Eng, Volume 6, Issue 2 (February 2025) – 8 articles

In recent years, there has been significant investigation into the high efficiency of perovskite solar cells. These cells have the capacity to attain efficiencies above 14%. As the perovskite materials that include lead pose a substantial environmental risk, components that are free from lead are used during the process of solar cell development. In this work, we use a lead-free double-perovskite material, namely Cs₂TiBr₆, as the main absorbing layer in perovskite solar cells to enhance power conversion efficiency (PCE). This work is centered on the development of solar cell structures with materials such as an ETL (electron transport layer) and an HTL (hole transport layer) to enhance the PCE. In this theoretical work, we perform simulations and analysis on double-perovskite Cs₂TiBr₆ to assess its efficacy as an absorber material in various HTLs like Cu₂O and CuI, with a fixed ETL of C60 using SCAPS (Solar Cell Capacitance Simulator, SCAPS 3.3.10) Software. This is a one-dimensional solar cell simulation program. In this work, the thickness of the double-perovskite material is also varied between 0.2 and 2.0 µm, and its efficiency is observed. The effect of temperature variation on efficiency in the range of 300 K to 350 K is observed. The effect of defect density on efficiency is also observed in the range of 1 × 10¹¹ to 1 × 10¹⁶. In this theoretical work, perovskite solar cells, including their absorbing layer, demonstrate outstanding ETLs and HTLs, respectively. As a result, the cells’ achieved PCE is improved. This work demonstrates the effectiveness of this lead-free double-perovskite structure that absorbs light in perovskite solar cells. Full article

Increasing the process efficiency of agricultural tasks is a key measure to decrease overall costs and CO₂ emissions. However, optimizing tractor–implement combinations is challenging due to the variety of processes and implements and the complexity of the powertrains in modern tractors. In addition, overall process efficiency is an ambiguous optimization objective in agricultural processes as it relates resource consumption to harvest yields, which are only known at the end of a harvest season. The presented approach defines process constraints, ensuring optimization does not negatively affect harvest yield. These constraints allow for the formulation of explicit objective functions that are observable during the operation. The method establishes a mathematical foundation for the optimization of agricultural processes. The mathematical principles of the theoretical framework and the techniques used to define control constraints are explored, whereby the applicability to alternative objectives like optimizing the overall process cost is highlighted. To demonstrate the practical utility of the proposed approach, an optimization cycle is applied to a real-world scenario: adapting the working speed during the tillage process using a cultivator to maximize energy efficiency. The approach simplifies the optimization problem by formulation as a constraint optimization problem, allowing for improving the operating point of tractor–implement combinations with respect to observable process objective functions. The results underline the importance of advanced control strategies in agricultural machinery, advancing precision agriculture and promoting sustainable farming practices. Full article

Research on the effects of magnetic fields on water and aqueous solutions has produced various findings, such as the suppression of scale formation in pipes and boilers, inhibition of metal corrosion, enhancement of concrete strength, and changes in properties like viscosity and electrical conductivity. However, the challenges in quantifying these effects, the issues with reproducibility affected by trace elements in the water used in the experiments, and the involvement of complex parameters and mechanisms have led to ongoing debates, with some questioning the very existence of magnetic field effects. The “memory effect”, where the impact of magnetic exposure persists for a certain period, further complicates explanations of these phenomena. To fully elucidate and enable practical applications of these effects, further research is essential. In this study, we aimed to investigate the magnetic field effects on water, including memory effects, where the quantification and elucidation potentially lead to various applications, including environmentally friendly solutions on scale suppression and life science issues. The results revealed that the vaterite phase precipitation ratio significantly increased in magnetically treated water, reaching up to 51%, from 26% without the treatment, which is high reproducibility; furthermore, a reduction in mean particle size was observed when using magnetically treated water, suggesting that it may help prevent scaling. Furthermore, when solutions of calcium carbonate, calcium chloride, and sodium bicarbonate were individually subjected to magnetic treatment, the most notable increase in the vaterite phase precipitation ratio was observed when calcium chloride and sodium bicarbonate solutions were magnetically treated separately and then reacted to precipitate calcium carbonate. Full article

The development of urban areas has led to an increase in the use of subsoil for installing transportation networks. These systems usually comprise the construction of side-by-side twin running tunnels built sequentially and in close proximity. Different studies have demonstrated that under such conditions, there is an interaction between tunnels, leading to greater settlements compared with those obtained if the tunnels were excavated separately. Supported by those findings, several analytical methods have been proposed to predict the settlements induced by the excavation of the second tunnel. This paper examines the applicability of these proposals across multiple case studies published in the literature by comparing the analytical predictions with the reported monitoring data of 57 sections. The results indicate that, regardless of the different soil conditions and geometrical characteristics of the tunnels, a Gaussian curve accurately describes the settlements in greenfield conditions and those induced by the second tunnel excavation, although with the curve becoming eccentric in this case. Despite some significant scatter observed, most methods predict the settlements induced by the second tunnel with reasonable accuracy, with Hunt’s method presenting the best fit metrics. The obtained findings confirm that existent methods can be a valid tool to predict the settlements induced by twin tunnelling during the early stages of design, although do also contain limitations and pitfalls that are identified and discussed throughout the paper. Full article

This note aims for a non-local extension of the Johnson–Mehl–Avrami–Kolmogorov (JMAK) kinetic equation, describing solid phase transformation through the implementation of the time-fractional Caputo derivative and Mittag-Leffler function instead of the exponential Avrami kinetics. These are preliminary results that include tests on some published data and a clarification of the concept. Full article

Aluminum 7075 alloys are widely utilized in aerospace, transportation, and marine industries due to their high strength and low density. However, further research is needed to understand their mechanical, thermomechanical, and vibrational behaviors when reinforced. This study focuses on the development of Al 7075 composites reinforced with zirconium silicate (ZrSiO₄), processed via sand stir casting. The mechanical properties, including tensile, compression, and impact strength, as well as thermomechanical and vibrational behaviors, were thoroughly investigated. A planetary ball mill was used to mix ZrSiO₄ with a wettability agent, and the results indicated that the addition of ZrSiO₄ with the wettability agent significantly enhanced the mechanical properties. Fourier Transform Infrared Spectroscopy (FTIR) was employed to identify the compounds formed after adding the reinforcement and wettability agent. Scanning Electron Microscope (SEM) images and Energy-dispersive X-ray (EDX) analysis revealed a uniform distribution of the particles within the matrix. The tensile, compression, and impact strengths increased by 20%, 21%, and 19%, respectively, with the addition of 8 wt% ZrSiO₄; however, strain decreased. Additionally, heat treatment further enhanced the mechanical properties of the composites. The thermomechanical properties showed improvement even at elevated temperatures, and the damping factor was enhanced with the addition of ZrSiO₄. The elemental composition of the reinforced composites was analyzed using EDX, confirming the presence of the reinforcement. This research highlights the potential of Al 7075-ZrSiO₄ composites for improved performance in various applications. Full article

The rising demand for housing continues to outpace traditional construction processes, highlighting the need for innovative, efficient, and sustainable delivery models. Off-site construction (OSC) has emerged as a promising alternative, offering faster project timelines and enhanced cost management. However, current research on cost models for OSC, particularly in automating material take-offs and optimising cost performance, remains limited. This study addresses this gap by proposing a new cost model integrating Digital Twin (DT) technology and AI-driven decision models for modular housing in the UK. The research explores the role of DTs in enhancing cost estimation and decision-making processes. By leveraging DTs and AI, the proposed model evaluates the impact of emergent technologies on cost performance, material efficiency, and sustainability across social, environmental, and economic dimensions. As proposed, this integrated approach enables a cost model tailored for OSC systems, providing a data-driven foundation for cost optimisation and material take-offs. The study’s findings highlight the potential of combining DTs and AI decision models to enhance cost modelling in modular construction, offering new capabilities to support sustainable and performance-driven housing delivery. The paper introduces a dynamic, data-driven cost model integrating real-time data acquisition through DTs and AI-powered predictive analytics. This dynamic approach enhances cost accuracy, reduces lifecycle cost variability, and supports adaptive decision-making throughout the OSC project lifecycle. Full article

Green synthesis of nanocomposites offers an eco-friendly and viable solution to overcome the limitations of conventional chemical and physical methods as it uses biological agents to act as reducing and stabilizing agents. The current study’s novelty is phyto-fabricated manganese (Mn)-doped zinc oxide (ZnO) nanocomposites using aqueous extract of H. enneaspermus by a biological method. Mn-doped ZnO nanocomposites were synthesized using manganese acetate and zinc acetate. The synthesized nanocomposites were characterized by XRD, FTIR, SEM, and EDX analysis. XRD shows the crystalline nature of nanocomposites with particle sizes of 30–40 nm, and FTIR reveals the presence of functional groups responsible for capping and stabilization. SEM analysis indicates spherical morphology with minor aggregation due to phytochemical interactions. EDX analysis of Mn-doped ZnO nanocomposites was used to verify the elemental composition, including Mn, Zn, O, and C. The anti-bacterial property of Mn-doped ZnO nanocomposites was assessed using the agar well-diffusion method against pathogens. The results of the anti-bacterial investigation proved that Mn-doped ZnO nanocomposites inhibit the growth of pathogens at different concentrations. The research concludes that the extract of H. enneaspermus acts as a capping and reducing agent in the synthesis process. The process can offer bio-compatible nanocomposites for new drug development against pathogens. Full article