Corrosion inhibitory effects of new synthesized compound namely 5,5'- ((1Z,1'Z)-(1,4-phenylenebis(methanylylidene))bis(azanylylidene))bis(1,3,4-thiadiazole-2-thiol) (PBB) on mild steel in 1.0 M HCl was investigated at different temperatures using open circuit potential (OCP), potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS). Results showed that PBB inhibited mild steel corrosion in acid solution and indicated that the inhibition efficiencies increased with the concentration of inhibitor, but decreased proportionally with temperature. Changes in impedance parameters suggested the adsorption of PBB on the mild steel surface, leading to the formation of protective films.
A new curcumin derivative, i.e., (1E,4Z,6E)-5-chloro-1,7-bis(4-hydroxy-3-methoxyphenyl)hepta-1,4,6-trien-3-one (chlorocurcumin), was prepared starting with the natural compound curcumin. The newly synthesized compound was characterized by elemental analysis and spectral studies (IR, ¹H-NMR and 13C-NMR). The corrosion inhibition of mild steel in 1 M HCl by chlorocurcumin has been studied using potentiodynamic polarization (PDP) measurements and electrochemical impedance spectroscopy (EIS). The inhibition efficiency increases with the concentration of the inhibitor but decreases with increases in temperature. The potentiodynamic polarization reveals that chlorocurcumin is a mixed-type inhibitor. The kinetic parameters for mild steel corrosion were determined and discussed.
This paper discusses the effect of jet impingement of water on a photovoltaic thermal (PVT) collector and compound parabolic concentrators (CPC) on electrical efficiency, thermal efficiency and power production of a PVT system. A prototype of a PVT solar water collector installed with a jet impingement and CPC has been designed, fabricated and experimentally investigated. The efficiency of the system can be improved by using jet impingement of water to decrease the temperature of the solar cells. The electrical efficiency and power output are directly correlated with the mass flow rate. The results show that electrical efficiency was improved by 7% when using CPC and jet impingement cooling in a PVT solar collector at 1:00 p.m. (solar irradiance of 1050 W/m² and an ambient temperature of 33.5 °C). It can also be seen that the power output improved by 36% when using jet impingement cooling with CPC, and 20% without CPC in the photovoltaic (PV) module at 1:30 p.m. The short-circuit current ISC of the PV module experienced an improvement of ~28% when using jet impingement cooling with CPC, and 11.7% without CPC. The output of the PV module was enhanced by 31% when using jet impingement cooling with CPC, and 16% without CPC.
Halloysite (HNT) is treated with sulfuric acid and the physico-chemical properties of its morphology, surface activity, physical and chemical properties have been investigated when HNT is exposed to sulfuric acid with treatment periods of 1 h (H1), 3 h (H3), 8 h (H8), and 21 h (H21). The significance of this and similar work lies in the importance of using HNT as a functional material in nanocomposites. The chemical structure was characterized by Fourier transform infrared spectroscopy (FTIR). The spectrum demonstrates that the hydroxyl groups were active for grafting modification using sulfuric acid, promoting a promising potential use for halloysite in ceramic applications as filler for novel clay-polymer nanocomposites. From the X-ray diffraction (XRD) spectrum, it can be seen that the sulfuric acid breaks down the HNT crystal structure and alters it into amorphous silica. In addition, the FESEM images reveal that the sulfuric acid treatment dissolves the AlO₆ octahedral layers and induces the disintegration of SiO₄ tetrahedral layers, resulting in porous nanorods. The Bruncher-Emmett-Teller (BET) surface area and total pore volume of HNTs showed an increase. The reaction of the acid with both the outer and inner surfaces of the nanotubes causes the AlO₆ octahedral layers to dissolve, which leads to the breakdown and collapse of the tetrahedral layers of SiO₄. The multi-fold results presented in this paper serve as a guide for further HNT functional treatment for producing new and advanced nanocomposites.
The advancements in material science and technology have made polyurethane (PU) one of the most important renewable polymers. Enhancing the physio-chemical and mechanical properties of PU has become the theme of this and many other studies. One of these enhancements was carried out by adding starch to PU to form new renewable materials called polyurethane-starch composites (PUS). In this study, PUS composites are prepared by adding starch at 0.5, 1.0, 1.5, and 2.0 wt.% to a PU matrix. The mechanical, thermal, and morphological properties of PU and PUS composites were investigated. Scanning electron microscope (SEM) images of PU and PUS fractured surfaces show cracks and agglomeration in PUS at 1.5 wt.% starch. The thermo-mechanical properties of the PUS composites were improved as starch content increased to 1.5 wt.% and declined by more starch loading. Despite this reduction, the mechanical properties were still better than that of neat PU. The mechanical strength increased as starch content increased to 1.5 wt.%. The tensile, flexural, and impact strengths of the PUS composites were found to be 9.62 MPa, 126.04 MPa, and 12.87 × 10(-3) J/mm², respectively, at 1.5 wt.% starch. Thermal studies showed that the thermal stability and crystallization temperature of the PUS composites increased compared to that of PU. The loss modulus curves showed that neat PU crystallizes at 124 °C and at 127 °C for PUS-0.5 wt.% and rises with increasing loading from 0.5 to 2 wt.%.
In recent years, the increasing level of CO₂ in the atmosphere has not only contributed to global warming but has also triggered considerable interest in photocatalytic reduction of CO₂. The reduction of CO₂ with H₂O using sunlight is an innovative way to solve the current growing environmental challenges. This paper reviews the basic principles of photocatalysis and photocatalytic CO₂ reduction, discusses the measures of the photocatalytic efficiency and summarizes current advances in the exploration of this technology using different types of semiconductor photocatalysts, such as TiO₂ and modified TiO₂, layered-perovskite Ag/ALa₄Ti₄O15 (A = Ca, Ba, Sr), ferroelectric LiNbO₃, and plasmonic photocatalysts. Visible light harvesting, novel plasmonic photocatalysts offer potential solutions for some of the main drawbacks in this reduction process. Effective plasmonic photocatalysts that have shown reduction activities towards CO₂ with H₂O are highlighted here. Although this technology is still at an embryonic stage, further studies with standard theoretical and comprehensive format are suggested to develop photocatalysts with high production rates and selectivity. Based on the collected results, the immense prospects and opportunities that exist in this technique are also reviewed here.
The natural dyes anthocyanin and chlorophyll were extracted from Musa acuminata bracts and Alternanthera dentata leaves, respectively. The dyes were then applied as sensitizers in TiO2-based dye-sensitized solar cells (DSSCs). The ethanol extracts of the dyes had maximum absorbance. High dye yields were obtained under extraction temperatures of 70 to 80°C, and the optimal extraction temperature was approximately 80°C. Moreover, dye concentration sharply decreased under extraction temperatures that exceeded 80°C. High dye concentrations were obtained using acidic extraction solutions, particularly those with a pH value of 4. The DSSC fabricated with anthocyanin from M. acuminata bracts had a conversion efficiency of 0.31%, short-circuit current (Isc) of 0.9mA/cm2, open-circuit voltage (Voc) of 0.58V, and fill factor (FF) of 62.22%. The DSSC sensitized with chlorophyll from A. dentata leaves had a conversion efficiency of 0.13%, Isc of 0.4mA/cm-2,Voc of 0.54V, and FF of 67.5%. The DSSC sensitized with anthocyanin from M. acuminata bracts had a maximum incident photon-to-current conversion efficiency of 42%, which was higher than that of the DSSC sensitized with chlorophyll from A. dentata leaves (23%). Anthocyanin from M. acuminata bracts exhibited the best photosensitization effects.
Many people suffer from myopia or hyperopia due to the refractive errors of the cornea all over the world. The use of high refractive index (RI), Abbe number (νd), and visible light transmittance (T%) polymeric contact lenses (CLs) holds great promise in vision error treatment as an alternative solution to the irreversible laser-assisted in situ keratomileusis (LASIK) surgery. Titanium dioxide nanoparticles (TiO2 NPs) have been suggested as a good candidate to rise the RI and maintain high transparency of a poly(methyl methacrylate) (PMMA)-TiO2 nanocomposite. This work includes a preparation of TiO2 NPs using the sol gel method as well as a synthesis of pure PMMA by free radical polarization and PMMA-TiO2 CLs using a cast molding method of 0.005 and 0.01 w/v concentrations and a study of their effect on the aberrated human eye. ZEMAX optical design software was used for eye modeling based on the Liou and Brennan eye model and then the pure and doped CLs were applied. Ocular performance was evaluated by modulation transfer function (MTF), spot diagram, and image simulation. The used criteria show that the best vision correction was obtained by the CL of higher doping content (p < 0.0001) and that the generated spherical and chromatic aberrations in the eye had been reduced.
The problem of bacteria resistance to many known agents has inspired scientists and researchers to discover novel efficient antibacterial drugs. Three rapid, clean, and highly efficient methods were developed for one-pot synthesis of 7-(aryl)-10,10-dimethyl-10,11-dihydrochromeno[4,3-b]chromene-6,8(7H,9H)-dione derivatives. Three components are condensed in the synthesis, 4-hydroxycoumarin, 5,5-dimethyl-1,3-cyclohexanedione, and aromatic aldehydes, using tetrabutylammonium bromide (TBAB), diammonium hydrogen phosphate (DAHP), or ferric chloride (FeCl3), respectively. Each method has different reaction mechanisms according to the catalyst. The present methods have advantages, including one-pot synthesis, excellent yields, short reaction times, and easy isolation of product. All catalysts utilized in our study could be reused several times without losing their catalytic efficiency. All synthesized compounds were fully characterized and evaluated for their antibacterial activity.
Current study employs mixture of chlorophyll-anthocyanin dye extracted from leaves of Cordyline fruticosa as new sensitizers for dye-sensitized solar cell (DSSCs), as well as betalains dye obtained from fruit of Hylocereus polyrhizus. Among ten pigments solvents, the ethanol and methanol extracts revealed higher absorption spectra of pigments extracted from C. fruticosa and H. polyrhizus respectively. A major effect of temperature increase was studied to increase the extraction yield. The results indicated that extraction temperature between 70 and 80°C exhibited a high dye concentration of each plant than other temperatures. The optimal temperature was around 80°C and there was a sharp decrease of dye concentration at temperatures higher than this temperature. According to experimental results, the conversion efficiency of DSSC fabricated by mixture of chlorophyll and anthocyanin dyes from C. fruticosa leaves is 0.5% with short-circuit current (Isc) of 1.3mA/cm-2, open-circuit voltage (Voc) of 0.62V and fill factor (FF) of 60.16%. The higher photoelectric conversion efficiency of the DSSC prepared from the extract of H. polyrhizus was 0.16%, with Voc of 0.5V, Isc of 0.4mA/cm-2 and FF of 79.16%. The DSSC based betalain dye extracted from fruit of H. polyrhizus shows higher maximum IPCE of 44% than that of the DSSCs sensitized with mixed chlorophyll-anthocyanin dye from C. fruticosa (42%).
In this study, the photocatalytic degradation of toxic pollutant (2-chlorophenol) in the presence of ZnO nanoparticles (ZnO NPs) was investigated under solar radiation. The three main factors, namely pH of solution, solar intensity and calcination temperature, were selected in order to examine their effects on the efficiency of the degradation process. The response surface methodology (RSM) technique based on D-optimal design was applied to optimise the process. ANOVA analysis showed that solar intensity and calcination temperature were the two significant factors for degradation efficiency. The optimum conditions in the model were solar intensity at 19.8 W/m(2), calcination temperature at 404 °C and pH of 6.0. The maximum degradation efficiency was predicted to be 90.5% which was in good agreement with the actual experimental value of 93.5%. The fit of the D-optimal design correlated very well with the experimental results with higher values of R (2) and R (2)adj correlation coefficients of 0.9847 and 0.9676, respectively. The intermediate mechanism behaviour of the 2-chlorophenol degradation process was determined by gas chromatography-mass spectrometry (GC-MS). The results confirmed that 2-chlorophenol was converted to acetic acid, a non-toxic compound.
Nanotubular clay minerals, composed of aluminosilicate naturally structured in layers known as halloysite nanotubes (HNTs), have a significant reinforcing impact on polymer matrixes. HNTs have broad applications in biomedical applications, the medicine sector, implant alloys with corrosion protection and manipulated transportation of medicines. In polymer engineering, different research studies utilize HNTs that exhibit a beneficial enhancement in the properties of polymer-based nanocomposites. The dispersion of HNTs is improved as a result of pre-treating HNTs with acids. The HNTs' percentage additive up to 7% shows the highest improvement of tensile strength. The degradation of the polymer can be also significantly improved by doping a low percentage of HNTs. Both the mechanical and thermal properties of polymers were remarkably improved when mixed with HNTs. The effects of HNTs on the mechanical and thermal properties of polymers, such as ultimate strength, elastic modulus, impact strength and thermal stability, are emphasized in this study.
Some novel coumarins were synthesized starting from 4-hydroxycoumarin and methyl bromoacetate. The structures of the newly obtained compounds were confirmed by elemental analysis, mass, IR and NMR spectra.
Graphene, which as a new carbon material shows great potential for a range of applications because of its exceptional electronic and mechanical properties, becomes a matter of attention in these years. The use of graphene in nanoscale devices plays an important role in achieving more accurate and faster devices. Although there are lots of experimental studies in this area, there is a lack of analytical models. Quantum capacitance as one of the important properties of field effect transistors (FETs) is in our focus. The quantum capacitance of electrolyte-gated transistors (EGFETs) along with a relevant equivalent circuit is suggested in terms of Fermi velocity, carrier density, and fundamental physical quantities. The analytical model is compared with the experimental data and the mean absolute percentage error (MAPE) is calculated to be 11.82. In order to decrease the error, a new function of E composed of α and β parameters is suggested. In another attempt, the ant colony optimization (ACO) algorithm is implemented for optimization and development of an analytical model to obtain a more accurate capacitance model. To further confirm this viewpoint, based on the given results, the accuracy of the optimized model is more than 97% which is in an acceptable range of accuracy.
Laser shock processing (LSP) is an innovative surface treatment technique with high peak power, short pulse, and cold hardening for strengthening metal materials. LSP is based on the application of a high intensity pulsed laser beam (I > 1 GW/cm(2); t < 50 ns) at the interface between the metallic target and the surrounding medium (a transparent confining material, normally water) forcing a sudden vaporization of the metallic surface into a high temperature and density plasma that immediately develops inducing a shock wave propagating into the material. The shock wave induces plastic deformation and a residual stress distribution in the target material. In this paper we study the increase of microhardness and surface roughness with the increase of laser pulse energy in 2024-T3 Al alloy. The influence of the thickness of the confining layer (water) on microhardness and surface roughness is also studied. In addition, the effect of LSP treatment with best conditions on wear behaviors of the alloy was investigated.
Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R(2) = 0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.
A lab-scale granular activated carbon sequencing batch biofilm reactor (GAC-SBBR), a combined adsorption and biological process, was developed to treat real wastewater from a recycled paper mill. In this study, one-consortia of mixed culture (4000-5000 mg/L) originating from recycled paper mill activated sludge from Kajang, Malaysia was acclimatized. The GAC-SBBR was fed with real wastewater taken from the same recycled paper mill, which had a high concentration of chemical oxygen demand (COD) and adsorbable organic halides (AOX). The operational duration of the GAC-SBBR was adjusted from 48 h to 24, 12 and finally 8 h to evaluate the effect of the hydraulic retention time (HRT) on the simultaneous removal of COD and AOX. The COD and AOX removals were in the range of 53-92% and 26-99%, respectively. From this study, it was observed that the longest HRT (48 h) yielded a high removal of COD and AOX, at 92% and 99%, respectively.
The optical properties of a ZnO photocatalyst were enhanced with various dopant concentrations of Fe(3+). Doped ZnO nanoparticles were synthesized via a sol-gel method without the use of capping agents or surfactants and was then characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and ultraviolet-visible (UV-Vis) spectroscopy. The results showed that ZnO has a wurtzite, hexagonal structure and that the Fe(3+) ions were well incorporated into the ZnO crystal lattice. As the Fe(3+) concentration increased from 0.25 wt.% to 1 wt.%, the crystal size decreased in comparison with the undoped ZnO. The spectral absorption shifts of the visible light region (red shift) and the band gap decreases for each Fe-ZnO sample were investigated. The photocatalytic activities of the ZnO and Fe-ZnO samples were evaluated based on the degradation of 2-chlorophenol in aqueous solution under solar radiation. The samples with a small concentration of Fe(3+) ions showed enhanced photocatalytic activity with an optimal maximum performance at 0.5 wt.%. The results indicated that toxicity removal of 2-chlorophenol at same line of degradation efficiency. Small crystallite size and low band gap were attributed to high activities of Fe-ZnO samples under various concentrations of Fe(3+) ions compared to undoped ZnO.
Large-scale solar energy production is still a great deal of obstruction due to the unpredictability of solar power. The intermittent, chaotic, and random quality of solar energy supply has to be dealt with by some comprehensive solar forecasting technologies. Despite forecasting for the long-term, it becomes much more essential to predict short-term forecasts in minutes or even seconds prior. Because key factors such as sudden movement of the clouds, instantaneous deviation of temperature in ambiance, the increased proportion of relative humidity and uncertainty in the wind velocities, haziness, and rains cause the undesired up and down ramping rates, thereby affecting the solar power generation to a greater extent. This paper aims to acknowledge the extended stellar forecasting algorithm using artificial neural network common sensical aspect. Three layered systems have been suggested, consisting of an input layer, hidden layer, and output layer feed-forward in conjunction with back propagation. A prior 5-min te output forecast fed to the input layer to reduce the error has been introduced to have a more precise forecast. Weather remains the most vital input for the ANN type of modeling. The forecasting errors might enhance considerably, thereby affecting the solar power supply relatively due to the variations in the solar irradiations and temperature on any forecasting day. Prior approximation of stellar radiations exhibits a small amount of qualm depending upon climatic conditions such as temperature, shading conditions, soiling effects, relative humidity, etc. All these environmental factors incorporate uncertainty regarding the prediction of the output parameter. In such a case, the approximation of PV output could be much more suitable than direct solar radiation. This paper uses Gradient Descent (GD) and Levenberg Maquarndt Artificial Neural Network (LM-ANN) techniques to apply to data obtained and recorded milliseconds from a 100 W solar panel. The essential purpose of this paper is to establish a time perspective with the greatest deal for the output forecast of small solar power utilities. It has been observed that 5 ms to 12 h time perspective gives the best short- to medium-term prediction for April. A case study has been done in the Peer Panjal region. The data collected for four months with various parameters have been applied randomly as input data using GD and LM type of artificial neural network compared to actual solar energy data. The proposed ANN based algorithm has been used for unswerving petite term forecasting. The model output has been presented in root mean square error and mean absolute percentage error. The results exhibit a improved concurrence between the forecasted and real models. The forecasting of solar energy and load variations assists in fulfilling the cost-effective aspects.
The most widely used method for detecting Coronavirus Disease 2019 (COVID-19) is real-time polymerase chain reaction. However, this method has several drawbacks, including high cost, lengthy turnaround time for results, and the potential for false-negative results due to limited sensitivity. To address these issues, additional technologies such as computed tomography (CT) or X-rays have been employed for diagnosing the disease. Chest X-rays are more commonly used than CT scans due to the widespread availability of X-ray machines, lower ionizing radiation, and lower cost of equipment. COVID-19 presents certain radiological biomarkers that can be observed through chest X-rays, making it necessary for radiologists to manually search for these biomarkers. However, this process is time-consuming and prone to errors. Therefore, there is a critical need to develop an automated system for evaluating chest X-rays. Deep learning techniques can be employed to expedite this process. In this study, a deep learning-based method called Custom Convolutional Neural Network (Custom-CNN) is proposed for identifying COVID-19 infection in chest X-rays. The Custom-CNN model consists of eight weighted layers and utilizes strategies like dropout and batch normalization to enhance performance and reduce overfitting. The proposed approach achieved a classification accuracy of 98.19% and aims to accurately classify COVID-19, normal, and pneumonia samples.