Mortar-aggregate interface is the weakest region in concrete in terms of the mechanical properties due to its relatively higher porosity compared with the surrounding bulk cement paste, which has a significant effect on the behavior of concrete when subjected to loading. As a result, the mechanical properties of the interface have been recognized as the principal condition for the meso-scale numerical modeling of the fracture process of concrete and concrete structures. In this study, the composite mortar-aggregate specimens with different surface roughness of aggregate and mortar strength were prepared to quantitatively investigate the mechanical properties of interface by means of a series of tests, including the splitting tensile test, the direct shear test and the three-point bending test. The test results indicated that the mechanical properties of interface to some extent depend on the strength grade of mortar and the roughness of aggregate surface. The failure mode largely depends on the fracture energy of mortar cohesion layer and the joint adhesion layer. It is also found that the fracture energy of interface increases with the increase of mortar strength and the roughness of aggregate surface. With purpose of providing basic constitutive model for meso-scale numerical simulation of concrete behavior, the tension softening curves of mortar-aggregate interface for different mortar strength grade were developed based on the test results. Finally, with the proposed constitutive model of interface on meso-scale, the response of plain concrete under loading were conducted using the Rigid Body Spring Model (RBSM). The numerical simulation results indicated that the expressions of tension softening curves were valid and can be successfully applied to the numerical analysis of concrete structures.
Titanium, stainless steel, and cobalt-chromium-based alloys represent the most widely used metallic biomaterials and high-performance structural materials owing to their outstanding corrosion resistance, mechanical properties, biocompatibility, and strength-to-weight ratio. This review provides a comprehensive classification of these alloys based on chemical composition and thermomechanical processing. Titanium alloys are categorized into α, near-α, α+β, metastable β, and stable β types; stainless steels into austenitic, ferritic, martensitic, duplex, and precipitation-hardened grades; while cobalt-chromium alloys are differentiated into cast (e.g., F75) and forged (e.g., F799) variants. The microstructure property relationships, influence of key alloying elements, and the effects of cold rolling and deformation processing on strength, fatigue resistance, and corrosion behavior are critically examined. Particular emphasis is placed on their diverse applications in the aerospace industry (airframe structures, jet engines, fasteners, and spacecraft components) and biomedical fields (orthopedic implants, cardiovascular devices, dental prosthetics, and trauma fixation devices). Advantages, limitations, biocompatibility issues (such as stress shielding and ion release), and recent advancements in surface modification techniques are discussed. Finally, future directions including the development of low-modulus β-titanium alloys, nickel-free stainless steels, improved Co-Cr alloys, and advanced additive manufacturing routes are outlined to address current challenges and meet the evolving demands of high-performance engineering and long-term biomedical applications.
Chabazite is a microporous material widely studied due to its applications in heterogeneous catalysis. In this study, the authors synthesized a zeolite by the hydrothermal method at 125°C using tetrapropylammonium bromide as an organic template, which was removed by calcination at 800°C. The characterization of the synthesized product was carried out by X-ray diffraction, Fourier transform infrared spectroscopy, X-ray fluorescence, scanning electron microscopy coupled with energy-dispersive spectroscopy. X-ray diffraction showed the presence of a crystalline phase consisting of chabazite crystallizing in the rhombohedral lattice with lattice parameters a = 9.4250 Å and α = 94.060°. Fourier transform infrared spectroscopy revealed absorption bands located between 400 – 1000 cm -1 , characteristic of zeolites. X-ray fluorescence highlighted the aluminosilicate nature with a Si/Al ratio of 4.5 for the synthesized product. The SEM coupled with EDS revealed the uniformity of the product, a hexagonal morphology or the symmetrical facets characteristic of rhombohedral symmetry. The protonated form of the synthesized zeolite, obtained by ion exchange, was used as a catalyst for the synthesis of isoamyl acetate with a yield of the impure product of 79.03%; this yield being close to the same product obtained (84.76%) from the same reaction catalyzed by sulfuric acid. The UV-visible spectral data validated the synthesis products.
This study investigates the geotechnical and mineralogical properties of iron ore tailings (IOT) samples—comprised of feed, hydrocyclone overflow, and underflow streams—collected from the Marampa Mines Limited (MML) Tailings Storage Facility (TSF). The primary objective was to quantify how hydrocyclone classification fundamentally alters the physical and mechanical behavior of segregated tailings for structural applications. Laboratory investigations, conducted in accordance with ASTM standards, included specific gravity, particle size distribution, Atterberg limits, one-dimensional consolidation, and consolidated-drained (CD) triaxial shear strength tests. Results demonstrate highly effective material segregation; the underflow was classified as Silty Sand (SM) with a significantly higher specific gravity (Avg. 3.26) compared to the finer, flaky particles in the overflow (Avg. 2.97). All samples were determined to be non-plastic. Mechanical testing indicated that the underflow achieved a superior maximum dry density (1990 kg/m³) and an enhanced effective angle of internal friction (ϴ’) of 38°, suggesting significantly higher shear strength for embankment construction. X-ray Fluorescence (XRF) analysis confirmed that iron (Fe) concentration was highest in the underflow (38.711%), while silicon dioxide (SiO2) dominated the overflow (50.047%), correlating mineral density with geotechnical performance. While stable under compacted conditions, the non-plastic nature of these materials necessitates strict drainage management to mitigate potential stability loss upon saturation. These findings provide critical baseline parameters for the design and safety assessment of modern IOT storage facilities.
This study is part of a circular economy approach aimed at valorizing polyethylene terephthalate (PET) waste in cementitious matrices through a materials science and engineering approach. PET waste from used containers underwent a controlled thermomechanical transformation (melting at 260°C, cooling, grinding, and sieving), yielding two distinct fractions: plastic aggregates (> 5 mm) and a fine powder. These two forms were incorporated into hydraulic concrete using two formulation strategies: (i) partial substitution of natural gravel with PET aggregates and (ii) partial substitution of sand with PET powder, at rates ranging from 0 to 18% by mass. The concrete's performance was evaluated after 7 days by measuring uniaxial compressive strength and water absorption capacity. The results show that the morphology and incorporation rate of PET significantly influence the concrete's properties. Substituting gravel with PET aggregates leads to a progressive decrease in mechanical strength and, at high concentrations, an increase in water absorption. Conversely, substituting sand with PET powder exhibits more favorable behavior at low concentrations (≤ 6–8%), characterized by a densification effect on the cementitious matrix. An optimal range of 5 to 8% PET powder is thus identified for non-structural hydraulic concrete applications.
Graphene, a two-dimensional carbon nanomaterial composed of single-layer carbon atoms forming a hexagonal honeycomb lattice via sp 2 hybridisation, has attracted extensive worldwide attention since its discovery in 2004. Benefiting from its distinctive atomic structure, graphene exhibits extraordinary physical and chemical properties, such as ultra-high electron mobility, excellent mechanical strength, superior thermal conductivity, and large specific surface area. Nevertheless, the inherent chemical inertness and unsatisfactory dispersibility of pristine graphene severely restrict its practical applications in various fields. Accordingly, the modification of graphene has become a key research direction to address these limitations. This paper systematically reviews the recent research progress of graphene and its modification strategies, mainly including covalent functionalisation, non-covalent functionalisation, and elemental doping. The application advances of modified graphene in energy storage, sensors, composite materials and other high-tech fields are comprehensively summarised. In addition, the existing challenges including mass production, quality stability and cost control, as well as future development trends, are prospected. Studies demonstrate that optimised modification design can effectively improve the performance of graphene-based materials, which hold great promise for wide applications in multidisciplinary areas.
Copper indium gallium selenide (CIGS) solar cells are among the most efficient thin-film photovoltaic technologies due to their high absorption coefficient, long-term stability, and bandgap tunability. However, the conventional CIGS/CdS structure raises environmental and regulatory concerns associated with cadmium toxicity, driving the development of fully Cd-free device architectures. In this context, zinc selenide (ZnSe) is a promising alternative buffer layer owing to its wide bandgap, high transparency, and favorable band alignment with CIGS. This work numerically investigates the combined influence of ZnSe buffer-layer thickness and doping concentration on the electrical performance of CIGS solar cells using the ATLAS-SILVACO TCAD simulator. The key photovoltaic parameters examined include the short-circuit current density (JSC), the open-circuit voltage (VOC), the fill factor (FF), and the power conversion efficiency (η). The results show that ZnSe thickness has a limited impact on VOC but significantly affects JSC, FF, and η. Very thin layers exhibit higher interfacial recombination and incomplete junction formation, whereas an optimal thickness between 0.08 and 0.10 µm ensures improved carrier transport, reduced losses, and superior efficiency. Doping concentration also plays a determining role. Although JSC and VOC remain only weakly sensitive to doping, the FF and η degrade markedly at high doping levels due to increased defect density, reduced carrier mobility, and enhanced nonradiative recombination. The optimal doping range is found to be 8×1016 to 2×1017 cm-3. Overall, the study provides clear guidelines for optimizing ZnSe-based buffer layers and demonstrates the importance of jointly controlling thickness and doping to design high-performance, environmentally compliant Cd-free CIGS solar cells. These results also offer a robust numerical foundation for future experimental validation and further device optimization.
In this article we measure the steady mass for our samples polyvinyl chloride and polyethylene. The constant mass is achieved when the acrylic box is used to shield the precision mass balance. The mass of our sample 1 polyvinyl chloride is 160 mg. Our sample 1 polyvinyl chloride is thin film of length 5.5 mm, width 7 mm and thickness 3.2 mm. The density of the polyvinyl chloride is 1300 kg/m3 in agreement with the literature. The stream flow is blocked when the acrylic shield is used. We observe fluctuations in the mass from 320 mg to 560 mg when there is no acrylic shield. The mass of our sample 2 polyethylene is 120 mg and the density is 893 kg/m3 with the acrylic shield. The mass of the polyethylene membrane material fluctuates from 60 mg to 350 mg without the acrylic shield. The geometry of our sample 2 polyethylene is length 14 mm, width 12 mm and thickness 0.8 mm. Further we build pixel computer aided design (CAD) model to correlate with the chemical elements in the periodic table towards exact match with the optical camera image of our two samples that are polyvinyl chloride and polyethylene. Furthermore we build the model to exact match to the scanning electron microscopy (SEM) in micrometer and nanometer resolution to both samples. The chemical periodic table elements are obtained from energy dispersive spectroscopy (EDS). The study of membrane materials can find applications towards energy and thermal management coolants.
Graphene/hexagonal boron nitride heterostructures provides an effective platform for tuning graphene’s electronic and optical properties while preserving its inherently high carrier mobility. In this work, the effect of post-growth thermal annealing on the optical band gap of G/h-BN heterostructures is investigated to examine temperature-dependent modifications at the graphene–substrate interface. The optical response of the annealed heterostructures was characterized using UV–Vis spectroscopy over the spectral range of 200–800 nm. The absorption spectra reveal a systematic red shift of the absorption edge with increasing annealing temperature, indicating a progressive modification of the electronic structure. Tauc method was used in the approximation of the optical band gap where a reduction of the optical band gap from 2.86 eV for the lower annealing temperature to 2.17 eV at the highest annealing temperature was observed. This act is associated to thermally induced interfacial relaxation, including changes in stacking configuration, and moirés super lattice formation. These processes lead to a reduction in substrate-induced symmetry breaking in graphene, thereby influencing its optical transitions. The findings contribute to a better understanding of temperature-driven interfacial effects in van der Waals heterostructures and provide insights relevant to the development of graphene-based optoelectronic and thermoelectric devices designed to operate under varying thermal conditions.
The paint industry's reliance on synthetic petroleum-based binders raises environmental concerns due to volatile organic compound (VOC) emissions and non-renewable resource depletion. This study investigates the feasibility of using Acacia senegal (Gum Arabic), a natural renewable binder, either alone or in combination with polyvinyl acetate (PVAc) for satin house paint production. Three paint formulations were prepared with varying binder compositions: 100% PVAc (Sample A), 100% Gum Arabic (Sample B), and 50% PVAc + 50% Gum Arabic (Sample C). Physicochemical properties including pH, drying time, coverage, and viscosity were evaluated. Results showed that all samples exhibited pH values slightly above the Standards Organization of Nigeria (SON) range (8.63-8.75 vs. 7.0-8.5). Drying time varied significantly: Sample B dried fastest (2 hours), followed by Sample C (2 hours 45 minutes), and Sample A slowest (3 hours 45 minutes). All samples achieved equivalent coverage (0.0136 m2), though brightness quality differed (Sample A: excellent, Sample B: dull, Sample C: good). The hybrid formulation (Sample C) demonstrated promising preliminary characteristics, suggesting that partial substitution of synthetic PVAc with natural Gum Arabic warrants further investigation for satin paint applications. While basic physicochemical properties were characterized, comprehensive performance testing including adhesion, scrub resistance, and quantitative gloss measurement is required to fully validate commercial viability. This research contributes to sustainable paint technology by demonstrating the viability of bio-based binders in decorative coatings.
The Romelt process is called liquid-phase smelting reduction process because in the metallurgical processes the reaction of coal and iron occurs in the liquid slag layer, which is boiling vigorously by oxygen-enriched air flow blown into the liquid slag. The bath of the furnace is charged with coal and iron ore, and an oxygen nozzle for secondary combustion is installed on both sides of the bath cavity to burn out the CO and H2 gases generated in the bath. CO and H2, rising from the boiling slag bath, are completely burned by oxygen blown into the secondary nozzle in the combustion chamber. The heat from this combustion reaction plays an important role in the Romelt process. 60-80% of the secondary combustion heat is transferred to the bath and becomes the heat source of the main process. At present, the Romelt process has a high CO content in the exhaust gas due to the low efficiency of combustion by oxygen blown into secondary nozzle and low oxidation of CO. This paper analyses the reason of the low efficiency of combustion by oxygen blown into conventional secondary nozzle using CFD, and based on it, suggests the blasting method to increase the secondary combustion efficiency by oxygen blown into the upper tuyere of the Romelt furnace. To improve the secondary combustion efficiency, a new type of catalyst for enhancing the oxidation of CO was investigated and more than 90% of efficiency of secondary combustion was achieved. At this time, oxygen concentration should be at least 95%.
It is difficult to achieve dry and precise classification for fine sand characterized by small particle size, high content of micro-powder, and unstable gradation. In this study, a rectangle swing screen assisted by airflow & ultrasonic was employed to achieve precise classification of fine tailings. Through detailed process calculations and sample analysis, the following conclusions can be drawn: The movement trajectory of the fine sand within the rectangle swing screen follows a 360° parabolic path. The current theoretical formula for calculating the resistance coefficient of the transitional flow field within the airflow-assisted rectangle swing screen should be revised. After pre-dried, the magnetic tailings, vanadium-titanium magnetic tailings and molybdenum tailings were precise classified by the new multi-field coupled classifiers. The new classifiers enables the production of products with a mixed-grade rate of less than 5%. The classification efficiency is influenced by the inclination angle of the screen, the length of the sieve, the air velocity, the ultrasonic amplitude & etc., and parameters can be reasonably set according to engineering requirements. Furthermore, the prepared products have been successfully applied in the production of dry-mixed mortar and can be manufactured on a batch scale. The dry-mixed mortar containing tailings has been applied in urban renewal projects and has achieved good results.
Metal-based complexes have attracted considerable attention due to their diverse biological activities and potential applications as antimicrobial agents. In this study, a series of previously synthesized metal complexes of Molybdenum(VI), Uranium(VI), Zirconium(IV), and Thorium(IV) were systematically evaluated to investigate their antifungal, antibacterial, and cytotoxic properties. The primary objective of this work was to assess the bioactive potential of these complexes and to identify promising candidates for antimicrobial applications. The antifungal activity of the complexes was examined against Aspergillus niger, A. fumigatus, and A. flavus using the agar diffusion method. Antibacterial efficacy was determined by minimum inhibitory concentration (MIC) assays against both Gram-negative (Pseudomonas aeruginosa and Escherichia coli) and Gram-positive (Streptococcus β-haemolyticus and Bacillus subtilis) bacterial strains. Cytotoxicity was evaluated using the brine shrimp lethality assay as a preliminary indicator of biological safety. The results demonstrated that all tested complexes exhibited varying degrees of antifungal and antibacterial activity. Notably, the Mo(VI) complex 2 showed the highest antifungal activity against A. flavus, producing a zone of inhibition of 14 mm. In antibacterial studies, Mo(VI) complex 4 displayed the lowest MIC values, indicating superior antibacterial potency, followed by the U(VI) complex 8, while Th(IV) complexes showed comparatively weaker activity. Cytotoxicity assessment revealed that Mo(VI) complex 5 exhibited the highest toxicity, whereas complexes 1 and 2 were comparatively less toxic. Overall, the findings suggest that Mo(VI) complexes possess significant antimicrobial potential and represent promising candidates for further development as bioactive agents.
The rapid advancement of nanotechnology has enabled the development of materials with unique properties that differ significantly from their bulk counterparts. Understanding and predicting the properties of nanomaterials, such as their electronic, optical, and mechanical characteristics, is crucial for their application in fields like electronics, energy storage, and catalysis. However, the computational methods used to predict these properties, particularly through quantum mechanical simulations such as Density Functional Theory (DFT), are computationally expensive and time-consuming, especially when applied to large datasets of nanomaterials. This paper proposes a novel approach that integrates machine learning (ML) techniques with DFT simulations to predict the structural and optical properties of nanomaterials. By utilizing a dataset derived from DFT calculations, we train and evaluate multiple machine learning models, including Random Forest, Support Vector Machine (SVM), and Deep Neural Networks (DNN), to predict key properties such as band gap, conductivity, and optical absorption. The goal is to develop a model that reduces the computational burden of traditional simulation methods while maintaining high accuracy and generalizability. The models were trained on a synthetic dataset that simulates the composition, size, and crystal structure of nanomaterials, with target properties generated based on these features. We evaluated the performance of the models using standard regression metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and R2. Results show that the DNN model provides the best predictive accuracy, closely followed by the Random Forest model, while the SVM model demonstrated lower performance in this context. Additionally, feature importance analysis revealed that material composition, particle size, and crystal structure were the most influential factors in determining the predicted properties of the nanomaterials. This research demonstrates the potential of machine learning to accelerate the discovery of new nanomaterials by providing a fast and scalable way to predict their properties. By combining the predictive power of ML with quantum mechanical simulations, this study offers an efficient framework for material discovery that can be applied to a wide range of nanomaterial systems.
Germanium-based perovskite solar cells have garnered significant interest within the scientific community due to their non-toxicity and excellent stability. However, their low conversion efficiency is an obstacle to their application and design. We designed a device with a normal configuration structured as Glass / FTO / SnO2 / IDL1 / CsGeI3 / IDL2 / Cu2O / Au to improve our germanium-based perovskite solar cell, designed The integration of interface defect layers IDL1 and IDL2 the reduction of recombination. The study revealed that these IDL1 and IDL2 layers play a crucial role in solar conversion performance. By adjusting the thickness, electron affinity and defect density of the IDL1 and IDL2 layers, the conversion efficiency of our device exceeds 19%. However, an increase in temperature in the environment can negatively affect the cell by decreasing its photovoltaic efficiency.
This study focuses on determining the thermomechanical properties of clay extracted from the Kangartoulo brickyard site in Massakory, reinforced with seyal gum arabic for sustainable development construction applications. Raw earth has been used and is used in the construction field for its abundance and low environmental impact. The experimental results of thermal tests show that a decrease in thermal conductivity and thermal effusivity is observed for a gum arabic content below 4%, followed by a slight increase beyond this threshold and also by varying the compaction pressure from 3 to 6 MPa. Regarding mechanical properties, the simple compressive strength almost tripled with the addition of gum arabic from 0 to 8%, it increased from 3.2 to 9.4 MPa for compaction pressures ranging from 3 to 6 MPa. The three-point bending strength has also been improved, increasing from 0.78 to 2.10 MPa for the same binder contents. The numerical simulation carried out with the RETScreen software made it possible to estimate an energy gain of 29% for the optimal formulation retained compared to cementitious materials.
This study reports the synthesis and characterization of ZnO-based nanocomposite thin films prepared by the sol-gel method associated with spin coating technique, with incorporation of silver (Ag), titanuim oxide (TiO2), and graphene nanoparticles as functional additive. The aim of this work is to investigate the influence of these nanoinclusions on the structural, optical, and electrical properties of ZnO thin films. X-ray diffraction (XRD) results confirm the retention of the hexagonal wurtzite structure of ZnO, with additional reflections at 38,1°, 44,3°, and 64,4° attributed to Ag, 25,3° and 48 ° to anatase TiO2, and a broad peak near 26° to GO. Scanning Electron Microscopy (SEM) analyse reveals enhanced grain connectivity and surface uniformity in composite films. UV-Vis spectroscopy indicates a tunable optical bandgap and improved transmittance in the visible range, especially for TiO2 and graphene-loaded films. Electrical measurements show a significant decrease in resistivity from 4,5*103 Ω.cm (ZnO) to 3,2*102 Ω.cm (ZnO-Ag), 1,7*102 Ω.cm in the ternary composite, with corresponding conductivity up to 5,9*10-3 S/cm and carrier mobility of 7,6 cm2/V.s in Ag and graphene-containing films, attributed to improved charge carrier mobility and percolation pathways. The multifunctional enhancement observed in these ZnO nanocomposites positions them as promising materials for transparent electrodes, photocatalytic devices, and UV photodetectors.
Printing on polymer clothing are textile industry major requirement. Woven label print machines are used in this study. Printing obtained on polymer substrate should be accessible and cost effective method. Design from free hand sketch in app and Computer Aided Design (CAD) direct use in polymer print machines are studied. The integration of polymer, clothing, paper analytical devices, stick paper devices, digital, electronic equipments, apps and surface characterization machines that are surface profilometer are needed. In this paper we develop woven label printing on the polymer. We draw using app. The design is printed on paper, stick paper and polymer. We have to perform scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) on the paper and stick paper. In this study we use the woven label machines. We print 100 prints on the woven label. We study the surface characteristics of the printed design on the cloth/polymer using surface profilometer. We obtain the vertical height features. Here we consider six random regions on the polymer that has the print. We understand from the surface characterization the polymer print features are coil. The vertical heights of the coils in various regions does vary from 50 µm to 400 µm. The details of the polymer need further study. We have to perform scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS) on the cloth with and without woven label print on the polymer cloth. The key results need numerical formula for the polymer. That is scope for the future. The details of the woven label equipment are needed for the development and progress of the methodology. There is research gap in this section. Here, we provide the shop details of the woven label equipment. The woven label printer prints at once 2000 to 10,000 same prints on each cloth. The cloth is square shape. The details of the printed woven label are given. We have to input the designs of our free hand sketch, apps and CAD. The printing is safe handling and cost effective. This is the novelty of the printer. We have placed the woven label image printed on the cloth on another substrate cloth. We repeat the study varying the number of woven label cloth from 1 to 100. The print on polymer from software can find applications for color drawings to print, sensors and digital polymer electronics applications.
The impregnation of wood in fiber cement boards aims to replace traditional ceiling boards, which are prone to moisture damage over time. This study explores a modified hornification process involving fiber treatment with a solution of hexamine and gallic acid (H/G method) compared to a conventional hornification method (H method), where fibers are soaked in tap water. The objective is to evaluate the influence of this modified process on the morphological, physicochemical, and mechanical properties of Urena lobata (UL) bast fibers from the Littoral region of Cameroon. The fibers underwent four wet-dry treatment cycles using both the H/G and H methods. Results revealed significant reductions in water and moisture absorption compared to untreated (UT) fibers. Water absorption decreased from 227.79±0.05% (UT) to 200.34±0.05% (H) and 130.37±0.03% (H/G), while moisture absorption reduced from 9.286% (UT) to 7.03% (H) and 5.854% (H/G). Additionally, an increase in fiber density was observed, rising from 1.72±0.012 g/cm³ (UT) to 1.78±0.012 g/cm³ (H) and 1.87±0.04 g/cm³ (H/G), attributed to the infiltration of hexamine and gallic acid into the fiber cells. Mechanical performance was assessed through flexural and compressive tests after 7, 14, and 28 days of curing. Both elastic modulus and compressive strength improved progressively from untreated fibers through the H method to the H/G method, with increases of 20% and 30%, respectively. These findings demonstrate that the hexamine and gallic acid treatment enhances the effectiveness of the hornification process, significantly improving the water resistance and mechanical performance of the treated fibers.
This three-dimensional numerical study investigates the combined effects of magnetic fields, carrier collection velocity at the p-n junction, and base thickness on the photogenerated current density in bifacial polycrystalline silicon solar cells. The model uses a columnar geometry centered on a single grain with front, rear, or dual-side illumination, representing realistic configurations of modern photovoltaic systems. The results demonstrate that the applied magnetic field reduces carrier mobility, degrading transport properties by lowering both the diffusion coefficient and diffusion length, which impacts the overall efficiency of the solar cell. Carrier collection velocity plays a crucial role as a key parameter, determining the transition between open-circuit (zero current) and short-circuit (maximum current) operating modes, and is highly sensitive to changes in the cell structure. Additionally, the base thickness significantly influences carrier collection efficiency: thinner bases show better performance under magnetic field conditions, as they reduce the path length for carrier diffusion. Bifacial illumination enhances the overall photocurrent by utilizing both the front and rear surfaces of the cell, but remains sensitive to the combined effects of magnetic fields, recombination, and geometry. This study provides valuable insights into how the physical configuration of solar cells can be optimized, suggesting that adjusting the base thickness and controlling recombination mechanisms can significantly improve the performance of photovoltaic systems in environments disturbed by magnetic fields or other external factors. The findings are relevant for designing more efficient bifacial solar cells in real-world applications.
