light energy harvesting characteristics of bismuth ferrite (BiFeO3) and BiFO3 doped with rare-earth metals such as neodymium (Nd), praseodymium (Pr), and gadolinium (Gd) dye solutions that were prepared by using the co-precipitation method. The structural, morphological, and optical properties of synthesized materials were studied, confirming that 5-50 nm sized synthesized particles have a well-developed and non-uniform grain size due to their amorphous nature. Moreover, the peaks of photoelectron emission for bare and doped BiFeO3 were observed in the visible region at around 490 nm, while the emission intensity of bare BiFeO3 was noticed to be lower than that of doped materials. Photoanodes were prepared with the paste of the synthesized sample and then assembled to make a solar cell. The natural and synthetic dye solutions of Mentha, Actinidia deliciosa, and green malachite, respectively, were prepared in which the photoanodes were immersed to analyze the photoconversion efficiency of the assembled dye-synthesized solar cells. The power conversion efficiency of fabricated DSSCs, which was confirmed from the I-V curve, is in the range from 0.84 to 2.15%. This study confirms that mint (Mentha) dye and Nd-doped BiFeO3 materials were found to be the most efficient sensitizer and photoanode materials among all the sensitizers and photoanodes tested.

Cetrimonium bromide and potassium thiocyanate assisted post-vapor treatment approach to enhance power conversion efficiency and stability of FAPbI3 perovskite solar cells.

Formamidinium lead iodide (FAPbI3) is the most promising perovskite material for producing efficient perovskite solar cells (PSCs). Here, we develop a facile method to obtain an α-phase FAPbI3 layer with passivated grain boundaries and weakened non-radiative recombination. For this aim, during the FAPbI3 fabrication process, cetrimonium bromide + 5% potassium thiocyanate (CTABr + 5% KSCN) vapor post-treatment is introduced to remove non-perovskite phases in the FAPbI3 layer. Incorporation of CTA+ along with SCN- ions induces FAPbI3 crystallization and stitch grain boundaries, resulting in PSCs with lower defect losses. The vapor-assisted deposition increases the carriers' lifetime in the FAPbI3 and facilitates charge transport at the interfacial perovskite/hole transport layer via a band alignment phenomenon. The treated α-FAPbI3 layers bring an excellent PCE of 22.34%, higher than the 19.48% PCE recorded for control PSCs. Besides, the well-oriented FAPbI3 and its higher hydrophobic behavior originating from CTABr materials lead to improved stability in the treated PSCs.

Correction: Unveiling concentration effects on the structural and optoelectronic characteristics of Zn1-x Cd x S (x = 0, 0.25, 0.50, 0.75, 1) cubic semiconductors: a theoretical study.

[This corrects the article DOI: 10.1039/D2RA03850A.].

An approach to removing COD and BOD based on polycarbonate mixed matrix membranes that contain hydrous manganese oxide and silver nanoparticles: A novel application of artificial neural network based simulation in MATLAB.

This study aimed to determine the efficacy of novel ultrafiltration and mixed matrix membrane (MMM) composed of hydrous manganese oxide (HMO) and silver nanoparticles (Ag-NPs) for the removal of biological oxygen demand (BOD) and chemical oxygen demand (COD). In the polycarbonate (PC) MMM, the weight percent of HMO and Ag-NP has been increased from 5% to 10%. A neural network (ANN) was used in this study to compare PC-HMO and Ag-NP. MMM was evaluated in combination with HMO and Ag-NP loadings in order to assess their effects on pure water flux, mean pore size, porosity, and efficacy in removing BOD and COD. HMO and Ag-NPs can decrease membrane porosity in the casting solution while increasing mean pore size. According to the study's findings, the artificial neural network model appears to be highly appropriate for predicting the removal of BOD and COD. To develop a successful model, a suitable input dataset was selected, which consisted of BOD and COD. An ideal model architecture for MMM was proposed based on an optimal number of hidden layers (2 layers) and neurons (5-8 neurons). Experiments and predicted data show a strong correlation between the developed models. BOD was predicted with an excellent R2 and a low root mean square error (RMSE) of 0.99 and 0.05%, respectively, while COD was predicted with an excellent R2 and a low RMSE of 0.99 and 0.09%, respectively. Based on the results, Ag-NP was found to be an excellent candidate for the preparation of MMMs as well as convenient for the removal of BOD and COD from polluted water sources.

Synthesis and Characterization of Polyvinyl Chloride Matrix Composites with Modified Scrap Iron for Advanced Electronic, Photonic, and Optical Systems.

In this study, Fe2O3 powder was synthesized using the co-precipitation method from scrap iron, which was then treated with varying concentrations of copper. Afterwards, the modified Fe2O3 was reinforced in the PVC matrix by using the solution-casting method to synthesize PVC composite films, which were subjected to a UV-visible spectrophotometer, a Fourier transform infrared spectrophotometer, an X-ray diffractometer, and a thermal gravimetric analyzer to evaluate the optical, chemical, structural, and thermal properties. FTIR analysis reveals the formation of the composite through vibrational bands pertaining to both components present, whereas no significant changes in the XRD patterns of PVC were observed after the doping of modified iron oxide, which reveals the compatibility of fillers with the PVC matrix. The optical properties of the copper-doped iron oxide-PVC composites, including absorbance, refractive index, urbach energy, and optical as well as electrical conductivity are measured, and show an increase in optical activity when compared to the pure PVC compound. Moreover, the increased thermal stability of the synthesized composite was also observed and compared with conventional compounds, which, in accordance with all the other mentioned properties, makes the copper-dopped iron oxide-PVC composite an effective material for electronic, photonic, and optical device applications.

Unveiling concentration effects on the structural and optoelectronic characteristics of Zn1-x Cd x S (x = 0, 0.25, 0.50, 0.75, 1) cubic semiconductors: a theoretical study.

The structural and optoelectronic characteristics of Zn1-x Cd x S (x = 0, 0.25, 0.50, 0.75, 1) semiconductors are reported using density functional theory within GGA, EV-GGA, and mBJ functionals. These semiconductors are observed in cubic symmetry at all Cd-concentrations and the lattice constant increases linearly with Cd-concentration while the bulk modulus shows a reverse behavior. These materials are direct bandgap semiconductors at all Cd-concentrations and their bandgap energy decreases from 3.67 eV to 2.59 eV. The isotropic optical properties of these direct bandgap semiconductors vary with Cd concentration as well, with absorption coefficients decreasing and absorbed near-UV light converting to visible blue light. Optical properties like refractive index, dielectric constant, conductivity, extinction coefficient, and reflectance are also displayed and discussed. These results provide useful theoretical understanding for the application of CdZnS semiconductors in photonic, photovoltaic, and optoelectronic devices.

Experimental Investigation and Numerical Simulation for Corrosion Rate of Amorphous/Nano-Crystalline Coating Influenced by Temperatures.

A high-velocity oxygen fuel (HVOF) system was employed to prepare a Fe49.7Cr18Mn1.9Mo7.4W1.6B15.2C3.8Si2.4 amorphous coating on mild steel. The electrochemical behavior of the resultant coatings, namely as-sprayed coating and vacuum heat-treated coating (at 650 °C and 800 °C), were investigated in a 3.5% NaCl solution at variable temperatures using scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, optical microscopy (OM), and XRD diffraction. Moreover, COMSOL Multiphysics version 5.5 software were employed for predicting the galvanic corrosion of amorphous material immersed in an aqueous NaCl solution, using the software finite element kit. The experiments demonstrated that the coatings' pitting resistance was significantly affected by temperature. The results also showed that temperature affected the pitting corrosion rate and changed the shape of the pits. However, the changes were not as extreme as those observed in stainless steel. Furthermore, there was no significant difference between the as-sprayed coating and the vacuum-heat-treated coating at 650 °C. At low NaCl concentrations at and temperatures below the critical pitting temperature, the resulting pits were significantly small with a hemisphere-like. By contrast, at a higher NaCl concentration at 70 °C, particularly in the case of heating at 650 °C, the pits appearing on the Fe-based amorphous coating were vast and sometimes featured a lacy cover.