Search

The current research is conducted with the aim of investigating a multi-generation energy system (MGS) for electricity, hydrogen, heating, cooling and hot water production using SRC, Kalina cycle and proton exchange membrane (PEM) electrolysis as the main subsystems. The thermodynamic analysis namely energy, exergy, and exergo-economic examination carried out. Analysis for each component is done after thermodynamic modeling. The exergy investigation showed that regenerator 2, vapor generator and condenser had the highest exergy destruction rate, respectively. A comparison was made between the current work and the basic system, and according to the results obtained, the system's ability to produce electricity, cooling, heating and hydrogen are calculated as 782 kW, 173.2 kW, 2265 kW and 0.01613 mol/day, respectively. Also, the energy and exergy efficiency of the proposed system increased by 3.13% and 5.37%, respectively. The optimization based on PSO method was carried out. The results of PSO optimization represented that in the case exergy destruction and exergy efficiency will be the optimization target these two outputs can reach the value of 2208 kW and 9.84%, while optimization based on exergy efficiency and production cost rate will lead to 9.86% and 166.6 $/h. • Simulation a CSP based system to design a poly-generation energy system. • Using PEM electrolyzer to generate hydrogen as an energy storage media. • The exergy efficiency of introduced system is 3.13% higher than basic system. • The output power of new plant is 1.54 MW higher than basic cycle. [ABSTRACT FROM AUTHOR]

The increasing concerns about pollutant emissions from the electricity generation sector have urged the deployment of novel and efficient technologies. In this regard, fuel cells are predicted to be essential in upcoming clean electricity generation systems. In particular, Flame-assisted Fuel Cells (FFCs) are among the new technologies and are envisaged to operate with various fuels; however, their relatively low electrical efficiency is a major drawback. The present research aims at the efficiency improvement of a methane-fueled FFC by recovering its waste heat for additional electricity generation using an Organic Rankine Cycle (ORC). To do so, a combined FFC-ORC framework is developed, and its thermodynamic performance as well as economic and environmental emission characteristics, are modeled. By implementation of parametric analysis, impacts on the performance of design/operating variables were examined. A tri-criteria optimization is also accomplished based on exergy efficiency, electricity cost, and CO 2 emission for the combined FFC-ORC and the standalone FFC. The results indicate better performance of the developed FFC-ORC over the standalone FFC in terms of efficiency and CO 2 emissions, respectively by 8.5-percentage points and 35.2%, under optimized cooperating conditions. However, the electricity cost shows an increment of 9.68% due to the additional expenditures associated with the ORC. [ABSTRACT FROM AUTHOR]

In this study, combining an excellent intrinsic property of polylactic acid (PLA) with the unique properties of three-dimensional (3D) printing technique and coating of chitosan-hydroxyapatite (CHI-HA) is used with electrospun nanofibers for the regeneration of hard tissues. This study aims to fabricate a microstructural scaffold with a PLA base by 3D fused deposition modeling (FDM) technique. High surface-to-volume ratio, high porosity, flexibility in surface performance, and exceptional mechanical performance are just a few of the characteristics that the small-diameter fibers display. Utilizing an examination from a scanning electron microscope (SEM), the morphological research is carried out. Besides, the biological reaction of the scaffolds is studied in phosphate buffer saline (PBS) and simulated body fluid (SBF). The samples are examined for wet and dry biological behavior, by SEM. Moreover, mechanical analyzes, including compressive strength and porosity, are performed on the samples and the results are evaluated in existing number models. Besides, the fuzzy modeling technique is used to forecast the properties of samples before fabricating and examining them. The results generally show that the presence of HA nanoparticles improves mechanical and biological properties. Specifically, the obtained results show that the sample with 10 wt% of HA is capable of suitable mechanical, chemical, and biological properties compared to other samples. [ABSTRACT FROM AUTHOR]

Air pollution is known as one of the most important causes of death in the whole world. Therefore, pollution reduction to achieve clean air was noticed by everyone. This way, using nanotechnology to control air and monitor is a novel approach. This paper investigates the effect of the number of graphene nano-pores on the SiO 2 separation from the H 2 O vapour in the presence of an external electric field with the magnitude of 0.01 V/Å using the molecular dynamics (MD) method. The electric field affects the charged particles and causes disturbance in the structure. It also prevents SiO 2 nanoparticles from passing through the graphene nanosheet. Also, the presence of carbon nanosheets acts as a membrane and affects the diffusion of water in the nanostructure. So, the results show that in the presence of a nano-pore, the number of H 2 O molecules reaches to 496 and 568 in reservoirs 2 and 3. Also, the number of SiO 2 nanoparticles reaches 10 and 4 in reservoirs 2 and 3. This shows that in reservoirs 2 and 3, about 80% and 60% of the SiO 2 nanoparticles are separated. As mentioned before, the electric field prevents the passage of SiO 2 nanoparticles through the graphene nanosheet. As the number of graphene nano-pores increases by 2, 3, 4, and 5, the number of passing water molecules increases. Considering that the number of graphene nano-pores has increased and the movement path of particles has increased, the number of passing particles almost increases. However, the electric field prevents the passage of SiO 2 nanoparticles. According to the results, the suggested setup can be employed for designing highly efficient nanostructured membranes for air purification and monitoring. [Display omitted] [ABSTRACT FROM AUTHOR]

In this project, the possibility of drug delivery application of three anti- Multiple sclerosis (MS) agents (containing diroximel fumarate (DXF), dimethyl fumarate (DMF), and mono methyl fumarate (MMF)) by using some heteroatom decorated graphitic carbonitride (g-C 3 N 4) (as nano-sized carriers) have been systematically investigated. The results of the study have indicated that As-g-C 3 N 4 QD is not a suitable candidate for drug delivery (at least in the cases of DMF, and DXF drugs); while, it would be an accurate semiconductor sensor for selective detection of each mentioned agents. Also, the use of the P -doped as well as pristine g-C 3 N 4 QD could lead to weak electronic signals with relatively same values (in electronvolts). It means that P -g-C 3 N 4 , and g-C 3 N 4 QDs are not good sensors for detection of each of the three considered drugs. However, those two sorbents would be suitable carriers for delivering of all three mentioned pharmaceuticals. [Display omitted] • The results of the work showed that the pristine and the P -doped-g-C 3 N 4 QDs could be used as suitable vehicles for delivery of all three considered MS drugs; while, the As-g-C 3 N 4 QD could not be applied as a control released carrier at least for those mentioned drugs. • The frontier molecular orbital (FMO) studies showed that among all the three considered QDs, only the As-g-C 3 N 4 QD could be applied as a selective semiconductor sensor for detection of all three MS drugs. [ABSTRACT FROM AUTHOR]

Studying the dynamic viscosity (DV) is a key factor to determine the nanofluids' hydrodynamic behavior (NFs). In this research, the effect of volume fraction (φ), shear rate (SR), and temperature (T) on the DV, and torque of SiO 2 nanoparticles (NPs)/ Ethylene glycol (EG) nanofluid (NF) are studied with an artificial neural network (ANN). Different machine learning (ML) models are examined to predict the rheological properties, and then the best model is selected for prediction. The results show that the torque mostly increased linearly with the SR in all samples. The slope of this enhancing trend is higher for lower T. The Gaussian Process Regression (GPR) models with the Matérn covariance function provided the best results on both datasets to predict the DV. The correlation results provided by this method to predict the DV in terms of Pearson's Linear Correlation Coefficient (PLCC), and Spearman's Rank Order Correlation Coefficient (SROCC) were 0.999 and 1, respectively. R squared (R2) was 0.996 and, the Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values of about 0.24 and 1.61 represented the accuracy and power of this method to predict the DV values unseen data by the model. The GPR torque predictor model performed very well by providing a correlation of about 0.98 and an RMSE of about 4. Matérn covariance functions that used separate length scales per predictor with ν = 3 / 2 (ardmatern 32) and ν = 5 / 2 (ardmatern52) were superior to other functions. All 100 models trained on each dataset were well-trained and quite reliable. The trained models were accurate enough to be used in related applications. [ABSTRACT FROM AUTHOR]

This study describes the mechanical behavior of a brick structure by inserting graphene nano-sheet (GNS) into this construction material using the Molecular Dynamics (MD) approach. Technically, we utilized Universal Force Field (UFF) and Tersoff Force Field (TFF), respectively, to simulate ideal brick (pristine brick) and graphene structures. The consequence of the equilibrium procedure of atomic structures indicates their suitable physical stability, which emerges from the proper MD simulation settings. Technically, to characterize the mechanical properties (MP) of pristine brick matrix (PBM) and reinforced brick-graphene (RBG) nanocomposite, some parameters like Stress-Strain (S–S) Curve, Young's modulus (YM), and Ultimate Strength (US) of a pristine compound, and reinforced structure are mentioned. Numerically, by inserting the GNS into the PBM with a 5% atomic ratio, Young's modulus of simulated nanostructure reaches 3379 MPa, and the US of brick increases to 19.14 MPa. These simulation results show the important effect of GNS on the MP of the PBM, which is suitable for construction applications such as cologne arches. • We investigated the mechanical behavior of brick structure by inserting Graphene nanosheets. • Stress-strain curve, Young's modulus, and ultimate strength of pristine compound and reinforced structure were reported. • Young's module reaches to 3379 MPa and the ultimate strength of brick increases to 19.14 MPa. • TResults show the effect of graphene nanosheets on mechanical properties. [ABSTRACT FROM AUTHOR]

[Display omitted] • The fabrication of ZnCo 2 O 4 -ZnO NSs was expanded using Polyethylene glycol. • The catalyst's properties were specified by FT-IR, SEM, TEM, XRD, and EDS analyses. • ZnCo 2 O 4 -ZnO NSs were deployed for the adsorption and elimination of asphaltene from crude oil. An advanced and eco-friendly method for the fabrication of ZnCo 2 O 4 -ZnO nanostructures (NSs), as highly effective nanocatalyst, was expanded using Polyethylene glycol (PEG) which is a new type of fuel and stabilizer. The influence of effectual elements such as the type of PEG and its quantity on the morphological features and function of ZnCo 2 O 4 -ZnO nanocatalyst was probed. The findings showed that changing the type of PEG and its amount can effectively control the dimensions, performance, and shape of ZnCo 2 O 4 -ZnO nanoparticles. The properties of produced ZnCo 2 O 4 -ZnO NSs were probed by FTIR, XRD, TGA, and, SEM, TEM. ZnCo 2 O 4 -ZnO NSs were employed as an extremely effectual recoverable adsorbent for the adsorption and elimination of asphaltene from crude oil. The existence of heterogeneity did not stop the progress. The products were effortlessly isolated from the green media, and the catalyst was employed many times without a distinguished drop in activity and selectivity. [ABSTRACT FROM AUTHOR]

[Display omitted] • The predictive PC-SAFT EoS has been utilized to predict the speed of sound, the isochoric and isobaric heat capacity of ionic liquids. • The surface area and molecular volume of the UNIFAC model have been used to estimate the segment number and hard sphere diameter. • The predictive PC-SAFT model can predict the specific isochoric and isobaric heat capacity of ILs up to high pressure, accurately. In this work, the predictive PC-SAFT EoS has been developed to predict the speed of sound, the isochoric and isobaric heat capacity of ionic liquids (ILs) over a wide range of pressures and temperatures. In this new methodology, the segment number and diameter of ILs have been estimated using the surface area and molecular volume of the UNIFAC model. The segment energy and association energy parameters have been obtained using an inverse relationship between dispersion/association energy and segment diameter. The results show that the predictive PC-SAFT model can predict the specific isochoric and isobaric heat capacity of ILs up to high pressure, accurately. In the case of the speed of sound, the model performance is acceptable by considering using no adjustable model parameters. To check the model capability, the new model results have been compared to the electrolyte PC-SAFT EoS. [ABSTRACT FROM AUTHOR]

In this study, the wave propagation and vibration analysis of sandwich structure with a bio-based flexible core and composite face sheets subjected to magnetic field are studied. In the present analysis, the material properties of composite face sheets are assumed viscoelastic based on Kelvin -Voigt model, and high-order sandwich panels theory is used for core modeling. The analysis of wave propagation and vibration of the sandwich structure is performed assuming complete adhesion between core and face sheets, and the governing equations of motion are derived by Hamilton's principle. Finally, the semi-analytical solution is applied to obtain the effects of the structural and foundation damping coefficients, different angles of the layers, the ratio of width to thickness, the ratio of the thickness of the core to the procedures, temperature variations, wave number, aspect ratios, elastic properties and number of layers on the wave propagation behavior of the sandwich plate for complete adhesion between layers. The results show that by increasing the ratio of the thickness of the core to the layers, the velocity of the wave propagation initially increases, and then decreases. Also, the application of the magnetic field has an increasing effect on the sandwich plate frequency. Finally, with the increase in the number of layers and the number of waves, the phase velocity increases, while the hardness of the system decreases when the temperature and damping coefficient rises. [ABSTRACT FROM AUTHOR]