Narrow Results

In order to intuitively present the layout and design of the solar energy utilization system, improve the integrity, and consistency of the design. Design and analyze the solar energy utilization system of green buildings based on Building Information Model (BIM). The data acquisition layer collects relevant data of green buildings and solar energy utilization system in RFID and WSN mode and transmits them to the data processing layer; the data processing layer filters the data related to green buildings and solar energy utilization system according to IPC construction standards, and transmits them to the model layer through the Internet of Things; the model layer uses the REVIT software combined with the filtered data to build and update the BIM model of green buildings and solar energy utilization system, intuitively present the layout and design of the solar energy utilization system, and improve the integrity and consistency of the design; the application layer uses the fuzzy comprehensive evaluation model, combined with the green building and solar energy utilization system BIM model, to simulate and analyze the solar energy utilization system environment of green buildings; the user layer provides users with human–computer interaction functions to view the design and analysis process of the solar energy utilization system of green buildings. Experiments show that this method can effectively collect relevant data of green buildings and establish a BIM model of solar energy utilization system; this method can effectively design the solar energy utilization system of green buildings; the solar energy utilization system designed by this method can effectively reduce the electric heating capacity of green buildings, and has an excellent energy-saving effect.

A ground-breaking solution that combines solar thermal energy and lithium-bromide vapor absorption technology to produce energy-efficient cooling and heating is the Intelligent Solar Assist 1kW Lithium Bromide Vapor Absorption system. This cutting-edge system uses the sun’s energy to power the absorption cycle, offering environmentally friendly and economically viable thermal management. Solar thermal collectors, a lithium bromide absorption chiller, a thermal energy storage device, and sophisticated control algorithms comprise the system’s main parts. Sunlight is captured and converted by solar thermal collectors into thermal energy, which is then used to produce the necessary heat for the lithium bromide absorption chiller. This chiller uses the absorption refrigeration cycle to efficiently cool or heat the specified area or process. When intelligent control algorithms are incorporated, the system performs and operates more effectively and efficiently. These algorithms regulate the thermal energy storage unit and optimize the use of solar energy, delivering a constant and dependable supply of cooling or heating as needed. Advanced monitoring and diagnostics features are also built into the system, allowing for remote control and in-the-moment performance evaluation. Disadvantages are ethical issues, lack of generalization, interpretability and complexity, scalability and processing resources, and scientific agreement. A novel Chimp-based recurrent model (CbRM) has been planned to be designed to predict the desired efficiency from the Evacuated Tube Collector (ETC) to overcome this issue. Comparing the Intelligent Solar Assist system to conventional heating and cooling systems, several benefits must be had. It minimizes greenhouse gas emissions, lessens reliance on traditional energy sources, and promotes a more sustainable future. The system also saves money using solar energy, lowering power costs and enhancing energy efficiency. Moreover, the proposed system implementation is done in Matlab. The method achieves the high efficiency of ETC in the range of about 0.9% which increases by 0.3% and the higher rate of COP was about 9.5% which increases up to 6%, as the increased concentration level of the strong solution was about 6.5% it was nearly 5% increase. The parameters in the suggested model were compared to the current parameters for the comparison analysis, and it was discovered that the proposed model had superior presenting efficiency.

Solar energy can be considered as an alternate solution to conventional energy sources. Short-term Photovoltaic (PV) Power Generation (PVPG) prediction methods are essential stabilize power integration among PV and smart grids. The PVPG generation process is highly dependent on climatic conditions and therefore high intermittent. Highly accurate PVPG prediction of PVPG acts based on the generation, transmission and dispersion of electricity, confirming the stability and dependability of power system. The current progress of Machine Learning (ML) and Deep Learning (DL) approaches enables for designing of accurate PVPG prediction models. In this view, this paper develops a new Badger Optimization with Deep Learning Enabled PV Power Generation Predictive (HBODL-PVPGP) model. The presented HBODL-PVPGP model enables to forecast of the PVPG process. To accomplish this, the HBODL-PVPGP model initially investigates the features depending upon intrinsic characteristics earlier in the learning process. In addition, the Bidirectional Gated Recurrent Unit (BiGRU) model is implemented for forecasting process. The performance of the BiGRU model can be improvised by the design of HBO-based hyperparameter tuning procedure. For ensuring the enhanced performance of the HBODL-PVPGP model, an extensive range of experimental study was effectuated and the results were investigated under various factors. The result highlighted the precipitated performance of the HBODL-PVPGP procedure on the current algorithms.

A new metamaterial absorber (MA) having distinct properties than those given in the literature is investigated. Although several designs have been studied for achieving absorption characteristics in single-band, dual-band and multiple bands within the whole spectrum of solar light, there has been limited number of researches examining the broadband MA in the visible light section of the spectrum. The designed structure is composed of the combination of three layers having different thicknesses including a metallic substrate, dielectric and a metal layer. Due to the sandwich-like structure, it can support the plasmonic resonance. The proposed structure, which provides a maximum absorption level of 99.42% at 579.26 THz, has a high absorption rate of 99% between the frequency band 545 and 628 THz. Numerical results indicate that the proposed structure has perfect absorption which is greater than 90.98% through the whole working frequency band. The dependency of the designed structure on the polarization angle is investigated for different incident angles with TE and TM polarizations as well as the TEM mode. In addition to its potential applications such as solar cells and cloaking, the designed structure can also be considered as a color sensor and an optical frequency sensor.

The world energy crisis necessitated the cause of the research interest into new, renewable and alternative energy sources. From this point of view, there is research on phenomena and different synthetic methods and on structure and electronic property optimization expressed by important material and device advancement. Efficiency and electricity generation (batteries, fuel cells, hydrogen energy) are nowadays actual questions. Because of that research, innovations and applications require extended knowledge by fractal nature characterization. The electrochemical energy sources solutions, especially electrolytes, are in fractal nature science focus. Based on the research novelties, especially electronic materials, we presented an investigation on fractal structure influence in electrochemistry. We explore the activation energy and fundamental thermodynamic functions and values, also the electrode surface changed by complex fractal correction through fractal dimension of grains and pores, and Brownian motion of involved particles, as well. At the end, the electrochemical Arrhenius and Butler–Volmer equation fractalization is applied. All of these open new perspectives for electrochemical energy processes, within electrolyte bulk and related electrodes and more precise energy generation. This is important for semiconductor processing in solar cells and devices. So, we included the knowledge of fractal sciences advancement in this field for current–voltage equation.

The growing popularity of artificial intelligence approaches has led to their application in a wide range of engineering fields. The most widely used artificial intelligence tool, artificial neural networks, can be used to predict data with high accuracy. An artificial neural network approach is being used to predict effective and accurate thermal conductivity and viscosity models for hybrid nanofluid systems. Here, new types of correlations relating to the thermophysical properties of Fly Ash–Cu nanoparticles with diameter sized 15.2nm and which are temperature-dependent are developed. The highest thermal conductivity and viscosity values were obtained for hybrid nanofluids with a mixture ratio of 20:80, with maximum amplification exceeding 83.2% and 65%, respectively, over the base fluid. The Fly Ash–Cu/water hybrid nanofluid’s viscosity and thermal conductivity are evaluated for a concentration range of 0–4%. The evaluation of the Fly Ash–Cu/water hybrid nanofluids system at concentrations ranging from 0 to 4% most likely entails a scientific or engineering study aimed at understanding the behavior and properties of this nanofluid mixture. Nanoparticles can agglomerate or settle in the base fluid over time, compromising the stability of the nanofluids. Researchers may be interested in determining how varied quantities of Fly Ash and Cu nanoparticles affect the nanofluid’s stability and sedimentation behavior. The heat transfer potential is examined within the optimistic range of temperatures of 30–80^∘C. Many fruitful results for turbulence and solar energy have been drawn. The Mouromtseff number achieved an optimal value for all concentration levels. The heat transfers of turbulent flow and thermal conductivity of hybrid nanofluids increase with the augmented values of concentrations and temperature. Researchers found an increase in thermal conductivity of hybrid nanofluids at 0–4% concentrations, potentially impacting heat transfer applications. The conclusion explores the potential integration of the developed correlations and neural network model into practical engineering or industrial applications involving solar energy and turbulence appliances. In this work, we extend the work of Kanti et al. [Sol. Energy Mater. Sol. Cells 234 (2022) 111423] which is on the properties of water-based fly ash-copper hybrid nanofluid for solar energy applications.

Technologies regarding solar heating, ventilation and air-conditioning (S-HVAC) are aimed at making modern 3D numerical forms that address the Sutterby flow ternary nanofluids circulating onward the convective heating and extendable seats. Heat transport includes joule heating, heat source or sink along with thermal radiation. Using fitting modifications, mathematically conveyed partial differential equations of energy, fixation and strength may decrease into ordinary differential equations (ODEs). They determine ODEs beyond dimension, and for this, the mathematical process is utilized. Copper–silver–aluminum alloys/sodium alginate (Cu–Ag–AA7075/C₆H₉NaO₇) was used to address the behavior of this research work. The natural attributes, for example, heat movement and surface drag coefficients, are numerically prepared and shown in figures and tables when there is an alteration in distant factors. The field of temperature was raised to develop the Biot number. This heat transport rate was hiked to 34.0839% although the shear stress rate was hiked to 32.8043% in the single nanoparticle case compared to the triple nanoparticle case. To validate the analysis, a comparison between the presented and existing is reported under certain assumptions on the flow parameters. It is found that the results are reliable and in line with the existing ones.

To drive a white light-emitting diode (LED) in portable devices, a dual-input serial DC–DC converter realizing individual switching modes is proposed in this paper. Unlike conventional single-input converters, the proposed converter provides output voltage by converting not only battery energy but also solar energy. Therefore, the proposed converter can suppress energy consumption of a battery. Furthermore, in the proposed converter, the -1/m× stepped-down voltage (m = 1,2,…,N) is generated to drive LED's cathode only when the voltage of solar-cells is insufficient to drive 1 × transfer mode. In other words, when the voltage of solar-cells is sufficient to drive LEDs, the proposed converter is in standby mode. For this reason, the proposed converter can realize high power efficiency, because energy loss caused by the power conversion is suppressed. The properties of the proposed converter are clarified by theoretical analyses. Furthermore, SPICE simulations and experiments show the validity of circuit design, where theoretical results correspond well with SPICE simulated results. For this reason, derived theoretical formulas can provide basic information to design negative switched capacitors (SC) DC–DC converters. The proposed converter will be useful as a driver circuit of white LEDs for display backlighting.

In this work, we used hourly data of high frequency of solar radiation from the entire Northeast region of Brazil. We used the Multifractal Detrended Fluctuation Analysis (MFDFA) method to analyze the characteristics of the solar radiation series in 137 meteorological stations from 2010 to 2022. For all analyzed series, the parameter ${\alpha }_0>0.5$ characterizes persistent series. The values of $r>1$ reveal asymmetry to the right, indicating that large fluctuations contributed to the multifractality process. The states of Maranhão and Bahia presented the highest values of spectrum width $W$, indicating greater complexity. We found that long-range correlations are the leading cause of multifractality observed in the dynamics of the series of solar radiation anomalies.

The object of this paper is to simulate and optimize small scale concentrating solar power tower (CSP) built and operationalized at King Abdulaziz University, Jeddah, Saudi Arabia, through analytic hierarchy process (AHP) technique. The aim is to facilitate cost effective integration of solar power coupled with energy generation technologies subjected to challenging climatic conditions; and also to present the effects of changing in parameters such as receiver, heliostats, storage tanks or power generation subsystem on the cost and system performance. This study adopts the AHP technique to obtain the most appropriate receiver shape out of three possible shapes; spherical, cubic, and cylindrical. The used criteria in this in this optimization are reliability, manufacturing in the vicinity, manufacturing cost, service and maintain cost, lower operation risks, and high performance. Based on the results of AHP analysis, square shape is selected. A finite element analysis via ANSYS is performed to compute the through analytic division of temperature in the receiver. The highest temperature from the simulation is 503°C. The thermal power, dispensed by the molten is 12.52 kW during the heat exchanger. However, 13 kW is the design thermal power; while about 3.7% is the percentage error in the thermal power. The findings of this research will provide the needed knowledge and scientific background to assist the authorities concerned in the energy sector in establishing a commercial-scale plant. At the end, Artificial Neural Network algorithms/Fuzzy system is modeled to optimize the process.

Roads have always been the main source of transportation all over the world. Easy accessibility and more safety are the most important features of road transportation. Improvements in these areas are constantly required and invited. Solar road studs are one of the remarkable improvements in road safety. Solar road studs use solar energy, which is the most sustainable and pollution-free source of energy that provides reliable power supplies and fuel diversification. Solar road studs are flashing solar cell-powered LED lighting devices used in road construction to delineate road edges and centerlines. This research work is dedicated to evaluating the reliability measures which include availability, mean time to failure (MTTF), cost analysis, and sensitivity analysis with their graphical representation by using the Markov process. Along with reliability assessment, Particle Swarm Optimization (PSO) technique is applied to optimize the cost of the system.

Using glasses with 200-nm Cu films as substrates, the colored solar energy selective absorbing films with three-layer structure had been designed by optical multilayer design software. The three layers materials were Fe doped AlN and AlN. The optical constants of Fe doped AlN films with different Fe volume fractions were calculated by the effective medium theories. The color of the absorbing films includes orange yellow, purplish pink, pink, purple, and green. The solar absorptance of each colored film is between 0.89 and 0.96. The thermal emittance is lower than 0.1. The green film has the highest brightness. The purplish pink film has the highest absorptance, while the orange yellow and purple films have the lowest emittance. The color, absorptance, emittance, and brightness of the green film at different angles of light incidence had been analyzed. When the incident angle increases from 0° to 50°, the color of the green film changes from green to blue, and its absorptance and emittance decrease.

The following topics are under this section:

• A general framework for predictive maintenance of manufacturing systems
• A remote-controlled smart platform for organ repair
• COVID-19 and its genetic relationship with other coronaviruses
• East meets West: cancer therapy using acupuncture and electrochemistry
• A triple-function bismuth oxochromate photocatalyst
• AI enables whole-slide imaging for diagnosis of nasal polyps

Solar energy is the abundantly available source of renewable energy with least impact on environment. Direct absorption solar collector (DASC) is the commonly used device to absorb heat directly from sun and make use of it for different heating applications. In the past, many experiments have been done to increase the efficiency of DASC using nanofluids. In this paper, an examination of solar collector efficiency for hybrid CeO₂/CuO–water (0.1% by volume) nanofluid under various flow rates and proportions of CeO₂/CuO nanoparticles is investigated. The experiments were conducted at flow rates spanning from 20cc/min to 100cc/min and with CeO₂/CuO nanoparticles proportions of 1:0, 1:0.5, 1:1, 0.5:1 and 0:1. The efficiency increases from 16.5% to 51.6% when the flow rate is increased from 20cc/min to 100cc/min for hybrid CeO₂/CuO (1:1)–water nanofluid. The results also showed an increase in efficiency of 13.8%, 18.1%, 24.3%, 24.9% and 26.1% with hybrid combination of CeO₂/CuO at ratios 1:0, 1:0.5, 1:1, 0.5:1 and 0:1, respectively, in comparison with water at a flow rate of 100cc/min.

The concerned study invariably presents the key findings of the scientometric analysis of Solar Cell Research (SCR) in the specific context of Africa and India. The outstanding contributions explicitly delivered by the successful collaboration of African and Indian authors are satisfactorily accounted for in specific terms of published author, year-wise, research area, funding agencies, published citations, and h-index. The necessary data for the needed research was retrieved from the Web of Science from 2009–2018. The raw data was further analysed and properly presented using MS Excel and VOSviewer as the keyword network tool. An aggregate number of scholarly publications in the global scenario at 117,605, Africa and India typically contributed 2,932 and 7,848, respectively. Joint research of 92 academic journals, receiving citations of 1,348, was usually observed. The highest source of 394 (29.23%) was received overwhelmingly in 2018. Out of the 652 published authors contributing constructively to the remarkable collaboration, H. C. Swart, of the University of the Free State, Bloemfontein, South Africa, contributed 14 publications, allegedly giving a 2.147% of the total count. This is followed by V. Kumar of the Indian Institute of Technology New Delhi (India); UCA (France); UFS (South Africa), which also contributed 12 publications measured at 1.84% of the total count of publications.

The economy of space and materials and the continuously increasing demand for advanced functionalities for diverse technologies requires the development of new synthetic methods. Many nanomaterials have enhanced photophysical and photochemical properties in solutions and/or on surfaces, while others have enhanced chemical properties, compared to the atomic, molecular, or bulk phases. Nanomaterials have a wide range of applications in catalysis, sensors, photonic devices, drug delivery, and as therapeutics for treatment of a variety of diseases. Inorganic nanoparticles are widely studied, but the formation of organic nanomaterials via supramolecular chemistry is more recent, and porphyrinoids are at the forefront of this research because of their optical, chemical, and structural properties. The formation of nanoscaled materials via self-assembly and/or self-organization of molecular subunits is an attractive approach because of reduced energy requirements, simpler molecular subunits, and the material can be adaptive to environmental changes. The presence of biocompatible groups such as peptides, carbohydrates, polyglycols and mixtures of these on the periphery of the porphyrin macrocycle may make nanoparticles suitable for therapeutics. This perspective focuses on responsive, non-crystalline porphyrinoid nanomaterials that are less than about 100 nm in all dimensions and used for catalytic or therapeutic applications.

The new visible-light operated CO₂-glucose biofuel cell consisting of chlorin-e₆ immobilized on TiO₂ thin layer film onto optical transparent conductive glass electrode (OTE) as an anode, formate dehydrogenase (FDH) and viologen with long alkyl chain co-immobilized OTE as a cathode, and the solution containing glucose, glucose dehydrogenase (GDH) and NAD⁺ as a fuel was developed. The short-circuit photocurrent and the open-circuit photovoltage of this cell are 37 μA.cm^-2 and 390 mV, respectively. The maximum power is estimated to be 57 μW.cm^-2. The overall photoenergy conversion efficiency is estimated to be 0.057%. After 2 h irradiation to this cell, 0.65 μmol of formic acid was produced. During irradiation, the photocurrent was constant value of 32 ± 10 μA.cm^-2 in the cell. Thus, CO₂ reduces and formic acid produces while generating electricity with visible light irradiation to this biofuel cell.

Environmental impact assessments (EIAs) and renewable energy developments are key instruments to achieving sustainable development goals. Additionally, environmental impact assessment reports (EIARs) are vital in communicating the findings of proposed developments to all stakeholders. Yet, the quality of EIARs does not always comply with criteria in a satisfactory manner, thereby compromising sustainability. The quality of 25 solar energy EIARs in South Africa was reviewed with an adapted Lee–Colley Review Package. Based on this review, 68% of EIARs were found to be satisfactorily conducted, whereas 80% of the overall scores were regarded as borderline quality grades. Interestingly, complex assessment tasks — determining impact significance, alternatives, mitigation measures and the communication of findings — were executed unsatisfactorily. The poor communication of environmental impacts to stakeholders is not only an obstacle for EIA processes but also for sustainable development mechanisms as a whole.

Solar steam generation is an efficient photo thermal conversion method, which has a wide range of applications in water purification and desalination. With an increasing requirement for technological advancements, the low efficiency of the working media has become a hindrance. In this work, ZrC nanofluid, which has good stability and broad-band absorption capability, was prepared to enhance the volumetric solar steam generation. The effect of ZrC nanoparticle concentration, within a large volume, on a solar steam generation was experimentally studied. It has been found that due to the unique optical absorption characteristics of ZrC nanoparticles, an advantageous temperature gradient with hot irradiation surface layer is attained and the irradiation energy is mostly absorbed by the top surface layer to generate steam. This reduces heat dissipation and improves the evaporation efficiency of the working media. Enhanced solar steam generation by using ZrC nanofluid in the base fluid reduces evaporation costs and expands its applicability in commercial production.

Nanofluids are promising in solar harvesting and solar thermal utilization. Ethylene glycol (EG) nanofluids have the advantages of high boiling point and low volatility, and therefore are highly desired in some circumstances. In this study, the solar harvesting and solar thermal conversion properties of EG were significantly enhanced by carbon chain nanostructures (CCNSs). The prepared CCNSs/EG nanofluids showed greater optical absorption compared to EG in the wavelength range from 250nm to 1400nm. The solar weighted absorption factor (Am) of the CCNSs/EG nanofluids was 95.9% at the mass fraction of 0.05 wt.%. The enhancement was 649.2% compared to that of EG. The photothermal conversion efficiency was determined to be 97.7% and the enhancement of 83.0% was achieved. An enhancement of 1.2% in thermal conductivity was also been observed. These enhancements can be ascribed to the special architectures of the CCNSs that provide fast transfer path for the generated heat.