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The focus of the study in this article is analyzing the electrochemical properties of molybdenum disulfide on miscible poly(methyl methacrylate)-poly(lactic acid) blends for supercapacitors. The interaction between molybdenum disulfide and miscible poly(methyl methacrylate)-poly(lactic acid) blends, affinity toward water, surface morphology, and mechanical properties are inspected by Fourier transform infrared spectroscopy, water contact angle, scanning electron microscopy, and universal testing machine, respectively. Among the developed membranes, 0.75 wt% of molybdenum disulfide on poly(methyl methacrylate)-poly(lactic acid) shows better electrochemical performances. It exhibits a maximum specific capacitance of 255.5 F g−1 at a current density of 1.00 mA g−1, maximum energy density of 22.7 Wh kg−1, and maximum power density of 360 W kg−1. A cycle study reveals 92% capacitance retention after 2500 cycles. The designed supercapacitor device shows a maximum specific capacitance of 1240 μF g−1 at a current density of 0.5 μA g−1, maximum energy density of 43 μWh kg−1, and maximum power density of 700 μW kg−1. Flexible membranes of molybdenum disulfide are expected to be a potent combination for supercapacitor applications.

In the past few years, significant research efforts have been directed toward improving the electrochemical capabilities of supercapacitors by advancing electrode materials. The present work signifies the development of poly(lactic acid)/alloysite nano-clay as an electrode material for supercapacitors. Physico-chemical characterizations were analyzed by Fourier transform infrared spectroscopy, wide-angle X-ray diffraction, and a universal testing machine. Cyclic voltammetry, electrochemical impedance spectroscopy, and galvanostatic charge–discharge techniques were employed to evaluate electrochemical characteristics. The optimized poly(lactic acid)/halloysite nano-clay film revealed the highest specific capacitance of 205.5 F g−1 at 0.05 A g−1 current density and showed 14.6 Wh kg−1 energy density at 72 W kg−1 power density. Capacitance retention of 98.48% was achieved after 1000 cycles. The microsupercapacitor device presented a specific capacitance of 197.7 mF g−1 at a current density of 0.45 mA g−1 with 10.8 mWh kg−1 energy density at 549 mW kg−1 power density.

The gel electrolyte significantly influences gel valve-regulated lead acid battery performance. To address this, the paper describes the preparation of novel polymer gel electrolytes using poly (vinyl alcohol) (PVA) and tetraethylorthosilicate (TEOS) for valve-regulated lead–acid batteries. FTIR technique is used to confirm the chemical reaction between PVA and TEOS. Electrochemical analyses such as cyclic voltammetry and electrochemical impedance spectroscopy were applied to optimize the concentration of PVA-TEOS polymer gel electrolyte. The optimum concentration of polymer gel electrolyte was determined as 20 wt% of TEOS in PVA (PE-1) with higher anodic peak and lower Rs and Rct values. The Galvanostatic charge–discharge tests were performed on the optimized gel system prototype battery. The highest capacity of 6.86 × 10−5 Ah at a current density of 0.2 mA cm−2 was achieved with an excellent capacity retention ratio of 85.7% over 500 cycles. The exceptional cycle performance and high capacity make PVA-TEOS gel electrolyte a promising candidate for practical battery application.

Polyelectrolyte complex membranes (PECMs) were prepared by combining sodium carboxymethyl cellulose (NaCMC) and gelatin (Ge) with variations in the Ge content in the NaCMC matrix. Characterization methods, such as infrared spectroscopy (FTIR), wide-angle X-ray diffraction (WAXD), thermogravimetric analysis (TGA), scanning electron microscopy (SEM), contact angle analysis (CA), and universal testing machines (UTM) were used to investigate the physicochemical studies of the prepared membranes. The pervaporation characteristics of membranes with Ge content were investigated using an azeotropic mixture of water and bioethanol. The obtained data revealed that the membrane with 15 mass% of Ge (M-3) showed a maximum flux of 7.8403 × 10−2 kg/m2·h with separation selectivity of 2917 at 30 °C. In particular, the total and water flux of PECMs are shown as very close to each other indicating that the fabricated membranes could be employed to successfully break the azeotropic point of water–bioethanol mixtures. Using temperature-dependent permeation and diffusion data, the Arrhenius activation parameters were calculated, and the obtained values of water permeation (Epw) were considerably smaller than bioethanol permeation (EpE). Developed membranes showed the positive heat of sorption (ΔHs), suggesting that Henry’s sorption mode is predominant.

The combustion phenomena are always complex in nature due to the involvement of complex series and parallel reactions. There are various methods that are involved in analyzing combustion phenomena. Viscosity is the first and foremost factor that acts as the DNA of fuel. By evaluating the viscosity, it is possible initially to understand the combustion phenomena. Thermophysical and transport properties are helpful during the intensification of the combustion process. Combustion experiments are economically infeasible and time-consuming processes. Combustion simulations demand excellent computational facilities with detailed knowledge of chemical kinetics. So far, the majority of researchers have focused on analyzing coal combustion phenomena, whereas less work has been carried out on liquid fuels, especially biodiesel combustion analysis. Traditional engine testing provides only performance parameters, and it fails to have oversight of the thermodynamic aspects. The application of thermal analysis methods in combustion research is useful in the design, modeling, and operation of the systems. Such investigations are carried out extensively in the combustor, engine, and process industries. The use of differential scanning calorimetry (DSC) and thermogravimetry (TG) to assess the properties of biofuels has been attracting researchers in recent years. The main objective of this paper is to discuss the application of TGA and DSC to analyze heat flow, enthalpy, thermal stability, and combustion indexes. Moreover, this paper reviews some of the other aspects of the kinetics of combustion, transport properties’ evaluation, and combustion simulations for biodiesels and their blends. TG curves indicate two phases of decomposition for diesel and three phases for biofuel. The B-20 blend’s (20% biodiesel and 80% diesel) performance was found to be similar to that of diesel with the combustion index and intensity of combustion nearly comparable with diesel. It is thermally more stable with a high offset temperature, confirming a longer combustion duration. A case study reported in this work showed diesel and B20 JOME degradation start from 40 °C, whereas jatropha oil methyl ester (JOME) degradation starts from 140 °C. JOME presents more decomposition steps with high decomposition temperatures, indicative of more stable compound formation due to the oxidation process. The peak temperature of combustion for diesel, JOME, and B20 JOME are 250.4 °C, 292.1 °C, and 266.5 °C, respectively. The ignition index for the B-20 blend is 73.73% more than that of diesel. The combustion index for the B20 blend is 37.81% higher than diesel. The B20 blend exhibits high enthalpy, better thermal stability, and a reduced peak temperature of combustion with an improved combustion index and intensity of combustion nearly comparable to diesel.

Polymer-based nanocomposites are being considered as replacements for conventional materials in medium to high-temperature applications. This article aims to discover the synergistic effects of reinforcements on the developed polymer-based nanocomposite. An epoxy-based polymer composite was manufactured by reinforcing graphene nanoplatelets (GNP) and h-boron nitride (h-BN) nanofillers. The composites were prepared by varying the reinforcements with the step of 0.1 from 0.1 to 0.6%. Ultrasonication was carried out to ensure the homogenous dispersion of reinforcements. Mechanical, thermal, functional, and scanning electron microscopy (SEM) analysis was carried out on the novel manufactured composites. The evaluation revealed that the polymer composite with GNP 0.2 by wt % has shown an increase in load-bearing capacity by 265% and flexural strength by 165% compared with the pristine form, and the polymer composite with GNP and h-BN 0.6 by wt % showed an increase in load-bearing capacity by 219% and flexural strength by 114% when compared with the pristine form. Furthermore, the evaluation showed that the novel prepared nanocomposite reinforced with GNP and h-BN withstands a higher temperature, around 340 °C, which is validated by thermogravimetric analysis (TGA) trials. The numerical simulation model is implemented to gather the synthesised nanocomposite’s best composition and mechanical properties. The minor error between the simulation and experimental data endorses the model’s validity. To demonstrate the industrial applicability of the presented material, a case study is proposed to predict the temperature range for compressor blades of gas turbine engines containing nanocomposite material as the substrate and graphene/h-BN as reinforcement particles.

Chitosan-capped silver nanoparticle (CS-capped AgNPs)-incorporated Poly(vinyl alcohol) (PVA) hybrid membranes were prepared by a solution-casting technique for ethanol dehydration via pervaporation. The incorporation of CS-capped AgNPs into the PVA membrane and its influence on membrane properties and pervaporation-separation process of azeotropic water/ethanol mixture was studied. The addition of CS-capped AgNPs into the PVA membrane reduced the crystallinity, thereby increasing the hydrophilicity and swelling degree of the hybrid membrane, supported by contact angle (CA) analyzer and swelling degree experiments, respectively. Fourier transform infrared spectroscopy (FTIR) demonstrated the formation of polymeric matrix between PVA and CS and also the binding of AgNPs onto the functional group of CS and PVA, which was also reflected in the microstructure images demonstrated by scanning electron microscopy (SEM) and by 2θ angle of wide-angle X-ray diffraction (WAXD). The effect of CS-capped AgNPs on the thermal stability of the hybrid membrane was demonstrated by differential scanning calorimetry (DSC) and thermogravimetric analyzer (TGA). These characteristics of the hybrid membrane positively impact the efficiency of the dehydration of ethanol, as indicated by pervaporation experiments. The best performances in total flux (12.40 ± 0.20 × 10−2 kg/m2 h) and selectivity (3612.33 ± 6.03) at 30 °C were shown for CS-capped AgNPs PVA hybrid membrane containing 2 wt.% CS-capped AgNPs (M-4). This confirms that the developed hybrid membranes can be efficiently used to separate water from azeotropic aqueous ethanol.

The development of radiation attenuation materials with lean cross-sections is the need of the hour. However, the inherent threat of radiations accompanying these processes is of major concern. Thus, in an attempt to shield unnecessary radiations, several novel materials have been fabricated alongside the conventional materials available. Yet, there is a need for cost-effective, efficient shielding materials that have good mechanical strength and effective shielding properties. The present work investigates ceramic composite behaviors and radiation shielding capacity reinforced with lead oxide nano-powder. Developed nano-lead-based cement composites were subjected to mechanical tests to determine flexural and compressive strengths to check their suitability for structural applications. Further, the gamma attenuation test of the composites was conducted to determine their neutron absorption capacity. The addition of nano-leadoxide in the control beams was varied from 0.7 to 0.95 and 1 wt.% of the ceramic matrix. The percentage of nano-leadoxide that gives the best results in both enhanced properties and economic aspects was determined to be 0.6 wt.% of the cement.

Natural polymers have attracted a lot of interest in researchers of late as they are environmentally friendly, biocompatible, and possess excellent characters. Membranes forming natural polymers have provided a whole new dimension to the separation technology. In this work, chitosan-gelatin blend membranes were fabricated using chitosan as the base and varying the amount of gelatin. Transport, mechanical, and surface characteristics of the fabricated membranes were examined in detail by means of the characterizing techniques such as Fourier transform infrared spectroscopy, differential scanning colorimetry, wide angle X-ray diffraction, scanning electron microscope, and thermogravimetric analysis. In order to analyze the water affinity of the developed blend chitosan-gelatin membranes, the percentage degree of swelling was examined. Out of the fabricated membranes, the membrane loaded with 15 mass% of gelatin exhibited the better pervaporation performance with a pervaporation separation index value of 266 at 30 °C for the solution containing 10% in terms of the mass of water, which is the highest among the contemporary membranes. All the fabricated membranes were stable during the pervaporation experiments, and permeation flux of water for the fabricated membranes was dominant in the overall total permeation flux, signifying that the developed membranes could be chosen for efficient separation of water–isopropanol mixture on a larger scale.

Tetraethylorthosilicate (TEOS)-crosslinked poly(vinyl alcohol) (PVA) solution was prepared and treated with benzaldehyde 2 sulphonic sodium salt acid (B2SA) for sulfonation. Different contents of graphene were incorporated into B2SA-grafted PVA–TEOS hybrid membrane to improve the membrane stability, mechanical strength, and overall pervaporation performance of the membranes. Membranes were fabricated using the casting technique. Developed membranes were then analyzed for their physicochemical changes by means of Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), scanning electron microscope (SEM), wide-angle X-ray diffraction (WAXD), thermogravimetric analysis (TGA), contact angle analysis (CA), and mechanical strength. The lower d-spacing value observed in WAXD was evidence for the decreased inter-chain distance between the polymer chains. DSC exhibited the enhanced thermal stability of the developed membranes compared to the plane PVA membrane with enhancement in Tg value (106 °C), which was well above the pervaporation experimental temperature. Incorporation of graphene induced higher mechanical strength to the fabricated membranes. Further, the membranes were tested for the pervaporation separation of bioethanol. All the membranes were stable throughout the pervaporation studies, with M-2 G showing the total permeation flux of 11.66 × 10−2 kg/(m2 h) at 30 °C.

The present investigation is directed towards synthesis of zinc oxide (ZnO) nanoparticles and steady blending with soybean biodiesel (SBME25) to improve the fuel properties of SBME25 and enhance the overall characteristics of a variable compression ratio diesel engine. The soybean biodiesel (SBME) was prepared using the transesterification reaction. Numerous characterization tests were carried out to ascertain the shape and size of zinc oxide nanoparticles. The synthesized asymmetric ZnO nanoparticles were dispersed in SBME25 at three dosage levels (25, 50, and 75 ppm) with sodium dodecyl benzene sulphonate (SDBS) surfactant using the ultrasonication process. The quantified physicochemical properties of all the fuels blends were in symmetry with the American society for testing and materials (ASTM) standards. Nanofuel blends demonstrated enhanced fuel properties compared with SBME25. The engine was operated at two different compression ratios (18.5 and 21.5) and a comparison was made, and best fuel blend and compression ratio (CR) were selected. Fuel blend SBME25ZnO50 and compression ratio (CR) of 21.5 illustrated an overall enhancement in engine characteristics. For SBME25ZnO50 and CR 21.5 fuel blend, brake thermal efficiency (BTE) increased by 23.2%, brake specific fuel consumption (BSFC) were reduced by 26.66%, and hydrocarbon (HC), CO, smoke, and CO2 emissions were reduced by 32.234%, 28.21% 22.55% and 21.66%, respectively; in addition, the heat release rate (HRR) and mean gas temperature (MGT) improved, and ignition delay (ID) was reduced. In contrast, the NOx emissions increased for all the nanofuel blends due to greater supply of oxygen and increase in the temperature of the combustion chamber. At a CR of 18.5, a similar trend was observed, while the values of engine characteristics were lower compared with CR of 21.5. The properties of nanofuel blend SBME25ZnO50 were in symmetry and comparable to the diesel fuel.

The present investigation uses a blend of Nigella sativa biodiesel, diesel, n-butanol, and graphene oxide nanoparticles to enhance the performance, combustion and symmetric characteristics and to reduce the emissions from the diesel engine of a modified common rail direct injection (CRDI). A symmetric toroidal-type combustion chamber and a six-hole solenoid fuel injector were used in the current investigation. The research aimed to study the effect of two fuel additives, n-butanol and synthesized asymmetric graphene oxide nanoparticles, in improving the fuel properties of Nigella sativa biodiesel (NSME25). The concentration of n-butanol (10%) was kept constant, and asymmetric graphene oxide nano-additive and sodium dodecyl benzene sulphonate (SDBS) surfactant were added to n-butanol and NSME25 in the form of nanofluid in varying proportions. The nanofluids were prepared using a probe sonication process to prevent nanoparticles from agglomerating in the base fluid. The process was repeated for biodiesel, n-butanol and nanofluid, and four different stable and symmetric nanofuel mixtures were prepared by varying the graphene oxide (30, 60, 90 and 120 ppm). The nanofuel blend NSME25B10GO90 displayed an enhancement in the brake thermal efficiency (BTE) and a reduction in brake-specific fuel consumption (BSFC) at maximum load due to high catalytic activity and the enhanced microexplosion phenomenon developed by graphene oxide nanoparticles. The heat release rate (HRR), in-cylinder temperature increased, while exhaust gas temperature (EGT) decreased. Smoke, hydrocarbon (HC), carbon monoxide (CO2) and carbon monoxide (CO) emissions also fell, in a trade-off with marginally increased NOx, for all nanofuel blends, compared with Nigella sativa biodiesel. The results obtained indicates that 90 ppm of graphene oxide nanoparticles and 10% n-butanol in Nigella sativa biodiesel are comparable with diesel fuel.

Background: Early identification of Alzheimer's disease (AD) is essential for optimal treatment and management. Deep learning (DL) technologies, including convolutional neural networks (CNNs) and vision transformers (ViTs) can provide promising outcomes in AD diagnosis. However, these technologies lack model interpretability and demand substantial computational resources, causing challenges in the resource-constrained environment. Hybrid ViTs can outperform individual ViTs by visualizing key features with limited computational power. This synergy enhances feature extraction and promotes model interpretability., Objectives: Thus, the authors present an innovative model for classifying AD using MRI images with limited computational resources., Methods: The authors improved the AD feature-extraction process by modifying the existing ViTs. A CatBoost-based classifier was used to classify the extracted features into multiple classes., Results: The proposed model was generalized using the OASIS dataset. The model obtained an exceptional classification accuracy of 98.8% with a minimal loss of 0.12., Conclusions: The findings highlight the potential of the proposed AD classification model in providing an interpretable and resource-efficient solution for healthcare centers. To improve model robustness and applicability, subsequent research can include genetic and clinical data.

Breast cancer (BC) is the leading cause of mortality among women across the world. Earlier screening of BC can significantly reduce the mortality rate and assist the diagnostic process to increase the survival rate. Researchers employ deep learning (DL) techniques to detect BC using mammogram images. However, these techniques are resource-intensive, leading to implementation complexities in real-life environments. The performance of convolutional neural network (CNN) models depends on the quality of mammogram images. Thus, this study aimed to build a model to detect BC using a DL technique. Image preprocessing techniques were used to enhance image quality. The authors developed a CNN model using the EfficientNet B7 model's weights to extract the image features. Multi-class classification of BC images was performed using the LightGBM model. The Optuna algorithm was used to fine-tune LightGBM for image classification. In addition, a quantization-aware training (QAT) strategy was followed to implement the proposed model in a resource-constrained environment. The authors generalized the proposed model using the CBIS-DDSM and CMMD datasets. Additionally, they combined these two datasets to ensure the model's generalizability to diverse images. The experimental findings revealed that the suggested BC detection model produced a promising result. The proposed BC detection model obtained an accuracy of 99.4%, 99.9%, and 97.0%, and Kappa (K) values of 96.9%, 96.9%, and 94.1% in the CBIS-DDSM, CMMD, and combined datasets. The recommended model streamlined the BC detection process in order to achieve an exceptional outcome. It can be deployed in a real-life environment to support physicians in making effective decisions. Graph convolutional networks can be used to improve the performance of the proposed model.

Chitosan-capped silver nanoparticle (CS-capped AgNPs)-incorporated Poly(vinyl alcohol) (PVA) hybrid membranes were prepared by a solution-casting technique for ethanol dehydration via pervaporation. The incorporation of CS-capped AgNPs into the PVA membrane and its influence on membrane properties and pervaporation-separation process of azeotropic water/ethanol mixture was studied. The addition of CS-capped AgNPs into the PVA membrane reduced the crystallinity, thereby increasing the hydrophilicity and swelling degree of the hybrid membrane, supported by contact angle (CA) analyzer and swelling degree experiments, respectively. Fourier transform infrared spectroscopy (FTIR) demonstrated the formation of polymeric matrix between PVA and CS and also the binding of AgNPs onto the functional group of CS and PVA, which was also reflected in the microstructure images demonstrated by scanning electron microscopy (SEM) and by 2θ angle of wide-angle X-ray diffraction (WAXD). The effect of CS-capped AgNPs on the thermal stability of the hybrid membrane was demonstrated by differential scanning calorimetry (DSC) and thermogravimetric analyzer (TGA). These characteristics of the hybrid membrane positively impact the efficiency of the dehydration of ethanol, as indicated by pervaporation experiments. The best performances in total flux (12.40 ± 0.20 × 10 -2 kg/m 2 h) and selectivity (3612.33 ± 6.03) at 30 °C were shown for CS-capped AgNPs PVA hybrid membrane containing 2 wt.% CS-capped AgNPs (M-4). This confirms that the developed hybrid membranes can be efficiently used to separate water from azeotropic aqueous ethanol.

Diabetic retinopathy (DR), Retinopathy of Pre-maturity (ROP), and Age-related Macular Degeneration (AMD) are multifactorial manifestations associated with abnormal growth of blood vessels in the retina. These three diseases account for 5% of the total blindness and vision impairment in the US alone. The current treatment options involve heavily invasive techniques such as frequent intravitreal administration of anti-VEGF (vascular endothelial growth factor) antibodies, which pose serious risks of endophthalmitis, retinal detachment and a multitude of adverse effects stemming from the diverse physiological processes that involve VEGF. To overcome these limitations, this current study utilizes a micellar delivery vehicle (MC) decorated with an anti-angiogenic peptide (aANGP) that inhibits αvβ3 mediated neovascularization using primary endothelial cells (HUVEC). Stable incorporation of the peptide into the micelles (aANGP-MCs) for high valency surface display was achieved with a lipidated peptide construct. After 24 h of treatment, aANGP-MCs showed significantly higher inhibition of proliferation and migration compared to free from aANGP peptide. A tube formation assay clearly demonstrated a dose-dependent angiogenic inhibitory effect of aANGP-MCs with a maximum inhibition at 4 μg/mL, a 1000-fold lower concentration than that required for free from aANGP to display a biological effect. These results demonstrate valency-dependent enhancement in the therapeutic efficacy of a bioactive peptide following conjugation to nanoparticle surfaces and present a possible treatment alternative to anti-VEGF antibody therapy with decreased side effects and more versatile options for controlled delivery.