Perovskite solar cells (PSCs) have garnered significant attention in recent years due to their promising potential in photovoltaic applications. Ongoing research aims to enhance the efficiency, stability, and overall performance of PSCs. This study proposes the integration of copper-based metal-organic frameworks (Cu-MOFs) to address critical issues such as inadequate light absorption, instability, and suboptimal power conversion efficiency. Cu-MOFs, synthesized via the hydrothermal method at varying concentrations, have demonstrated an ability to mitigate defects in perovskite films and enhance charge transport. The structural versatility of Cu-MOFs allows for the development of new composites with improved stability and efficiency. By selecting the optimal MOF, hole transport layer (HTL), and counter-electrode materials, the performance of PSCs can be significantly improved. This research focuses on the functionalization of Cu-MOFs within PSCs to boost their efficiency. MOFs, which are porous materials composed of organic and inorganic components, are increasingly utilized in various fields including catalysis, energy storage, pollution treatment, and detection, due to their large surface area, tunable pore size, and adjustable pore volume. Despite their potential, the application of MOFs in aqueous environments has been limited by their poor performance. However, through techniques such as X-ray diffraction (XRD), UV-Vis spectroscopy, Raman spectroscopy, and scanning electron microscopy (SEM), it has been confirmed that Cu-MOFs can be successfully modified. Post-hydrothermal treatment, SEM results indicate enhanced stability and functionality of Cu-MOFs. The integration of Cu-MOFs in PSCs is expected to reduce energy consumption and significantly enhance the efficiency of these solar cells.
This study aims to develop energy-efficient and environmentally friendly cooling solutions that are both effective and adaptable to various climates and structural forms. By leveraging computational fluid dynamics (CFD) software ANSYS and simulation software Engineering Equation Solver (EES), an innovative approach was undertaken. The investigation focused on the optimization of external air cooling via adjustable injectors operating at three distinct velocities, across three airflow rates. Concurrently, the adaptability of the cooling flow was enhanced by varying the number of turns in a coil within the heat exchanger's condenser section. This dual-phase method facilitated a comprehensive analysis across 54 scenarios, employing the EES software for the calculation of the coefficient of performance (COP) enhancement metrics. The efficiency of the cooling apparatus was rigorously evaluated by methodically altering the number of cooling tube turns and injection velocities. The apparatus comprised a loop-and-tube heat exchanger with a modifiable structure, where the second phase of the study addressed the thermal impact of air entry velocity and water spray mechanisms, featuring cooling tube adjustments ranging from five to thirteen turns. The initial phase examined the effects of air entry area and water spray techniques through variable injector configurations, with diameters of 15, 24, and 20 cm, and dimensions of 10 cm in height and 25 cm in length, alongside a conduit width of 60 mm. The findings revealed that the thermal dynamics of the heat exchanger and fluid flow are significantly influenced by the apparatus's geometry, particularly the air entry area and water spraying mechanism. Temperature and velocity contours illustrated that the number of loop turns and injections markedly affects system performance. An optimal configuration, consisting of 35 injectors and 13 coil turns, achieved a COP of 4.537 at an inlet velocity of 2.0 m/s, signifying the most effective system design identified within this study.
In the realm of heat transfer, the phenomenon of boiling heat transfer is paramount, especially given its efficiency in harnessing the latent heat of vaporization for significant thermal energy removal with minimal temperature alterations. This mechanism is integral to various industrial applications, including but not limited to the cooling systems of nuclear reactors, macro- and micro-electronic devices, evaporators in refrigeration systems, and boiler tubes within power plants, where the nucleate pool boiling regime and two-phase flow are prevalent. The imperative to optimize heat exchange systems by mitigating excessive heat dissipation, whilst simultaneously achieving downsizing, has consistently been a critical consideration. This research uses computational, based on Fluent software, to analyze thermal characteristics and cooling mechanisms of different concentrations of nanofluids, in conjunction with surfaces adorned with diverse fin geometries. Specifically, the study scrutinizes the thermal performance of water-based nanofluids, incorporating Copper (II) Oxide (CuO) nanoparticles at concentrations ranging from 0% to 1.4% by volume, under boiling conditions. The analyses extend to the efficacy of different fin shapes—including circular, triangular, and square configurations-within a two-dimensional geometry, under the conditions of forced convection heat transfer in both steady and transient, viscous, incompressible flows. The findings are poised to contribute to the design of more efficient heat exchange systems, facilitating enhanced heat dissipation through the strategic use of nanofluids and meticulously designed surface geometries.
This investigation addresses the critical challenge of devising robust and sustainable energy infrastructures by integrating renewable energy sources in Makkovik, Newfoundland, and Labrador. A hybrid renewable energy system (HRES) comprising wind turbines, photovoltaic (PV) solar panels, battery storage, and backup diesel generators was evaluated for its viability and efficiency. With the help of the HOMER Pro software, extensive modeling and optimization were conducted, aimed at reducing dependency on fossil fuels, cutting carbon emissions, and enhancing economic benefits via decreased operational costs. The results indicated that the energy demands of Makkovik could predominantly be met by the proposed system, utilizing renewable resources. Significant reductions in greenhouse gas emissions were observed, alongside improved cost-efficiency throughout the system's projected lifespan. Such outcomes demonstrate the system’s capability to provide an environmentally friendly and technically viable solution, marking a substantial step towards energy resilience and sustainability for isolated communities. The integration of diverse renewable energy sources underlines the potential for substantial emission reductions and operational cost savings, highlighting the importance of innovative energy solutions in enhancing the sustainability and resilience of remote areas. This study contributes vital insights into optimizing energy systems for economic and environmental benefits, advancing the discourse on renewable energy utilization in isolated regions.
In the quest to secure energy supply and mitigate dependence on imported fossil fuels, nations are diversifying into renewable energy sources (RES). This study investigates the impact of renewable electricity production on economic growth, alongside the interplay with research and development (R&D) expenditures, through a comparative lens focusing on Norway and Brazil—both pioneers in the renewable energy arena. Analysis incorporates per capita R&D expenditures to gauge the nexus between renewable energy initiatives and R&D investment, employing data spanning from 2003 to 2014. The investigation reveals a notable divergence between the two nations. In Norway, no significant link was identified between the volume of renewable energy produced and per capita R&D expenditures. Nonetheless, a causal connection between economic growth and R&D investment was observed, with a robust correlation suggesting a profound influence of economic expansion on R&D activities. Contrarily, Brazil's scenario delineates a unidirectional causal relationship where economic growth positively influences the renewable energy sector, with no discernible association between R&D expenditures per capita and economic growth. These findings underscore the variegated impacts of renewable energy policies and R&D investments on economic dynamics within the context of Norway and Brazil, highlighting the necessity for tailored approaches in leveraging renewable energy for sustainable development.
Indonesia, known for its abundant renewable resources, especially solar energy, presents a substantial potential for developing solar-powered solutions to meet its increasing electricity demands. This study explores the feasibility of a Solar Power Plant (PLTS) as the energy source for a personal Electric Vehicle Charging Station (SPKL), facilitating the transition from fuel-based to electric vehicles. Using a simulation-based approach, a hypothetical daily electricity load of 12,711 kW was considered. The simulations indicate that an On-Grid PLTS is the most economically viable option, offering significant investment returns. The annual energy output of the PLTS was calculated to be 30,767 kWh. Financial projections suggest a substantial profit by the 25th year, amounting to IDR 374,450,204.39. This research underscores the strategic importance of integrating hybrid technologies in developing renewable energy infrastructures, particularly in regions like Indonesia, where solar irradiance is high. The findings advocate for broader implementation of such systems aligned with national energy sustainability and economic efficiency goals.
Open Access
Improvement the Preparation of C4 Oolefin Through Ethanol Coupling and Optimization the Gray Correlation Degree Algorithmpengyuan li , qingquan xu , cheng huang , haoqing wang , yisen wang , zibo wang , yibo zhang , ao wang , tianci cui , xinyue ni , yutong wang , chen gong |
Available online: 03-29-2024
C4 olefin is an important chemical raw material, but traditional production methods use limited and polluting fossil energy as raw materials. Ethanol stands out from many alternative energy sources because of its wide sources, easy conversion, and low pollution. The preparation of C4 olefins from ethanol has become an effective alternative route for olefin production, which has great environmental and economic value. Metal oxides are the main catalysts for the preparation of C4 olefins from ethanol. In this paper, a $\mathrm{SiO}_2$-$\mathrm{HAP}$ catalyst with both acid and base active sites was designed, and Co metal with dehydrogenation activity was supported on its surface. To improve the catalytic activity and improve the conversion of ethanol and the selectivity of C4 olefin, experiments were carried out by changing the process parameters such as $\mathrm{Co}$ loading (weight ratio of $\mathrm{Co}$ to $\mathrm{SiO}_2$), HAP (hydroxyapatite) mass, ethanol concentration, and reaction temperature. The improved gray relational degree algorithm was used to analyze the relational degree of process parameters with ethanol conversion and C4 olefin selectivity. Experimental results show that the detection accuracy of this algorithm for C4 olefin selectivity is better than that of the traditional algorithm without considering the difference in change rate between data, the detection accuracy is improved by 50%, and the detection accuracy of ethanol conversion is improved by 2%.
Solar energy, a ubiquitous and environmentally friendly source, plays a pivotal role in mitigating carbon emissions and reducing air pollution. This study evaluates the performance of a 50-watt monocrystalline solar panel over a thirty-day period in October 2022, within Merauke Regency, South Papua Province, Indonesia. Adopting an experimental research methodology and comprehensive data collection, measurements of solar intensity, temperature, voltage, and current were systematically gathered using temperature sensors, ammeters, and voltmeters. These measurements were obtained by positioning the solar panel at a perpendicular angle to direct sunlight, with data recorded between 9:00 and 16:00 Eastern Indonesia Time. The analysis of the collected data was conducted to ascertain the panel's efficacy, revealing an average output of 20.68 volts, 1.95 amperes, 40.37 watts, and a 9% efficiency. Notably, peak performance was observed on the tenth day, characterized by 21.30 volts, 2.24 amperes, 47.71 watts, and an efficiency of 11.01%. The findings of this investigation are anticipated to inform the installation and utilization strategies of similar solar panel types within Merauke Regency and potentially broader applications. This study underscores the critical influence of solar irradiance on the operational performance of monocrystalline silicon solar panels, contributing valuable insights to the field of renewable energy research.
Among the various heat transfer mechanisms, boiling heat transfer is distinguished by its capacity to dissipate substantial heat via the latent heat of vaporization with minimal temperature differentials. This phenomenon is pivotal across a range of industrial applications, including the cooling of macro- and micro-electronic devices, boiler tubes in power generation plants, evaporators in refrigeration systems, and nuclear reactors, where the nucleate pool boiling regime and two-phase flow are of particular interest. The drive to enhance heat exchange systems' efficiency has consistently focused on minimizing heat loss through system miniaturization. This investigation employs numerical simulations via the Fluent software to elucidate the heat transfer and cooling processes facilitated by nanofluids with varied concentrations on differently shaped finned surfaces, alongside the utilization of water and ethylene glycol as base fluids. Specifically, the thermal performance of $\mathrm{Al}_2 \mathrm{O}_3$-water nanofluids at different concentrations (0, 0.3, 0.6, 1, 1.2, and 1.4 percent by volume) was scrutinized under boiling conditions across surfaces endowed with circular, triangular, and square fins. The study confirmed that the incorporation of $\mathrm{Al}_2 \mathrm{O}_3$ nanoparticles into the water base fluid not only enhances its thermal conductivity but, in conjunction with micro-finned surfaces, also augments the available surface area, thereby improving wettability. These modifications collectively contribute to a marked increase in the heat transfer coefficient (HTC) and a reduction in the critical heat flux (CHF). Furthermore, it was observed that at a 0.3% volume concentration of $\mathrm{Al}_2 \mathrm{O}_3$ with square fins, the temperature span extends from 373.1 to 383.1 K. Nonetheless, the long-term stability and efficacy of nanofluids are subject to potential impacts from nanoparticle aggregation and sedimentation. This study underlines the synergistic effect of nanoparticle-enhanced fluids and micro-finned surface architectures in bolstering pool boiling heat transfer, signifying a promising avenue for thermal management advancements in various industrial domains.
In the quest for sustainable and environmentally friendly biofuels, Calophyllum inophyllum L., commonly known as Nyamplung, presents a promising feedstock due to its high oil content (75%) and a significant proportion of unsaturated fatty acids (approximately 71%). Notably, the oil extracted from this species exhibits higher viscosity and reduced capillarity compared to conventional kerosene, posing unique challenges for biodiesel conversion. This study explores the efficacy of electromagnetic induction heating as a novel transesterification method to produce biodiesel from Nyamplung oil. The process was optimized across a range of temperatures (45-65°C), reaction times (0.43-1.03 minutes), methanol to oil molar ratios (6:1), and a catalyst concentration of KOH at 2% of the total weight of oil and methanol. The conversion of Nyamplung oil into biodiesel was primarily assessed through the formation of methyl esters, with Gas Chromatography-Mass Spectrometry (GC-MS) employed for analytical verification. A comprehensive kinetic analysis revealed a transesterification reaction rate constant of rT=6.46×1014e(-1,068.93/RT) [ME], indicating an activation energy requirement of 1,068 kJ/mol at the operational peak temperature of 65°C. This activation energy is notably lower than that observed with microwave heating, suggesting electromagnetic induction as a more efficient heating mechanism for this reaction. The findings underscore the potential of electromagnetic induction heating in enhancing the conversion efficiency of high-viscosity feedstocks like Nyamplung oil into biodiesel, offering a promising avenue for the production of renewable energy sources. The detailed evaluation of reaction kinetics and activation energies within this study not only contributes to the optimization of biodiesel production processes but also reinforces the viability of Calophyllum inophyllum L. as a sustainable biofuel precursor.
The integration of Artificial Intelligence (AI) into sustainable energy management presents a transformative opportunity to elevate the sustainability, reliability, and efficiency of energy systems. This article conducts an exhaustive analysis of the critical aspects concerning the AI-sustainable energy nexus, encompassing the challenges in technological integration and the facilitation of intelligent decision-making processes pivotal for sustainable energy frameworks. It is demonstrated that AI applications, ranging from optimization algorithms to predictive analytics, possess a revolutionary capacity to bolster intelligent decision-making in sustainable energy. However, this integration is not without its challenges, which span technological complexities and socio-economic impacts. The article underscores the imperative for deploying AI in a manner that is transparent, equitable, and inclusive. Best practices and solutions are proposed to navigate these challenges effectively. Additionally, the discourse extends to recent advancements in AI, including edge computing, quantum computing, and explainable AI, offering insights into the evolving landscape of sustainable energy. Future research directions are delineated, emphasizing the importance of enhancing explainability, mitigating bias, advancing privacy-preserving techniques, examining socio-economic ramifications, exploring models of human-AI collaboration, fortifying security measures, and evaluating the impact of emerging technologies. This comprehensive analysis aims to inform academics, practitioners, and policymakers, guiding the creation of a resilient and sustainable energy future.