Mahatma Gandhi University

Lithium–sulfur (Li–S) battery technology is increasingly recognized for its promising future as a high-performance energy storage solution, with an energy density of 2600 WhKg⁻¹ and a substantial theoretical capacity of 1675 mA hg⁻¹. This battery type is suboptimal for commercial applications, such as lithium-ion (Li-ion) cell systems, due to rapid capacity attenuation and poor low cycle performance and rates. Enhancements in cathodes, anodes, and electrolytic materials are essential for attaining elevated power and energy density. Significant advancements have been achieved in overcoming these challenges by the incorporation of carbon-based nanomaterials into lithium–sulfur battery systems. This review article analyzes recent advancements in the use of carbon-based nanomaterials, including carbon nanotubes, graphene, carbon nanofibers, and carbonaceous composites, to enhance the efficiency of lithium–sulfur batteries. The analysis concludes with an examination of future prospects and challenges in the sector, emphasizing the need for more research to optimize the use of carbon-based nanomaterials in lithium–sulfur batteries. The full potential of Li–S batteries may be achieved by the incorporation of enhanced carbon materials, facilitating their widespread use in portable devices, electric vehicles, and grid energy storage systems. Graphical abstract

In recent years, there has been a notable increase in the usage of natural fibers as reinforcements in polymer composites. However, exposure to high temperatures frequently causes problems for these fibers. Ceramic particles, such as silicon carbide (SiC), are added to them to increase their longevity and thermal stability. The impact of SiC particles on the dynamic mechanical and thermal characteristics of woven bamboo fiber hybrid composites is investigated in this work. In an epoxy matrix, different weight fractions of SiC particles (0, 3, 6, 9, and 12%) were added, and the hand layup process was used to create hybrid composites with three layers of bamboo fiber/SiC. Analysis of the hybridization’s synergistic effects was done using both dynamic and thermal mechanics. The findings showed that with a 6% SiC inclusion, the impact strength (59.4%), tensile strength (30.7%), and hardness (5.9%) were all markedly enhanced by the SiC particles. In addition, the 6% SiC reinforcement generated the maximum thermal stability with increased energy absorption and recovery, according to thermomechanical analysis (TMA) and dynamic mechanical analysis (DMA). The useful contribution of SiC particles to improving the structural and thermal performance of bamboo fiber epoxy composites, which qualifies them for demanding applications, was further validated by fracture analysis.

In recent days, the expansion of Internet of Things (IoT) and the quick advancement of computer system applications contribute to the current phenomenon of data growth. The field of intrusion detection has expanded considerably as a result of the need to protect networks from various attacks. Previously, security has been provided by combining conventional intrusion monitoring systems with a high number of security measures. However, the ability of combined systems to analyze enormous amounts of data has been restricted. Therefore, in this research, open-source and freely available datasets known as NSL-KDD and CSE-CIC-IDS2018 datasets are analyzed. Those datasets contain a class column that splits the attack detection into two classes (normal and anomalous) and four categories (DoS, probe, R2L, and U2R). Then, feature encoding and scaling are used for pre-processing. After that, a SelectPercentile-based feature selection algorithm is suggested to identify the numerous various intrusion attacks and choose the best features. Later, the Regularized Long Short-Term Memory (LSTM) is employed to classify the data. The result analysis verified that Regularized LSTM surpasses the existing models in the NSL-KDD based on accuracy (99.95%), false alarm rate (0.05%), attack detection rate (99.82%), and f1-measure (99.94%). While in the CSE-CIC-IDS2018 dataset, the Regularized LSTM method achieves better accuracy (99.33%), false alarm rate (0.07%), attack detection rate (99.96), and f1-measure (99.95%).

This paper provides an in-depth look at the latest developments in dye-sensitized solar cell (DSSC) technology. It focuses on the use of special materials, like polyaniline (PANI), graphene oxide (GO), and carbon nanotubes (CNTs). These materials improve the efficiency and stability of solar cells, and this study offers significant insights into their characteristics and practical uses. This article examines major trends in material selection, structural optimization, and manufacturing procedures by juxtaposing results from scientific literature with advancements in the patent arena, addressing the issues of developing next-generation solar cell designs. We examine the synergistic effects of PANI's stability, GO's electrical conductivity, and CNTs' mechanical strength, highlighting their roles in enhancing light absorption, charge transfer efficiency, and overall device longevity. Bibliometric data from sites, like Scopus and Lens.org, indicate substantial advancements in energy conversion efficiency and decreases in charge transfer resistance. Patents, like WO 2020 and EP3824-B1, illustrate the increasing significance of flexibility, resilience, and scalability in solar cell designs. Biopolymer-based electrolytes made from chitosan, guar gum, and starch are examples of sustainable solutions that show better ionic conductivity and mechanical stability, making them eco-friendly choices. This paper highlights the significance of nano and microfillers in enhancing electron mobility and minimizing resistive losses. Practical implementations, including photovoltaic chargers and flexible solar panels, illustrate the conversion of theoretical advancements into functional technologies. The study delineates future research avenues, promoting the utilization of nanocomposites and catalytic materials to enhance solar cell performance and thus facilitate sustainable and scalable energy solutions to address escalating global energy demands.

The urgent need to address climate change and industrial feedstock security is the reason behind the rising demand for bio-based products. Unsaturated polyester resin (UPR) is at the forefront of sustainable innovation because of its exceptional resilience, durability, and chemical resistance. A major step towards environmentally friendly UPR synthesis is marked by the novel use of bio-based building blocks and reactive diluents made from renewable resources, as highlighted in this review. In particular, a thorough investigation is conducted into the application of bio-based acids like itaconic acid, succinic acid, and muconic acid, as well as bio-based alcohols like 1,3-propanediol and sorbitol. Moreover, it is claimed that the creative use of modified plant oils and reactive diluents such as ferulic acid, itaconic acid, and sobrerol derivatives is a revolutionary development. Aqueous polyester systems are given special attention, demonstrating their promise as a sustainable substitute in UPR synthesis. This analysis lays the foundation for a revolutionary approach to sustainable material design by combining recent advancements with new avenues and potential applications for bio-based UPR. This study lays the groundwork for a more environmentally friendly future in industrial polymer production by fusing science, sustainability, and cutting-edge innovation.

Multi‐component reactions (MCRs) involve the reaction of three or more compounds to yield a single product. Typically, MCRs are eco‐friendly and atom‐economical processes, widely used to synthesize pharmaceutically relevant compounds with diverse applications in both medicinal and synthetic chemistry. Nowadays, transition metals are widely used as catalysts in MCRs due to their exceptional ability to create both C–C and C‐heteroatom bonds. Metal‐catalyzed MCRs offer optimal chemical diversity, excellent atom economy, and energy savings.

A novel class of substituted 1,3,4‐oxadiazole coupled 1,2,3‐triazole analogues were prepared and evaluated for their epidermal growth factor receptor (EGFR) inhibitory profiles and antiproliferative activities. The confirmation of the structures of the synthesized compounds was done using spectroscopic techniques. Using the MTT assay, the in vitro cytotoxicity was investigated against three human cancer cell lines, MDA‐MB‐468, HepG‐2, and A549. Compound 8a had the highest anticancer activity against all cancer cell lines, with an IC 50 range of 1.02 ± 0.56–3.67 ± 0.07 μM. The EGFR inhibition of the most active compounds, 8a , 8b , 8d , 8f , and 8h was further assessed. In contrast to Erlotinib (IC 50 = 0.19 ± 0.07 μM), compounds 8b and 8h , demonstrated IC 50 values of 0.54 ± 0.18 and 0.33 ± 0.06 μM, respectively. Binding interactions showed that the synthesized compounds were involved in inhibiting the growth of cancer by blocking the EGFR enzyme (PDB:3W2Q). The DFT/B3LYP method functionalized with a 6–31 g(d, p) basis set was employed to calculate quantum parameters, MEP analysis, HOMO, and LUMO. Compounds 8b , 8g , and 8h have displayed good in silico ADMET properties. Compounds 8b , 8g , 8h , and 8j displayed good drug‐likeness scores (1.02, 1.09, 0.60, and 0.75) and none of the compounds can cross the blood–brain barrier because they are all outside the boiled egg yolk.

Emerging antibiotic resistance among bacterial pathogens of diabetic foot ulcers (DFUs) cause a significant threat to the human health. In the study, deep ulcer swabs were collected from 70 diabetic patients with foot ulcer. Among the 187 bacterial strains purified from the same, major representations were identified to be from Klebsiella pneumoniae and Staphylococcus spp. Here, polymicrobial infection (87.14%) was found to be more prevalent than monomicrobial (12.86%). From the antibiotic susceptibility test results, 34 bacterial isolates were identified as MDR pathogens with resistance to β-lactam and carbapenem classes of antibiotics. Furthermore, molecular screening has revealed the presence of antibiotic resistance gene such as blaSHV,blaCTX-M, blaTEM,blaOXA-48, NDM-1, mecA and blaZ genes among the isolates studied. Biofilm analysis has further revealed 31 strains to have strong and 3 with moderate biofilm production property. Among the MDR strains, K. pneumoniae (DFU2.2) and methicillin-resistant S. aureus (MRSA) (DFU24.3) were subjected to the whole-genome sequencing (WGS) based analysis due to their significant role in the chronicity of DFUs. The resistome prediction from the WGS data of DFU2.2 has revealed it to have the presence of a novel extended β-lactamase gene blaSHV-106 which has not been reported previously from India. Pan-genome analysis of DFU2.2 and DFU24.3 has also provided detailed insight into the genetic diversity, evolution, and pathogenic potential of the selected strains. The findings of this study hence suggest the emerging AMR to be one of the major risk factors challenging the therapeutic response of DFUs, the incidence of which is alarmingly high.

Cesium bismuth bromide (CBB) provides a compelling lead free, non‐toxic alternative in perovskite optoelectronic applications. Doping with transition metal has been employed for the improvement of photophysical characteristics in perovskites. In this study, the incorporation of heterovalent Zn²⁺ ions in CBB nanosheets and its effect on the structural, morphological, linear, and non‐linear properties are investigated. Zn doping leads to a decrease in lattice strain and crystallite size eliciting a reduction in the nanosheet dimension. Combined with the morphological alteration, incorporation of Zn results in an enhancement in the UV absorbance cross section of CBB and a reduction in Urbach energy brought on by the shallow defect passivation. The electronic states of the new systems probed using first principle studies pointed to the formation of new states in the conduction band. This instigates an enhancement of third‐order optical non‐linearity in the perovskites. The two‐photon absorption coefficient increased by a factor of three and the optical limiting threshold is reduced to half, upon incorporation of optimal amount of Zn. This study on the effects of heterovalent substitution in lead free perovskites, in modifying the electronic states and the optical properties points to augmenting novel optoelectronic applications.

Consumers face unique behavioral challenges regarding the exercise of their rights, influenced not only by consumer rights awareness but also by psychological attributes. In this study, we explore the role of self-assertiveness in the relationship between consumer rights awareness and consumer rights exercise. Drawing on data from a sample of 510 consumers, analyzed through OLS regression, the study reveals that higher levels of self-assertiveness strengthen the relationship between consumer rights awareness and consumer rights exercise, controlling for sociodemographic factors. The study emphasizes the potential benefits of combining psychological attributes like self-assertiveness, into consumer education and policy, offering implications for consumer educators, consumer practitioners, and policymakers. The findings suggest that the consumer education programs should address the sociopsychological aspects of consumer behavior. By recognizing psychological pathways influencing consumer behavior, stakeholders can design more holistic approaches to support the consumer well-being by fostering responsible exercise of consumer rights.

Nitrogen-doped Silicon Carbide (SiC) thin films were deposited on p-Si (100) and glass substrates using Radio Frequency Plasma Enhanced Chemical Vapor Deposition (RF-PECVD) technique. The structural, compositional, and linear and non-linear optical properties of the films were probed as a function of nitrogen content using various characterization techniques; like Grazing Incidence X-ray Diffraction (GIXRD), X-ray Photoelectron Spectroscopy (XPS), UV–Visible Spectroscopy, and Photoluminescence Spectroscopy. Increase in the N2 flow rate from $0\% \;to\; 41.2\%$ during deposition resulted in decrease in intensity of the α-SiC peak (1020) in the XRD spectra, due to formation of the Si–N bonds, indicating reduction in crystallinity. XPS confirms formation of SiC hexagonal phase in the film surface, and Nitrogen doping was found to cause oxidation due to generation of defect sites. Band-gap widening is observed with increasing N2 concentration up to 5 sccm (2.43–2.67 eV), beyond that the value decreases. Intense visible emission was observed in N-doped films, along with the UV emission, which is observed for undoped film as well. The CIE-1931 chromaticity plot exhibits color perception close to pure white in the N-doped SiC films, the blue color perception is observed in the undoped SiC film. The value of Correlated Colour Temperature for the samples in the white light region is in between 2500 K and 6500 K which shows the high quality of the generated white light.

In the digital era, texts act as one of the essential means for transmitting information. However, it is very crucial to detect text patterns in an extremely complex background and multilingual environment. Although improvements in Deep Learning (DL)-centric techniques have succeeded in enhancing the accuracy of Text Detection (TD) and recognition from scene images, performing the same in a cluttered background still remains challenging. Therefore, this paper presents a novel nature scene text prediction approach using the Vocabulary-Transformer-Pipeline pruner (VTP)-based Phrasenet. Initially, the Natural Scene (NS) image dataset is collected from publicly available sources. Then, pre-processing is performed for the NS image; here, foreground and background pixel separation, clutter background removal by LMS, image reconstruction, and image pyramid are done. From the pre-processed image, the text region is predicted by using RSA-SEDO-MSER. Next, significant features are extracted from the predicted text region by employing SIFT, IFT, and HOG techniques. Subsequently, based on MEBOA-HF, the text is recognized by extracting the text region’s candidate pixels. Meanwhile, the non-text regions are recognized by placing the rotating anchor boxes. Then, features are extracted from the recognized non-texts for efficient recognition criterion. Thereafter, the extracted features are subjected to Pixel-BERT for efficient mapping of the image pixels with text. Eventually, the text is detected from the mapped text by utilizing VTP-PN. The experimental outcomes proved that the proposed methodology achieved a higher accuracy of 97.597%, thus outperforming prevailing techniques.

In-situ observations of atmospheric Black Carbon (BC) aerosols over the northern Indian Ocean are sparse, especially during the Indian Summer Monsoon season due to harsh and challenging oceanic conditions associated with strong south-westerly winds and rough sea states. In the present study, we measured atmospheric BC over the Arabian Sea (AS) during June on board a research expedition. While BC is expected to decrease as we move away from continental landmass, surprisingly, despite negligible land-based combustion activities at this time of the year, a zone of high BC was observed offshore within a narrow band impacted by the Biparjoy cyclone. The median BC concentration was two-fold higher within the cyclone-impacted zone than in the region east of this zone. Airmass back-trajectory and satellite fire map analysis revealed that savanna burning in Africa could significantly affects elevated BC signals over the AS. However, the absence of correlation of BC with biomass-burning tracers inside the high-BC zone clearly suggested some other active source(s). Correlation analysis of BC with oceanic deep-water vertical mixing indicators as well as atmospheric processes provides vital pointers that a significant amount of this BC can be regurgitated from waters, which are brought to the surface from depth, as the deep ocean is one of largest reservoirs of BC aerosols. These findings demand a nascent scope for controlled simulation experiments to estimate regurgitated BC from the ocean to reduce its uncertainty.

Lead free halide perovskites have been explored ardently for optoelectronic applications. Organic-Inorganic hybrid halide perovskites have shown promise with novel optical properties, bandgap tuning and improved carrier dynamics while introducing...

Ketoamides are privileged chemical entities featuring a carbonyl group bonded to an amide. Bearing two pronucleophilic and two proelectrophilic sites, this structural scaffold exhibits distinct chemical properties and unparalleled biological activity. Owing to its wide application in medicinal, agricultural, and synthetic chemistry, methods for assembling this distinct moiety are ever‐growing in demand. With the increasing focus on green synthesis, traditional routes to α ‐ketoamides have faded in recent years giving rise to the development of photocatalytic, electrosynthetic, and microwave‐assisted catalytic protocols. We hereby provide a comprehensive and critical summary of all the catalytic advancements witnessed in this field from 2016 to the present.

The growing demand for sustainable and high-performance sensors has driven the development of hydrogen peroxide (H2O2) sensing technologies utilizing innovative material combinations. This study developed cutting-edge H2O2 sensors by integrating 3D printing technology and materials like silver nanoparticles, carbon nanotubes, recycled battery powder, and biodegradable polymers such as acrylonitrile butadiene styrene (ABS), polylactic acid (PLA) (5%, 10%), and polyvinyl alcohol (PVA) (5%, 10%). The cyclic voltammetry analysis demonstrated that electrodes with 10% PVA exhibited superior electrocatalytic activity and sensitivity for detecting H2O2 compared to PLA-based electrodes. This innovative approach addresses environmental concerns associated with electronic waste, enhancing sensor durability and electrochemical efficiency.

A green protocol for the synthesis of 1H‐benzo[d]imidazole derivatives, utilizing zinc(II) catalysis in a one‐pot strategy is successfully developed. This method efficiently accomplishes the reaction of o‐phenylenediamine with a variety of aldehydes, yielding benzimidazoles with superior efficiency spanning a broad substrate scope. An admirable application of this protocol is the synthesis of Thiabendazole, an anthelmintic drug highlighting a prominent achievement in drug synthesis. Mild operational conditions and excellent yields make this methodology highly sustainable.

The objective of this study was to assess the feasibility of using a poly(vinylidene fluoride) (PVDF) membrane modified with cellulose/nanostructures as a separation technique for the removal of poly(vinyl alcohol)(PVA)/reactive dyes from synthetic textile wastewater. The goal was to recycle PVA/reactive dye yellow 145 for reuse in the industry while simultaneously reclaiming water for reuse. To achieve this, the study aimed to evaluate the influence of SnO 2 /ZnO nanostructures on the polymer mixture, examining their impact on permeation and rejection of PVA/reactive dye. Additionally, the study investigated the antifouling properties of PVDF, both in the presence and absence of electrospun cellulose nanofibers. Chemical analysis techniques, including SEM, EDS, FTIR, mechanical strength testing, contact angle measurement, AFM, and determination of molecular weight cutoff (MWCO), were employed to assess the synthesized membranes. The MWCO results indicated a decrease in pore size after surface modification with electrospun cellulose acetate (CA), with the modified membrane (M2-Mod) showing a reduced MWCO of 6700 Da compared to the unmodified membrane’s MWCO of 13,980 Da. Furthermore, the study aimed to identify the optimal polymeric nanocomposite of PVDF with nano-SnO 2 or ZnO, along with electrospun cellulose nanofibers, to enhance %PVA and %dye rejection while improving membrane productivity and fouling resistance. The formulation containing a mixture of SnO 2 and ZnO, in the presence of electrospun CA, demonstrated superior performance, achieving 98% PVA rejection, 95% reactive dye rejection, and a stable flux of 20 LMH, with a normalized flux of 92%. Overall, it can be concluded that the optimized modified membrane formulation (M2-Mod) exhibited excellent antifouling behavior, holding significant potential for promoting circular economy and sustainability in textile wastewater treatment.