International Journal of Energy Research (IJER) is dedicated to providing a multidisciplinary, unique platform for researchers, scientists, engineers, technology developers, planners, and policy makers to present their research results and findings in a compelling manner on novel energy systems and applications. IJER covers the entire spectrum of energy from production to conversion, conservation, management, systems, technologies, etc. We encourage paper submissions aiming at better efficiency, cost improvements, more effective resource use, improved design and analysis, and reduced environmental impact.
In this study, we propose two advanced processes, i.e., advanced syngas-to-methanol (AS2M) and direct CO2-to-methanol (DC2M) processes, for methanol production using waste CO2 and renewable H2 as feedstock. The AS2M process produces methanol from syngas after converting CO2 to CO via reverse water-gas shift and separating CO from a mixture through pressure swing adsorption. In comparison, the DC2M process directly synthesizes methanol from CO2 through direct hydrogenation. Different unit processes and recycles were synthesized to determine the optimal process configurations and operating conditions for maximizing the methanol production rate. The technoeconomic and environmental capabilities of the two proposed processes were analyzed with four evaluation criteria (carbon and energy efficiencies, CO2 reduction, and unit production cost) and compared with conventional CO2-to-methanol processes. A sensitivity analysis for various utilities and H2 supply strategies was performed to evaluate the economic feasibility and environmental benefits of the proposed systems with different design options. Our findings showed that both processes could achieve improved technical, economic, and environmental performances compared to conventional processes. In particular, the DC2M process showed the lowest unit production cost at $1.02/kg because of its simple configuration and mild operating conditions.
This paper examined the usage of thermally conductive angled fins within an annular conduit through numerical simulation. Despite the thermally conductive nature of the fins increasing heat transfer surface area, this investigation found that using an optimal fin angle can promote the generation of vortical structures which aid heat transfer. Using ANSYS-Fluent with the SIMPLEC algorithm and the SST κ − ω turbulence model, this research found that heat transfer performance improved considerably when the generated vortices were sufficiently large and robust. However, the type of generated vortex had a profound impact when optimising for higher performance evaluation criterion (PEC) values. Longitudinal vortices improved heat transfer performance with a low impact on pressure drop increase, unlike transverse vortices, which increased pressure drop significantly. The fin angles of 50° and 60° yielded high heat transfer performance without much increase in pressure drop, thus resulting in higher PEC values. Additionally, using fin heights that correlate to 20% to 60% of the gap between the concentric walls was ideal when designing heat exchangers to achieve higher PEC values. The results of this numerical investigation have been validated both theoretically and experimentally to ensure accurate reporting of the findings.
Two-dimensional transition metal dichalcogenides (TMDs) have gained attention as potent catalysts for the hydrogen evolution reaction (HER). The traditional trial-and-error methodology for catalyst development has proven inefficient due to its costly and time-intensive nature. To accelerate the catalyst development process, the Gibbs free energy of hydrogen adsorption ( Δ G H ∗ ), computed using the density functional theory (DFT), is widely used as the paramount descriptor for evaluating and predicting HER catalyst performance. However, DFT calculations for Δ G H ∗ are time-consuming and thus pose a challenge for high-throughput screening. Herein, we devise a predictive model for Δ G H ∗ within transition metal-doped TMD systems using a machine learning (ML) framework. We calculate DFT Δ G H ∗ values for 150 TM-doped MX2 (CrS2, MoS2, WS2, MoSe2, and MoTe2) and apply various ML algorithms. We validate the universality of our model by constructing 15 new external test sets. The prediction results show a high correlation coefficient of R 2 = 0.92 . Based on feature analysis, the three most important parameters are the number of valence electrons of the doped transition metal, the distance of the valence electrons of the doped transition metal, and the electronegativity of the doped transition metal. Our DFT-based ML model provides a useful guideline for the material development process through Δ G H ∗ prediction and facilitates the efficient design of transition metal dichalcogenide catalysts that exhibit superior HER activity.
The supercritical CO2 cycle is one of the next generation’s power generation cycle. Especially, the transcritical CO2 Rankine cycle (TCRC) is a suitable candidate for dispersed generation systems with small-scale solar thermal applications. Compared to other cycle studies applied in other fields such as nuclear energy, there are limited reports on renewable energy fields. Therefore, in this study, the TCRC for a small-scale solar thermal heat source is investigated by thermodynamic and experimental methods. The experimental facility was built with approximately 12 kW of thermal capacity and commissioned to evaluate its performance using a case study. The maximum temperature of the cycle is the primary optimization variable of the experiment, and it has a significant impact on the cycle thermal efficiency. Based on the experimental data, the trends of the cycle thermal efficiency and generated power are simulated assuming that the TCRC is operating with real insolation during the daytime. As a result of the simulation, maximum efficiencies of 6.41 and 6.03% are obtained from maximum solar radiation amounts of 758 and 674 W/m2 in May and June, respectively. At that time, the amounts of power generated were 726 W and 626 W, respectively.
Recently, Zeolitic Imidazolate Frameworks (ZIFs) and their hybrid composites have incited a lot of interest in the research community and have shown promising potential in supercapacitors owing to their excellent conductivity, high surface area, tunable structure, rich redox chemistry, composition diversity, etc. Even though many ZIFs are being studied for the advancement of electrode materials used for energy storage applications, in this review, we are focused on ZIF-8 and ZIF-67 only. The electrochemical performance of pure ZIFs is poor due to low electronic conductivity and poor cycling life. To counter this, ZIFs are mixed with other materials like conducting polymers, other transitional metals composites, and activated carbons to prepare hybrid composites. Furthermore, the highly porous structure and large surface area of the ZIFs cage act as an ideal template for designing composites with excellent supercapacitor applications. This reviewis focus on the synthesis and electrochemical performance of such materials. This review is divided into two main parts: the design and synthesis of ZIF-8 and ZIF-67 derivatives for supercapacitor applications and the electrochemical performance of ZIF-8 and ZIF-67-based derivatives in three-electrode and two-electrode setups. Lastly, the challenges and obstacles encountered while employing ZIF-8 and ZIF-67-based composites in supercapacitors will be reviewed and commented on.
This paper proposes and analyses several configurations for hybridising concentrating solar power (CSP) plants with combined cycle gas turbines (CCGT). The objective is to increase the solar contribution to a large extent, much higher than those obtained in integrated solar combined cycles but maintaining synergies, which are usually lost when increasing the solar share. For that, two thermal energy management systems are introduced at different temperature levels. First, a configuration with only the low-temperature system is proposed. Then, an enhanced configuration with the low- and high-temperature systems is conceived. These configurations are compared to reference CSP and CCGT state-of-the-art plants. The analyses include different strategies of operation and two sizes for the thermal energy storage system. The results show that the first proposed configuration introduces some synergies but cannot improve the performance of the reference CSP and CCGT working separately, due to an issue with the solar dumping on days with high solar irradiation. The enhanced configuration overcomes this problem and maintains the synergies, leading to an improvement from both the thermodynamic and economic points of view, increasing the solar contribution and decreasing the levelized cost of energy over the reference plants.
A rotor shaft under high rotating speeds and heavy loading may establish fatigue damage in terms of cracks due to the long duration of the operation. Analysis of the size and location of the crack in the rotor shaft becomes very difficult, especially while the rotor shaft revolves in a viscous fluid medium. This research is an attempt to measure the vibration signature of a multicracked cantilever rotor shaft with additional mass at the free end in a different fluid medium at a finite region. The dynamic response of a cracked cantilever rotor shaft, with additional mass at the free end, partly immersed in air and diverse viscous mediums are measured experimentally. The existence of open cracks in the rotor shaft in both transverse directions, along the crack and perpendicular to the crack, was considered. The experimental analysis is performed to examine the variation in vibration response with varying the size of the rotor shaft, crack depth, and fluid properties. The finite element analysis technique is employed by using ANSYS to authenticate the vibration response of the same multicracked cantilever rotor shaft in air and different viscous mediums.
Evaporative cooling is an efficient approach for removing heat from nuclear reactors, solar power plants, solar panels, and energy storage devices, such as lithium-ion batteries and fuel cells. Nanotextured surfaces can provide improved evaporative cooling by increasing the total surface area to enhance the heat transfer rate and reducing the temperatures of local hotspots. In this study, we introduced rhombic dodecahedral zeolitic imidazolate framework-8 (ZIF8), a class of metal-organic frameworks, via impregnation to create nanotextured surfaces. The impregnation time was varied to obtain various thicknesses of ZIF8. We found that the increased surface area of ZIF8 improved convection cooling, which considerably reduced the temperature of the heated substrate. Air, mist (buoyant aerosols), and spray (inertial droplets) were independently used as coolants to compare the cooling performance of noncoated (bare) and ZIF8-coated substrates. Compared to the noncoated substrate, the optimal ZIF8 film yielded temperature reductions of Δ T = 13 °C and 10°C for air and spray cooling, respectively.
The economic complexity index is an effective dimensionality reduction tool that is applied to forecast and predict future economic growth, income, and environmental quality. Renewable energy plays an important role in mitigation of carbon dioxide emissions. This study explores the nexus between economic complexity, renewable energy, FDI, trade, and environmental quality in Japan for the period 1970Q1-2019Q4. We use carbon dioxide (CO2) emissions as dependent variable while economic complexity index (ECI), foreign direct investment (FDI) inflow, renewable energy (RNE), and trade as explanatory variables. This study applies a quantile autoaggressive approach for analysis; the result of this study suggests a long-run implication of the ECI, FDI, GDP, RNE, and trade for the CO2 emissions. While only RNE and trade show mixed results in the short run, the rest of the variables do not have short-run implications. This implies that emissions mostly result in the industrial production activities only in the long run and in some quantiles only in the short run. The Japanese government may adopt different measures to reduce the CO2 emissions in the country, such as carbon tax and tax exemption on renewable energy investment. Furthermore, the government may adopt the renewal energy in production, which could achieve sustainable development goal.
In this study, a carbon-neutralized direct methanol fuel cell (DMFC) using two bifunctional electrodes, Pd-Ag and Pt-Zn, has been designed. This system has two modes, which are fuel-cell mode and spontaneous CO2 reduction mode. In the operation of fuel-cell mode, the methanol has been oxidized into CO2 on the Pd-Ag electrode and generates electricity. In the next step of the operation, CO2, which is the product of fuel-cell mode, has been spontaneously reduced to CO on Pd-Ag, and electricity has been obtained. In contrast, the Pt in the Pt-Zn electrode catalyzes the oxygen reduction reaction in the fuel-cell mode, and the Zn in Pt-Zn is oxidized sacrificially in the CO2 reduction mode. During operation in the fuel-cell mode, a power density of 12.11 mW/cm2 has been obtained with the production of CO2. On the other hand, the power density out of the CO2 reduction mode has been 11.76 mW/cm2. In each mode, the faradaic efficiencies of CO2 and CO have been 98.81% and 89.11%, respectively.
This study involved a Reynolds-averaged Navier-Stokes- (RANS-) based computational fluid dynamics (CFD) analysis of the 37-pin wire-wrapped fuel bundle of the PNC Plant dynamics test loop (PLANDTL) facility. Previously, mainly the hydrodynamic phenomena of the wire-wrapped fuel bundle were analyzed, but the present study additionally included heat transfer analysis through conjugate heat transfer. The main purpose of the study was to benchmark the experimental data of the PLANDTL 37-pin wire-wrapped fuel bundle to investigate the heat transfer phenomena. In addition, the aim was to verify the accuracy of the RANS-based CFD analysis method using the STAR-CCM+ simulation software in comparison with the experimental data. The grid used for verification was an innovative grid system consisting of hexahedra using Fortran-based code. The development of the RANS-based CFD methodology included grid sensitivity analysis, turbulence model sensitivity analysis, and turbulent Prandtl number sensitivity analysis. Information on the temperature, mass flow rate, and area of the CFD results for each subchannel was provided for the top of the heated section and is expected to serve as a reference for future studies aiming to perform the validation and verification of a PLANDTL facility. In addition, the dependence of the peak temperature on the azimuth angle of each pin was analyzed.
In synchronous machines, electromechanical swinging can be damped by parametric control of the excitation current. This is possible only in case the excitation time constant is much smaller than the mechanical constant of the machine. The method described in this paper is effective for damping oscillations caused by oscillations in the grid frequency, grid voltage, and mechanical torque fluctuations. The method is based on the Lyapunov stability theory and demonstrated on a real synchronous machine. This machine operates as a noninterruptible backup power system. The original power fluctuations were up to 50% of the nominal power of the machine. With the described control, a sevenfold increase in the damping of fluctuations caused by grid frequency variations has been achieved.
Unbalancing the real power in power system leads to fluctuation in system frequency which can cause the several negative effects on performance and reliability of the interconnected power system. Therefore, to deal this the load frequency control (LFC) of a three-area asymmetric thermal power system integrated with a solar thermal power plant (STPP), a realistic dish-stirling solar thermal system (DSTS), and an accurate high voltage direct current (HVDC) link is presented in this work. For the suggested system, a novel cascade controller called fractional-order proportional-integral and integral-double-derivative with filter (FOPI-IDDN) is designed. By minimizing a newly proposed performance index called the HPA-ISE, and adjusts the controller and other system model parameters using a meta-heuristic method called the crow search algorithm (CS). When comparing the system dynamics, it was found that the suggested FOPI-IDDN controller outperformed the FOPI, PIDN, and FOPIDN controllers. The findings of this study show that HPA-ISE shows approximately 30 % and 60 % improvements in settling time (ST) and peak overshoots (POS) for frequency response, and 32% and 18 % improvement for the tie power responses in terms of ST and POS over ISE criteria. Also, studies on different area capacity ratios have shown that a system connected to a greater capacity ratio operates better. The realistic DSTS system with fixed and recurring insolation in area-1 and area-2 outperforms the others, according to experiments using different DSTS insolation. Also, it is discovered that the parallel AC-AHVDC link study is superior to the AC and HVDC connection research. Moreover, it seems from the sensitivity study that the CS-optimized FOPI-IDDN controller improvements obtained under normal settings are consistent across a wide range of changes.
The electric field distribution of insulator surface is nonuniform, and the maximum electric field is visible around two terminals of the insulator. Using a microvaristor layer is one of the methods of field control that can reduce the electric field stresses to prevent an extension of discharges on the insulator surface and a complete flashover caused by the subsequent development of arcing. This study targets the effect of zinc oxide (ZnO) microvaristors on the electric field distribution along the contaminated and clean composite insulators that have been investigated. In addition, the impact of the insertion of microvaristor layers on the critical flashover voltage (CFO) of the insulators through a mathematical formula has been presented for the first time. The estimation of electric field distribution is conducted through finite element method (FEM) on a 400 kV insulator using COMSOL Multiphysics, in which the optimal dimensions of the microvaristor layer were obtained using the accelerated particle swarm optimization (APSO) algorithm. Then, for the first time, the analysis of the influence of the ZnO insertion on the transient performance of the insulator, i.e., the outage rate of the network, is performed in EMTP software for the insulator with the optimized insertion of the microvaristor layer. Modelling techniques were used to simulate the components of a transmission network according to the valid models. Finally, by setting different values for CFO, Monte Carlo simulation, and linking EMTP and MATLAB software, the lightning flashover rate (LFOR) and the failure risk (F.R.) of the different insulator models are calculated. It is shown that the proposed method reduces the maximum electric field of the inside and outside of the insulator, which in turn leads to a reduction in the outage rate of the power network and the insulation risk of the insulator, and an increase in CFO of the insulator.
We prepared a perovskite material, copper-doped strontium titanate (Cu-SrTiO3), using the chemical bath deposition method and cast it on a CuFeO2/Cu photoelectrode to generate hydrogen from sanitation water splitting. This preparation method considers a simple mass product and does not depend on complex techniques. The prepared perovskite materials had a compact nano-/microstructure. Both CuFeO2 and Cu-SrTiO3/CuFeO2 exhibited excellent optical properties, with bandgap values of 1.4 and 1.26 eV, respectively. Here, the prepared CuFeO2 and Cu-SrTiO3 thin films are used as photoelectrodes for hydrogen generation, and their current-voltage relationship is analyzed under various conditions, such as different light intensities, wavelengths, and temperatures. This approach is promising for using wastewater as a source of hydrogen gas without requiring any additional electrolyte, making it a dual-purpose approach for both hydrogen generation and wastewater treatment. Through the electrochemical study, increasing the light intensity from 25 to 100 mW.cm-2 resulted in a corresponding increase in the produced J ph values from -1.02 to -1.292 mA.cm-2. Similarly, the J ph values increased from -1.25 to -1.91 mA.cm-2 as the temperature increased from 30 to 70°C. We also calculated all thermodynamic parameters, the quantum efficiency (QE), and incident photon to current conversion efficiency (IPCE). For the Cu-SrTiO3/CuFeO2/Cu photoelectrode, the activation energy ( E a ) value was 14.14 kJ mol-1, while the Δ H ∗ and Δ S ∗ values were 11.46 kJ·mol-1 and 34.9 kJ-1·mol-1, respectively. Additionally, the IPCE value was 3.31%. The prepared photoelectrode showed high stability and low cost, making it a potential candidate for industrial applications.
In this study, the influence of design factors (concentration of Fe3O4 nanofluid (NF), mass flow rate, FPDASC height, and emissivity of the receiver) of flat plate direct absorption solar collector (FPDASC) using Fe3O4 NF was investigated using the CFD (computational fluid dynamics) method. As a result, when the concentration of Fe3O4 NF increases up to 0.1 wt%, the thermal and exergy efficiencies increase by 0.773 and 0.0293, respectively, due to the increased optical absorbance. Increasing the mass flow rate of Fe3O4, NF decreases the outlet temperature; however, thermal efficiency increases due to reduced heat loss and improved heat transfer. Moreover, there is little effect on the irreversibility of the FPDASC due to the Bejan number with almost one, although the mass flow rate increases the pressure loss. The increasing height of the FPDASC and the emissivity of the receiver improve the thermal and exergy efficiencies in the case of water with low optical absorbance. In contrast, the increasing height of the FPDASC and the emissivity of the receiver decrease the thermal and exergy efficiencies when the optical absorbance is high (0.1 wt% Fe3O4 NF).
Accurate determination of photovoltaic (PV) parameters holds immense significance for ensuring the reliability of solar system operations, uninterrupted power supply for load consumption, and efficient control and management of energy sources. I-V curves transform parameter extraction into a nonlinear optimization problem supported by the I-V data points in the PV model to characterize the PV model macroscopically. Therefore, this paper proposes a novel parameter extraction model using the Q -learning-based multistrategy improved shuffled frog leading algorithm (CRNSFLA). During the evaluation process of the proposed algorithm, the colony predation algorithm (CPA) is utilized to expand the search range of the worst individual, which is no longer confined to the line segment range between the current and best values. In the later stage of evaluation, the optimal individual serves as the starting point and is applied to the Nelder-Mead simplex (NMS) for forming a simplex to mine higher-quality solutions. Besides, the simplest reinforcement Q -learning allows for a reasonable switch between these two mechanisms. A reasonable balance between exploration and exploitation trends is ensured while making full use of the advantages of both according to the reward and punishment mechanisms. The comprehensive test results under various optimization functions, different PV models, and environmental conditions demonstrate that the proposed algorithm is more advantageous than existing algorithms for parameter extraction problems. Specifically, CRNSFLA had RMSEs of 9.8602E-04, 9.8248E-04, and 9.8248E-04 in the single-diode model (SDM), double-diode model (DDM), and three-diode model (TDM), respectively. Moreover, compared with the original shuffled frog leading algorithm, the CRNSFLA showed significant improvements in 62% of the optimization functions. Therefore, CRNSFLA can be considered an effective tool for solar cell parameter extractions.
The farming sector like any other industry needs to be decarbonized. Hence, it is essential to meet the energy demands of the farms by adopting energy systems with a low-carbon footprint. Depending on the weather conditions, heating or cooling is needed. Within this context, this study presents a new hybrid renewable decentralized energy system that is designed to satisfy the requirements for heating, cooling, and electricity of a smart farm in South Korea. The under-investigation energy system comprises solar PV arrays, heat pumps, thermal energy storage tanks, and a wood pellet boiler. This study is the first to conduct an inclusive techno-enviroeconomic assessment of such a hybrid energy system by utilizing actual meteorological data on an hourly basis. This enables the model to be dynamic and facilitate accurate and reliable assessments. The modelling efforts have been performed in Aspen Plus and MATLAB to investigate the thermodynamic behaviour of the system. The investigation shows that the proposed system has achieved a daily average temperature of around 23.9°C inside the farm throughout the year with a standard deviation of 2.16°C. For the economic assessment, the levelized cost of energy has been selected as the main economic indicator, and this has been estimated at $0.218/kWh. It is found that the PV panels and the biomass boiler dominate the capital expenditures, and the biomass feedstock is the major contributor to the operating expenditures. Further, the proposed energy system reduces CO2 emissions, by up to 88.94%, when compared to conventional fossil-based energy systems. The outcomes of this study represent a holistic evaluation for such a low-carbon hybrid energy system when applied to greenhouses in Korea and in similar locations.
A flexible piezoelectric nanogenerator (PENG) was developed to convert ambient mechanical energy into electrical energy. Highly crystalline template-free zinc oxide (ZnO) microrods were prepared using a wet chemical method at a low temperature. As-synthesized ZnO microrods were blended with polyvinylidene fluoride (PVDF) to prepare a piezoelectric composite film using the supersonic spraying method. A PENG electrode comprising ZnO microrods (0.5 g) produced 15.2 V under a tapping force of 20 N at 5 Hz. In addition, an output current of 32 μA was produced with a maximum power density of 12.5 μW cm–2. The output voltage considering various body movements was investigated to demonstrate the flexibility and durability of the proposed PENG. Furthermore, the supercapacitive properties of ZnO/reduced graphene oxide were studied.
The air-based photovoltaic-thermal collector (PVTC) is a system that can generate electricity and heated air simultaneously from solar energy. This study investigates the electrical and thermal performances of an air-based single-pass double-flow photovoltaic-thermal collector (SPDFPVTC) coupled with a nonuniform cross-section rib (NUCSR) under various operating conditions. The rib is installed at the rear of the photovoltaic panel to enhance the heat transfer performance between the photovoltaic panel and the flowing air. Based on the energy balance equations, a mathematical model of the proposed SPDFPVTC is established and validated by experimental results. The solar intensity, air mass flow rate, and wind speed are selected as operating conditions. The effects of these operating conditions on the electrical and thermal performance of the SPDFPVTC have been discussed. In addition, this study evaluates the daily performance of SPDFPVTC with and without NUCSR. The average electrical, thermal, and overall efficiency were 17.59%, 43.96%, and 61.55%, respectively, for SPDFPVTC with NUCSR and 16.97%, 38.87%, and 55.83%, respectively, for SPDFPVTC without NUCSR. Consequently, installing NUCSR could enhance the daily electrical, thermal, and overall energy output of SPDFPVTC by 4.33%, 13.23%, and 10.63%, respectively.
Energy decision-makers have considered solutions to meet the demand for affordable and highly reliable energy due to population growth and technological advancement. One of these possibilities is the utilization of several energy carriers in one system as an energy hub. Instead of optimizing a single energy carrier, the energy hub optimizes a system with many energy carriers, including electricity, natural gas, and local heat, by use of its converters and storages. In this paper, a novel and new general framework is proposed to evaluate and compare both series and parallel connections of n hub to analyze cost and reliability aspects by considering coupling matrices. In order to compare the outcomes of the connections of several comparable hubs in both series and parallel modes, new indices are proposed and evaluated from the aspect of evaluating the amount of energy not supplied and the amount of energy input to each hub. Additionally, simulations are run for a variety of scenarios in order to better assess the proposed model and investigate each type of connection by evaluating the proposed performance indices. The results show that in all the examined scenarios, the total cost of the energy carriers in the series mode (link in the output) is lower than in the parallel mode (link in the input).
Hierarchical porous silica-supported nickel catalysts modified with different amounts of lanthanum (La) were synthesized via “one-pot” method using cetyltrimethylammonium bromide as template, urea as precipitant, and tetraethyl orthosilicate as silica source. Their catalytic performances were evaluated in dry reforming with methane under different conditions (La loading, reaction temperature, and time on stream). The synthesized and spent catalysts were extensively characterized by ICP, physisorption, chemisorption, XRD, TPR, XPS, HAADF-TEM, TPH, Raman’s spectroscopy, and TG analysis. The impact of lanthanum amount on the catalytic performance, sintering, and carbon deposition was discussed. Compared to unmodified catalyst, La promoter induced the nickel nanoparticles with larger crystallite sizes and weakened the metal-support interaction as well as the formation of 1 : 1 nickel-phyllosilicate, leading to the metal sintering increasing in the order Ni1.5La/SiO2 < Ni3.0La/SiO2 < Ni4.5La/SiO2. The modified catalysts exhibited better carbon resistance, which was significantly enhanced with increasing La content. Despite this, the stability increased following the sequence of Ni3.0La/SiO2 < Ni4.5La/SiO2 < Ni1.5La/SiO2. Ni1.5La/SiO2 displayed the best stability at 750°C within 10 h stability test, with CH4 conversion dropping from 61.3 to 58.0%. The deactivation reason for Ni1.5La/SiO2 was mainly the carbon deposition, while that for Ni3.0La/SiO2 and Ni4.5La/SiO2 was the metal sintering. These results emphasized that the activity and stability in the NiLa/SiO2 catalysts for the dry reforming of methane depended on two important factors, the metal-support interaction and the particles size of nickel, providing the necessity and sufficiency to balance two attributes.
In this study, untethered nanotextured thermopneumatic soft actuators (UTPSAs) were developed using a soft elastomer body encapsulating a volatile fluid (Novec 7000), which underwent a phase change (evaporation) when stimuli that convert energy into heat were applied using wireless transmission. Herein, we analyzed three types of stimuli: (i) thermal blowing, (ii) irradiation with infrared light, and (iii) electromagnetic energy transmission. In the third case, an electromagnetic field induced an electric current in a wire coil embedded in an elastomeric body, thus providing Joule heating to induce fluid evaporation. The bending curvature and force generated during bending were examined under various operational conditions, which enable one to select the optimal operating mechanism of UTPSAs for a specific environment. Specifically, diverse operating capabilities of UTPSAs are expected to be useful in dynamic environments, e.g., rescue situations. In addition, as a potential application, a crawler-configured UTPSA was fabricated, and its operation was demonstrated.
This paper presents a mathematical model of 255 kW grid-connected solar photovoltaic (SPV) system. To study the performance characteristics of the grid-connected SPV system, a new hybrid adaptive grasshopper optimization algorithm with the recurrent neural network (AGO-RNN) control technique was implemented. Furthermore, the power quality at the point of common coupling (PCC) has been studied using the conventional (PSO) and proposed AGORNN controllers. The characteristics of the PV system were analyzed under varying environmental (variable irradiance & temperature) conditions considering 3 different cases such as(i) standard test conditions (STC), (ii) variable radiation with constant temperature, and (iii) variable radiation with variable temperature. For each case, the total harmonic distortion (THD) has been calculated using proposed AGORNN control technique, and the results were compared with particle swarm optimization (PSO) technique. The 255 kW PV model is initially developed and connected to a three-level NPC inverter an MPPT-based perturbation and observation algorithm. Later, the PV model is con-trolled by an AGO-RNN pulse width modulation (PWM) controller and is then integrated and to the main grid at PCC. The main advantage of this technique is exploited the separate DC-DC converter between the SPV module and the inverter. Finally, the proposed grid-connected SPV system was simulated on MATLAB for analyzing the performance of the system based on its I-V, P-V characteristics, inverter voltage, grid power, gird voltage, grid current, power factor, and THD under different environmental conditions. The simulation results demonstrate that the current magnitude and THD of the SPVGC system are improved with the cutting-edge AGO-RNN controller compared to PSO in all three different scenarios, and this value is less than 1.6%, which is within the permitted limits of IEC 61727 standards.
The flow boiling heat transfer performance of R22 and R407c, in a microfin tube with a helix angle of 22°and an apex angle of 48°, was evaluated in a study. The study is aimed at investigating the impact of heat flux, mass flux, saturation temperature, and vapor quality on the heat transfer coefficient during flow boiling. Two different saturation temperatures, 293.15 K and 313.15 K, were used in the experiments, with heat fluxes ranging from 25 to 85 kW.m-2 and mass fluxes ranging from 150 to 350 kg.m-2 .s-1. To validate the experimental data, the results were compared with existing correlations for microfin tubes. The calculated error margin among all correlations with the experimental dataset, which ±15% and ±30%, was also matched by 85% and 95% of the datasets, respectively. Findings reveal that at lower saturation temperatures, the average heat transfer coefficients augmented with increasing mass flux. The study also found that R22 has a higher heat transfer coefficient than R407c at low saturation temperatures due to its stronger thermal conductivity and lower viscosity.
While energy production is highly dependent on fossil fuels, which consider the main source of global warming, biofuels would play a significant impact in diminishing such warming. In this paper, biooils were extracted from inedible seeds (Jatropha and Castor) using different continuous devices (solvents, screw presses, and hydraulic press-machines), aiming to achieve the highest oil’s yield of improved extraction properties at reduced time and energy. A wide range of engine speeds of 35, 60, 85, 110, and 135 rpm and preheating temperatures of 100, 125, 150, 175, 200, and 250°C were extensively studied to find their impact on the extraction properties. Results proved the ability of the screw press machine to extract the highest biooil yields from Jatropha and castor seeds. The optimum yield of Jatropha and castor were achieved at an extraction temperature range of 150-175°C at a motor speed of 135 rpm and a temperature range of 200-250°C at a motor speed of 35 rpm, respectively. Noteworthy, the yield of extracted castor oil is potentially solidified at low temperatures <100°C, leading oil samples to become like a dough. In contrast, lowering the temperatures of the Jatropha seeds improved the physical and chemical properties of the extracted oil. At a certain temperature (e.g., 100°C), the properties of both extracted and diesel oils are quite similar, which can be used directly in diesel engines.
Sulfonated poly(phenylene-co-arylene ether sulfone) multiblock copolymers are synthesized via Colon’s nickel-mediated cross-coupling reaction and are investigated as a proton-exchange membrane fuel cell. To investigate the influence of the fluorine moieties on the membrane properties, two different membranes are prepared, one containing a fluorinated hydrophobic poly(arylene ether) block (6F polymer membrane) and a nonfluorinated biphenyl (BP) polymer membrane. The proton transport, morphology, mechanical properties, and oxidative stabilities of the membranes are examined in relation to the ion-exchange capacity (IEC). 6F polymer membranes show superior proton conductivity and oxidative stability (results of Fenton’s oxidative stability and hydrogen peroxide exposure tests) compared with the BP polymer membranes. In water at 25°C, 6F and BP polymer membranes with IEC 2.0 meq g–1 exhibit proton conductivity of 0.11 S cm–1 with 6F having 16% lower water uptake than BP polymer. Meanwhile, at 30% RH and 80°C, 6F-X5Y9-(2.0) exhibits proton conductivity of 0.0026 S cm–1 that almost 50% higher than BP-X5Y7-(2.0) with 0.0018 S cm–1, while at 90% RH and 80°C, both polymers have an almost similar value of 0.10 S cm–1. Oxidative stability with the Fenton test under harsh conditions demonstrates that 6F-X5Y9-(2.0) has an extent degradation of 26%, almost 19% lower than BP-X5Y7-(2.0) with 32%, and the hydrogen peroxide exposure test demonstrates that 6F has 50% lower extent of degradation than BP with 5 and 9%, respectively. Fuel cell performance test at 80°C and 100% RH show that 6F-X5Y9-(2.0) exhibits a current density of 1.6 A cm–2 at 0.6 V (hydrogen/air) and outperforms Nafion-NR211 and BP-X5Y7-(2.0), 1.4 A cm–2 and 1.2 A cm–2, respectively. Undoubtedly, incorporating fluorinated moieties could enhance proton transport properties and oxidative stability favorable for fuel cell application.
The currently implemented indiscriminate subsidy policy in China is difficult to provide effective incentives for a firm’s investment behavior because it does not take into account the differences in resource characteristics. Thus, this paper puts forward a type of differentiated subsidy that considers resource conditions, consisting of a basic guaranteed subsidy and a variable incentive subsidy. First, from the perspective of the economic efficiency of enterprises, the amount of basic subsidy required by enterprises is calculated by the discounted cash flow method. Then, from the government’s perspective, a variable incentive subsidy amount is calculated by establishing an expectation benefit maximization function using principal-agent theory. The case application shows that due to the superior resources and development conditions of the Fuling block, it requires a significantly smaller subsidy amount than the Weiyuan block which verifies the need to consider regional differences in the design of shale gas development subsidies.
The aim of the current study is to investigate the combustion, performance, and emission characteristics of a diesel engine adopting graphene nanoplatelets and 10% v/v dimethyl carbonate as fuel additives in a 30% biodiesel and 70% diesel blend. The novel findings are documented in the subsequent sections. The surface modification of graphene nanoplatelets using a lipophilic surfactant was used which gave highest stability in fuel samples which is a main distinctive in this research work. Nanofuels were prepared using 30, 60, and 90 ppm concentrations of nanoparticles through ultrasonication. The behaviour of graphene nanoplatelet was characterized using field emission scanning gun-electron microscopy, high-resolution transmission electron microscopy, Fourier transform infrared, and X-ray diffraction. A diesel engine having uniform speed of 1500 rpm was used for the experiment at various load conditions to assess the engine operating parameters for all the prepared samples, including baseline diesel. It was observed that the combustion characteristics were found to be greatly enhanced, such as cylinder pressure and heat release rate, increased by about 15.45% and 9.63%, respectively, for B30GNP60DMC10 sample than diesel at higher loads. Performance parameters such as brake thermal efficiency (elevated by 8.98%) and brake-specific fuel consumption (diminished by 25.54%) have been significantly analyzed and compared to diesel. While the emissions (such as hydrocarbons and carbon monoxide) were found to be reduced by 22.87% and 25.67%, respectively, for B30DMC10, the nitrous oxide and smoke opacity were also reduced by 9.57% and 12.4%, respectively, for the B30GNP60DMC10 sample. Hence, a combining operation of graphene nanoplatelets and dimethyl carbonate additives in a biodiesel blend presented great potential in terms of performance improvement and reduction in emission parameters in diesel engine.
In modern chemical engineering, various derivative-free optimization (DFO) studies have been conducted to identify operating conditions that maximize energy efficiency for efficient operation of processes. Although DFO algorithm selection is an essential task that leads to successful designs, it is a nonintuitive task because of the uncertain performance of the algorithms. In particular, when the system evaluation cost or computational load is high (e.g., density functional theory and computational fluid dynamics), selecting an algorithm that quickly converges to the near-global optimum at the early stage of optimization is more important. In this study, we compare the optimization performance in the early stage of 12 algorithms. The performance of deterministic global search algorithms, global model-based search algorithms, metaheuristic algorithms, and Bayesian optimization is compared by applying benchmark problems and analyzed based on the problem types and number of variables. Furthermore, we apply all algorithms to the energy process optimization that maximizes the thermal efficiency of the steam methane reforming (SMR) process for hydrogen production. In this application, we have identified a hidden constraint based on real-world operations, and we are addressing it by using a penalty function. Bayesian optimizations explore the design space most efficiently by training infeasible regions. As a result, we have observed a substantial improvement in thermal efficiency of 12.9% compared to the base case and 7% improvement when compared to the lowest performing algorithm.
SnSe2, a layered posttransition metal chalcogenide, has attracted attention as a high-efficiency thermoelectric material owing to the intrinsic low thermal conductivity. Herein, a series of Sn S e 1 − x T e x 2 ( x = 0 , 0.025, 0.0375, 0.075, 0.1, and 0.125) samples was synthesized to examine the influence of Te doping on electrical, thermal, and thermoelectric properties of n -type SnSe2 alloys. Interestingly, carrier concentration and mobility were simultaneously increased for x = 0.025 and 0.0375. Therefore, electrical conductivity is increased for x = 0.025 and 0.0375 compared to that for the pristine sample, resulting in power factor increase to 0.25 mW/mK2 for x = 0.025 by 12% at 790 K. However, reductions in the electrical conductivity were observed for the samples with x > 0.0375 due to the decrease in carrier mobility for x > 0.0375 , resulting in the decrease of power factor. The lattice thermal conductivity slightly reduced for the doped samples owing to point defects of Te and vacancies originating from Te doping. Consequently, the thermoelectric figure of merit ( z T ) was increased to 0.45 and 0.49 for Sn(Se1.975Te0.025)2 ( x = 0.025 ) and Sn(Se1.9625Te0.0375)2 ( x = 0.0375 ) samples at 790 K, respectively, which was enhanced by 40% and 53% compared to that for undoped SnSe2. The enhanced electrical transport properties were validated by weighted mobility, density-of-state effective mass, and quality factor, and the reduction of the lattice thermal conductivity is analyzed by the Debye-Callaway model.
A 3D-printed multicoupled piston-type cylindrical triboelectric nanogenerator (MPC-TENG) that utilizes contact-separation and lateral-sliding operational modes to harvest rotational motion and convert it into electricity was proposed. The electrical performances of the fabricated four similar piston-type cylindrical TENGs (PC-TENGs) were systematically investigated. TENGs in general produce electricity in an alternating-signal form which may not be used to directly power electronic devices. Therefore, all the individual PC-TENGs were connected with a simple external filter circuit to obtain direct current (DC) electrical output, and further, they were parallelly connected to increase the overall electrical output from the MPC-TENG. The MPC-TENG consists of four PC-TENGs and produces a DC electrical output of ~40 V and ~12.5 μA at 380 rpm. Furthermore, the MPC-TENG was attached to wind cups to harvest wind energy and a Pilton wheel to harvest hydrokinetic energy, respectively. The harvested energy was stored in energy storage devices to power various small-scale electronic gadgets. Furthermore, a real-time self-sustaining alarm combined with the MPC-TENG was demonstrated to detect unauthorized human/wild animal entry into a protected region. This work also shows that the DC electrical signals from the proposed MPC-TENG can be further increased by combining more PC-TENG devices.
There is a desperate demand for efficient energy storage systems to fulfill future energy demands. Herein, we exemplify a facile solvothermal approach followed by heat treatment to synthesize NiO/g-C3N4 nanocomposites for enhanced supercapacitor applications. The molar ratio of g-C3N4 is varied to achieve numerous nanostructures like nanoparticles and nanorods with optimum specific capacitance. Further, all as-prepared electrode materials are examined for supercapacitor application. The electrochemical behavior of prepared NiO/g-C3N4 nanocomposites is carried out under cyclic voltammetry (CV), galvanostatic charge-discharge (GCD), and electrochemical impedance spectroscopy (EIS) in a three-electrode cell under different electrolytes such as aqueous sodium sulphate electrolyte (1.0 M Na2SO4) and potassium hydroxide electrolyte (3.0 M KOH). Among all the electrode materials, NO-4 (1 : 2) shows the highest specific capacitance of 338.68 F/g at a scan rate of 2 mV/s and 161.3 F/g at a current density of 1 A/g in 1.0 M Na2SO4 electrolyte. Also, this electrode material shows 95.22 F/g at a scan rate of 2 mV/s in 3.0 M KOH electrolyte. The excessive specific capacitance of this electrode material is due to retarded charge transfer resistance in the interface at the electrode and electrolyte and a increased number of active sites. The investigation of the electrokinetics of all the prepared electrodes was also carried out, and it revealed the charge storage contribution of capacitive and diffusive parts which levitates the higher specific capacitance. The two-electrode study for evaluating supercapacitor performance is studied. The NO-4//NO-4 SSD in 1.0 M Na2SO4 electrolyte shows 18.23 F/g at a specific capacitance of 1 A/g with a corresponding energy density of 10.13 Wh/kg and a power density of 1.01 kW/kg, respectively.
Semiconductor catalysts play a potential role for efficient electrocatalytic hydrogen production. In this work, copper bismuth oxide (CuBi2O4) nanostructures were synthesized via the coprecipitation method using two different Cu precursors: one is Cu(NO3)3·9H2O and the other is CuCl2. When using Cu(NO3)3·9H2O, the sample showed an interconnected and aggregated irregular spherical CuBi2O4 nanoparticle structure. On the other hand, the CuCl2-derived CuBi2O4 sample exhibited an interconnected ultrathin nanoflake structure. The CuBi2O4 nanoflakes displayed a higher electrochemically active surface area (160 cm2) than the CuBi2O4 nanoparticle (116 cm2). Accordingly, the CuBi2O4 nanoflakes revealed an excellent hydrogen evolution reaction performance with a low Tafel slope (117 mV/dec) and a small overpotential (384 mV at 10 mA/cm2 in 1 M KOH). These results specify that the CuBi2O4 nanoflakes are a suitable electrocatalyst material for high-performance water splitting.
The intimidating level of anthropogenic CO2 in the atmosphere responsible for global warming and erratic weather conditions needs to be addressed on a priority basis. Different kinds of materials were used to capture CO2 to curtail the alarming and drastic effects of global warming. An ionic liquid (IL) 1-butyl-3-methylimidazolium methanesulfonate [C4mim][CH3SO3] was chosen, owing to its unique and efficient characteristics required for CO2 capture. Thermos-physical characteristics such as sigma surface, sigma profile, and sigma potential are calculated from the COSMO-RS model independent of any kind of experimental or coefficient data as an input. The mandatory information required for the interaction of IL with CO2 was obtained from this model. The COSMO-RS model depends upon unimolecular quantum chemical analysis associated with statistical thermodynamics, molecular structure, and conformation. The structural confirmation of [C4mim][CH3SO3] IL was performed by FTIR, 1H NMR, and 13C NMR spectroscopic methods. Spectrochemical properties are calculated by FTIR, NMR, UV-visible, and fluorescence. Maximum CO2 solubility performed at room temperature (RT) and 45 bar was found to be ~2.7 mmol/g. The uptake of CO2 indicates the presence of sulphur-functionalized anions and bulky alkyl groups in IL’s significant affinity towards CO2. According to hysteresis-based classification, CO2 sorption and desorption follows type H3 classification, which indicates the presence of microporous and mesoporous in the IL sample. The effect of functionalized anions and alkyl groups on CO2 capture is highlighted in this study. The present study is aimed at providing a detailed overview related to theoretical and experimental study and application in terms of CO2 capture of IL.
This study uses numerical simulations to determine the evaporation characteristics of palm biodiesel droplets under normal gravity at temperatures ranging from 473 to 873 K and pressures ranging from 0.2 to 5 bar. A transient, two-phase, axisymmetric volume of fluid (VOF) model is employed to model transport processes across phases. The palm methyl ester is modelled as a single-component fuel with temperature- and pressure-dependent thermophysical properties. The study compares the obtained evaporation rates with those available in the literature and presents the effects of external parameters in experimental setups. Additionally, the study investigates the effects of changing the oxygen/nitrogen composition of the environment at elevated temperatures. The results show that elevated temperatures enhance the evaporation rate at all pressures and oxygen contents due to significantly enhanced thermal conductivity and droplet surface temperatures, while elevated pressures decrease the evaporation rates. Across the pressure range, evaporation rates decrease by 219%, 213%, and 196% for temperatures of 473, 673, and 873 K, respectively. Furthermore, increasing oxygen concentration in the environment can also increase the evaporation rate; however, the effect is less noticeable with a 6.4% increase at 473 K and more significant with a 27.8% increase at 873 K across the selected oxygen composition range.
Since boron nitride nanotubes (BNNTs) were first manufactured, they have gained considerable attention for their wide-scale application as reinforcing composites, piezoelectric materials, electrical insulating materials, thermal conductors, and neutron shielding materials because of their excellent mechanical, electrical, thermal, and neutron absorption properties. Despite the remarkable properties and broad application scope of BNNTs, their use has been limited because of their ineffective structural control due to the presence of one-dimensional nanoparticles. To overcome this limitation, we investigated an approach for the collective self-assembly of BNNTs by using block copolymers (Pluronic P65 and Pluronic P85) as a template and studied the BNNT-induced phase behavior of the block copolymer. For homogenous mixtures of BNNTs and block copolymers, the BNNTs were encapsulated by the in situ polymerization of surfactants (p-BNNTs), where their overall structures were confirmed by small-angle neutron scattering (SANS) and atomic force microscopy (AFM) measurements. The p-BNNTs were mixed with the block copolymers (at 50%, Pluronic P65 or Pluronic P85) by centrifugation in alternative directions to form homogeneously mixed complexes. Polarized optical microscopy (POM) and small-angle X-ray scattering (SAXS) measurements confirmed a two-dimensional hexagonal structure of the BNNTs in the block copolymer matrix that self-assembled upon heating, which can give a possibility of being used as effective piezoelectric materials for energy harvesting. Moreover, upon the addition of BNNTs, the phase behavior of the block copolymer can be controlled, allowing the formation of hexagonal, face-centered cubic, and body-centered cubic structures depending on the BNNT concentration and temperature. This study provides a new and simple method to control the collective BNNT structure.
In this study, a coal-fired power plant with an integrated S-CO2 cycle is proposed to improve the system operational flexibility. To optimize the performance, a control strategy of variable load regulation is proposed. First, a dynamic mathematical model of the system is established based on the conservation of mass and energy principles, and then, dynamic verification of the model is carried out. In order to evaluate the performance of the proposed system, an exergy analysis is performed on the S-CO2 cycle, indicating that the exergy loss rate of the heater in the cycle is the highest. Finally, the dynamic performance of the system is simulated, and the dynamic response of the power generation load is analyzed. In addition, the system is evaluated based on the performance indicator of the flexibility of the power generation. It was found that the proposed system in this paper has a large load ramp rate which can quickly follow the load response. Meanwhile, compared with load downregulation, the system has greater potential for load upregulation.
This research investigated the impacts of model prediction on the optimization of hybrid energy systems using a system consisting of solar panels, batteries, a proton exchange membrane fuel cell (PEMFC), and a chemical hydrogen generation system. A PEMFC has several advantages, such as low operating temperatures, fast response times, high power density, and environmental friendliness, and it can convert hydrogen into electricity. However, because hydrogen costs are an important consideration, the PEMFC is usually integrated with hybrid energy systems to guarantee system sustainability. Therefore, in this study, a whole-year household load and solar radiation data were applied to optimize the system components and power management, thereby reducing the system cost by 42.43% and improving system sustainability by 7.05%. The system responses showed that some hydrogen consumption might be saved if the solar and load profiles could be foreseen. Two prediction models were developed that could accurately forecast the radiation and load profiles. Next, a second-year dataset was employed to verify the effectiveness of the model prediction. The results showed that the system cost was reduced by 40.20% without model prediction and by 44.06% with model prediction compared to the original system settings. Finally, experiments to illustrate the feasibility of the hybrid energy system were conducted using prediction models. Based on the results, the model prediction was deemed effective in improving the performance of hybrid energy systems.
A study has been conducted on the electrochemical properties of 1-ethyl-3-methylimidazolium trifluoromethanesulfonate (EmimTFO) protic ionic liquid enhanced by adding potassium nitrate (2.5 M) aqueous solution. The properties of EmimTFO as well as mixtures diluted by molar fractions of 0.6, 0.7, 0.8, and 0.9 of KNO3 were also investigated through measurements of viscosity, density, and conductivity. In a three-electrode test run at 0.25 A g-1, the addition of 2.5 M KNO3 solution generated peak specific capacities of ~40.2 and ~85.8 mAh g-1 on the positive and negative potentials, respectively. These performances surpassed the specific capacities obtained for EmimTFO in a three-electrode run at 0.25 A g-1 using the same electrode material (activated carbon). The top-performing electrolyte mixture ([EmimTFO]0.8[2.5 M KNO3]0.2) was then used to assemble a symmetric supercapacitor, which could run at a voltage of ~2.1 V. The device was able to retain 71.35% of its capacitance after 10,000 cycles of charge and discharge. It also displayed higher specific energy and power of 22.21 Wh kg-1 and 520 W kg-1, respectively, at 0.5 A g-1 as compared to specific energies of 4.73 Wh kg-1 and 11.2 Wh kg-1 for the devices assembled with single EmimTFO and 2.5 M KNO3 as the electrolytes, respectively.
The widespread use of Internet-of-things (IoT) devices has inspired researchers to adopt unique material design strategies to realize efficient indoor organic photovoltaic (OPV) systems. However, despite acceptor halogenation being an effective strategy for modulating OPV properties, studies on the systematic examination of nonfullerene acceptor- (NFA-) OPVs under dim indoor light using the halogenation approach are scarce. This study evaluates the performance of NFA-OPVs under indoor light by employing a halogenation approach with Y6-derivatives. The choice of the chlorination or fluorination unit in an NFA significantly affects the indoor performance of OPVs. The champion OPV devices with a chlorinated acceptor demonstrated excellent power conversion efficiency (PCE) of 25.5% compared to that of the fluorinated acceptor (PCE: 22.5%) under 1000-lx light-emitting-diode (LED) illumination. Moreover, suitable energy levels, satisfactory spectral matching, and improved surface morphology of the chlorinated acceptors resulted in the excellent indoor performance of the OPVs. In addition, acceptor chlorination resulted in high crystallinity and planarity, which facilitated suppressed trap-assisted recombination and low open-circuit voltage (VOC) loss of OPV devices in an indoor environment.
One of the essential challenges of tandem solar cells is designing and adjusting the current-matched tandem structures with high efficiency and stability. Nitride-based wide band gap semiconductors, owing to their high stability and high resistance against the cosmic rays, are appropriate elements to apply as the top cell of tandem solar cells. On the other hand, the organic-inorganic hybrid perovskites are emerging materials with exclusive electronic properties such as tunable band gap, low cost, simple manufacturing process, and efficient charge transport properties, making them capable candidates to be used in tandem layered structures. The aim of this paper is to adjust and optimize the performance of a two-terminal tandem solar cell consisting of InxGa1-xN as the top cell and a FAPbIyBr3-y as the bottom cell. We have studied the effect of different practical parameters such as the indium molar of the top cell, iodine molar of the bottom cell, the thickness of each layer, threading dislocation density of InxGa1-xN, and surface texturing effect on the performance of the two-terminal tandem structure. Because of the prominence of current matching problem in two-terminal tandem structures, we have determined the optimum situation for maximum light harvesting along with the minimum value of current matching factor. In the optimum situation, the current matching factor of 0.15 mA/cm2 leads to the power conversion efficiency of 25.17% for the device.
Bioethanol production from cellulosic materials is important in mitigating the concomitant displacement and exploitation of
primary food crops for biofuel production and reducing carbon emissions which exacerbate climate change. The problem of
reduced yield in the production and availability of yeast locally poses a barrier to market adoption and penetration of
bioethanol. The study examined the effect of particle size and different yeast strains on the yield of bioethanol from waste
sawdust that was sourced from a local timber processing centre. The samples of yeast were prepared from baker’s yeast
(Saccharomyces cerevisiae) and palm wine yeast (Saccharomyces chevalieri). The sawdust was reduced to 212 μm, 300 μm, and
500 μm particle sizes. The samples of each particle size were pretreated and hydrolyzed with H2SO4 and fermented with S.
cerevisiae or S. chevalieri yeast. The results obtained show that the weight, pH, density, viscosity, flash point, and heating value
of the produced bioethanol ranged between 221.67 and 322.64 g, 6.2 and 6.6, 0.821 and 0.878 g/mL, 1.073 and 1.193, 14 and
C, and 20.5 and 23.1 MJ/kg, respectively, while the alcohol content of each of the samples was 69%. Furthermore, the
bioethanol yield from Saccharomyces cerevisiae yeast was 213.9 mL, 193.2 mL, and 186.3 mL, for the 212 μm, 300 μm, and
500 μm particles, while for Saccharomyces chevalieri yeast, the yield was 289.8 mL, 255.3 mL, and 220.8 mL for the 212 μm,
300 μm, and 500 μm, respectively. An ANOVA on the effect of particle size on ethanol yield shows a significant difference at
5% level of significance. The study demonstrated that the use of locally produced yeast and increasing the surface area of
sawdust increase bioethanol yield. Hence, it was concluded that better yeast strain use and biomass particle size reduction to a
level that allows the optimal surface area for the reaction improve the yield of bioethanol. The study outcome can help in
ameliorating the continued dependence on fossil fuels and the food security problems arising from displacing or utilizing food
for fuel and could also encourage commercial-scale cellulosic ethanol production from waste.
The use of covering material is an important measure to control the radon migration of uranium tailings. Radon diffusion and migration are affected by cover layer parameters, such as diffusion coefficient, overburden thickness, particle size, and ore body width. The radon reduction effect of single-layer mulching is often less than that of double-layer, and the material parameters of the cover layer are uncertain; however, they can be explained by a fuzzy dynamic equation. Firstly, the radon exhalation model is constructed with the radon percolation diffusion and migration method in a double-layer covering. Secondly, a fuzzy target of radon exhalation and a fuzzy constraint model are constructed subject to the total cost and thickness of covering material by a triangular membership function. Lastly, the models are aimed at solving the corresponding extreme value interval of the fuzzy target of radon exhalation by immune genetic algorithm, to reconstruct the fuzzy target, fuzzy constraint, and fuzzy aggregation function, where, ultimately, the optimal radon control decision can be obtained by swarm intelligence algorithm subject to different levels between possibility and importance. An example demonstrates a database of optimal decision-making schemes for double-layer coverage, and flexible management of radioactive pollutants is realized.
Nowadays, integration of renewable sources into the local distribution system and the nonlinear behavior of advanced power electronic equipment have made a large impact on the power quality (PQ). The unified power quality conditioner (UPQC) is a multifunctional FACTS device, which is a combination of both shunt active filter and series active filters via a common DC link. Presently, the artificial intelligence is playing a vital role in the development of the intelligent control methods. Traditional training methods of artificial neural network (ANN) like back propagation and Levenberg-Marquardt may get stuck in local optimal solution which leads to the invention of ANN trained optimally by metaheuristic algorithms. This paper develops a firefly algorithm-trained ANN (FF-ANNC) controller for the shunt active filter and proportional integral controller (PI-C) for the series active filter of the UPQC integrated with the solar energy system and battery energy storage via boost converter (B-C) and buck boost converters (B-B-C). The main aim of the proposed FF-ANNC is to reduce the mean square error (MSE) thereby achieving the constant DC link capacitor voltage (DLCV) during load and irradiation variations, reduction of imperfections in current waveforms, improvement in power factor (PF), and mitigation of sag, swell, disturbances, and unbalances in the grid voltage. The working of developed FF-ANNC was tested on five test studies with different types of loads and source voltage balancing/unbalancing conditions. However, to demonstrate supremacy of the suggested FF-ANNC, a comparative study with the training methods like genetic algorithm (GA) and ant colony optimization (AC-O) and also with other methods that exist in literature like PI-C, fuzzy logic controller (FL-C), and artificial neuro fuzzy interface system (ANFI-S) was conducted. The proposed method reduces the total harmonic distortion to 2.39%, 2.32%, 2.27%, 2.45%, and 2.66% which are lower than the existing methods that are available in literature. The FF-ANNC shows an excellent performance in reducing voltage fluctuations and total harmonic distortion (THD) successfully and thereby improving PF.
With the maturation of nonlinear systems, considerable endeavors have been made to provide valid and high-speed controllers to supervise superior and more complex systems. Artificial intelligence has been remembered as the head topic among designers in the last decade. One of the popular control techniques is fuzzy logic, which is known to provide a controller that simulates the behavior of an expert operator. On the other hand, due to the necessity of change in human energy sources and the popularity of solar energy, attention to the greatest utilization of this category of green resources has significantly increased. Maximum power point tracking (MPPT) in solar systems is a headed topic, with innovative methods being presented every day despite numerous articles. However, the less discussed topic is the choice of a fuzzy inference system. In this article, the two classes of Mamdani and Sugeno are discussed to introduce the best controller for extracting more power from a solar system by implementing both types and gaining an understanding of their differences. In addition, the influence of the number of input membership functions on the controller performance is investigated. Therefore, two different input membership functions are given to each fuzzy system model. It should be noted that fuzzy system setup has been done by genetic algorithm to respond to the mortal desire to automate various processes, which is a subset of artificial intelligence. Accordingly, four different fuzzy systems have been designed and implemented on a solar system. The results were tested and summarized in various radiations in MATLAB Simulink.
The design and efficient synthesis of oxygen redox electrocatalysts possessed with high activity are of the essence for advanced rechargeable Zn-air batteries (ZABs). In particular, porous architectures composed of transition metal compound and carbonaceous material have attracted significant attention owing to their enhanced electrocatalytic activity. This study reports the fabrication of metal-free N and S co-doped porous CNT microspheres (3DNSCNT) via spray drying and subsequent post-treatment. Moreover, to hybridize with metal phosphide, CoP nanoparticles are uniformly decorated on the microspheres (3DNSCNT/CoP) by the hydrothermal method and phosphidation treatment. Due to the effect of the combination of the porous architecture inside the entangled 3DNSCNT and uniformly deposited CoP nanoparticles, 3DNSCNT/CoP exhibits superior bifunctional electrocatalytic activities for oxygen redox reaction in 0.1 M KOH electrolyte compared with noble metal-based catalysts like Pt and Ru. Furthermore, as an air cathode for ZABs, 3DNSCNT/CoP exhibits a high-power density (177 mW cm-2), low polarization overpotential, and durable cycle performance (200 h).
Higher-order neutron fluxes (i.e., higher-order harmonics) are widely applied in perturbation theory and modal kinetics, and they are important for research on the physical characteristics of accelerator-driven subcritical reactors (ADSRs). This paper presents a computational scheme for reconstructing the neutron flux in the steady state according to the biorthogonal properties of the forward and adjoint neutron fluxes, which can be used to analyze how higher-order harmonics affect the steady-state neutron flux under λ-and prompt α-modes. Simulation results indicated that a modal synthesis method based on λ-and prompt α-modes can effectively reconstruct the steady-state neutron flux and core power in an ADSR with a power reconstruction accuracy of within 5%. The higher-order harmonics can be classified into three types according to their physical characteristics: the first type contributes significantly to the steady-state neutron flux, the second type contributes almost nothing to the steady-state neutron flux, and the third type contributes nothing to the steady-state neutron flux. The external neutron source contributes only to specific harmonic expansion orders, which are characterized by significant axial and radial symmetry for both the λ-and prompt α-modes.
The experiment was carried out on Broad Breasted Bronze and medium white turkey at National Agriculture Research Center, Khumaltar, Lalitpur from May 20 to July 22. The effect of treatment was analyzed using one-way ANOVA to study the Breed and season effect on turkey production. Three toms including 2 Bronze and 2 White along with 9 hens including 4 Broad Brested Bronze and 5 Medium White were used in the experiment. Completely randomized Design (CRD) was employed to investigate and compare the Artificial insemination and Natural breeding condition in Turkey birds. The total number of birds (n =28) used for the study were randomly allotted to 3 treatments (3x3) factors replicated 3 times in each unit. The experimental research was factorial with different level of semen volume: 0.3 ml, 0.4 ml and 0.5 ml made available from the Black Tom, weight and semen count. Data were analyzed for descriptive statistics between the variables were analyzed using R programming. The statistically significant means were then compared using Duncan's Multiple Range Test (DMRT). The majority of the data shows non-significant results in terms of semen volume, weight of Tom, semen count, egg-weight, and egg number (p>0.05). Therefore, thorough further research and the publication of research articles corroborating the aforementioned findings can open many doors to new breeding methods for Turkey bird species that are both advised and efficient.
Electrolysis is a promising approach for biodiesel production. However, low electrical conductivity of a reaction mixture results in a low reaction rate. Thus, this study developed a novel catalyst-free electrolysis process using an ionic liquid as a supporting electrolyte for biodiesel production. Various ionic liquids were assessed, and 1-ethyl-3-methylimidazolium chloride ([Emim]Cl) exhibited the highest electrical conductivity (4.59 mS/cm) and the best electrolytic performance for transesterification. Electrolysis in the presence of [Emim]Cl was subsequently optimized using response surface methodology to maximize biodiesel yield. A maximum biodiesel yield of 97.76% was obtained under the following optimal reaction conditions: electrolysis voltage, 19.42 V; [Emim]Cl amount, 4.43% (w/w); water content, 1.62% (w/w); methanol to oil molar ratio, 26.38 : 1; and reaction time, 1 h. Notably, [Emim]Cl could be efficiently reused for at least three cycles with a corresponding biodiesel yield of 94.81%. Moreover, the properties of the synthesized biodiesel complied with EN and ASTM standards. The findings of this study indicate that catalyst-free electrolysis using [Emim]Cl as a supporting electrolyte is an eco-friendly and efficient method for biodiesel production.