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Surface tempering of poly-(3 thiophene acetic acid) coated carbon fiber paper electrode with spine-like cobalt inorganic phosphate: An efficacious electrochemical metol sensor /
Surfaces and Interfaces, Vol.35, ISSN No: 2468-0230.
N-methyl-p-aminophenol sulfate (metol) is a photographic developing agent that has a toxic effect on humans and aquatic life. A cost-effective and sensitive electrochemical sensor was developed by electrodepositing Co-Pi over poly-(3 thiophene acetic acid) coated carbon fiber paper electrode (Co-Pi/PTAA/CFP) for the determination of metol (ML). Surface modification of Co-Pi facilitates superior electrocatalytic performance by offering more active sites and faster electron transport kinetics. The Physico-chemical characterization of the fabricated electrode was carried out by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) Field emission scanning electron microscopy (FESEM) with energy-dispersive X-ray spectroscopy (EDS), Optical profilometer, Fourier transform infrared spectroscopy (FTIR), and electroanalytical techniques. -
Surface tempering of poly-(3 thiophene acetic acid) coated carbon fiber paper electrode with spine-like cobalt inorganic phosphate: An efficacious electrochemical metol sensor
N-methyl-p-aminophenol sulfate (metol) is a photographic developing agent that has a toxic effect on humans and aquatic life. A cost-effective and sensitive electrochemical sensor was developed by electrodepositing Co-Pi over poly-(3 thiophene acetic acid) coated carbon fiber paper electrode (Co-Pi/PTAA/CFP) for the determination of metol (ML). Surface modification of Co-Pi facilitates superior electrocatalytic performance by offering more active sites and faster electron transport kinetics. The Physico-chemical characterization of the fabricated electrode was carried out by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) Field emission scanning electron microscopy (FESEM) with energy-dispersive X-ray spectroscopy (EDS), Optical profilometer, Fourier transform infrared spectroscopy (FTIR), and electroanalytical techniques. The electrochemical studies were performed using Cyclic voltammetry (CV), Electron Impedance spectroscopy (EIS), and Differential pulse voltammetric (DPV). DPV studies revealed excellent sensing performance for ML, with a wide linear dynamic range of 6 nM to 800 nM, and a limit of detection (LOD) of 2 nM. A distinctive oxidative anodic peak was observed at 0.11 V indicating the excellent electrochemical performance of the electrode. The results suggested that the developed electrode exhibited good catalytic activity, selectivity, and sensitivity towards the electrochemical determination of ML. Further, the developed electrode was extended to its application in real samples obtained from lake water and domestic wastewater. 2022 -
Surface Roughness Analysis in AWJM for Enhanced Workpiece Quality
Abrasive Water Jet Machining is a distinctive manufacturing process that effectively removes material from a workpiece by employing a high-pressure stream of water combined with abrasive particles. The final quality of the machined surface is directly influenced by various process parameters, such as the traverse speed, hydraulic pressure, stand-off distance, abrasive flow rate, and the specific type of abrasive used. In recent times, extensive research has been undertaken to enhance the performance of AWJM, with a specific focus on critical performance measures like surface roughness. This paper presents the latest advancements in AWJM research, with particular attention given to enhancing performance measures, implementing process monitoring and control, and optimizing process variables for applications involving high-carbon steel. 2024 E3S Web of Conferences -
Surface modulation and structural engineering of graphitic carbon nitride for electrochemical sensing applications /
Journal of Nanostructure in Chemistry, Vol.12, Issue 5, ISSN No: 2193-8865.
The rediscovery of the old-age material graphitic carbon nitride (g-C3N4), a 2D conducting polymer, has given rise to a tide of articles exploring its diverse applications. Recently, owing to its excellent physicochemical stability and tunable electronic structure, the material has proven to be an eminent candidate for improving the sensing quality of electrodes. Excellent properties of g-C3N4 such as exposed surface area, metal-free characteristics, and low-cost synthesis have attracted facile and economical designing of sensors for a variety of analyte molecules. Herein, the readers are introduced to the historical development of g-C3N4 and escorted to the present findings of its electrochemical sensing applications. Along with its sensing utilities, the review shares some exciting insights into the synthesis, structural, and surface chemistry modulations of g-C3N4. -
Surface modulation and structural engineering of graphitic carbon nitride for electrochemical sensing applications
The rediscovery of the old-age material graphitic carbon nitride (g-C3N4), a 2D conducting polymer, has given rise to a tide of articles exploring its diverse applications. Recently, owing to its excellent physicochemical stability and tunable electronic structure, the material has proven to be an eminent candidate for improving the sensing quality of electrodes. Excellent properties of g-C3N4 such as exposed surface area, metal-free characteristics, and low-cost synthesis have attracted facile and economical designing of sensors for a variety of analyte molecules. Herein, the readers are introduced to the historical development of g-C3N4 and escorted to the present findings of its electrochemical sensing applications. Along with its sensing utilities, the review shares some exciting insights into the synthesis, structural, and surface chemistry modulations of g-C3N4. A great many approaches for overcoming the inherent limitations have also been critically discussed, starting with the precursor in use. This review article aims to provide a concise perspective and direction to future researchers for enabling them to fabricate smart and eco-friendly sensors using g-C3N4. Graphical abstract: [Figure not available: see fulltext.] 2021, The Author(s), under exclusive licence to Islamic Azad University. -
Surface modified graphene/SnO2 nanocomposite from carbon black as an efficient disinfectant against Pseudomonas aeruginosa
Carbon based nanocomposite with well-defined integrated properties are highly sort after in the field of nanobiotechnology and nanomedicine. We report a facile one step hydrothermal route for the production of graphene sheets interlaced with SnO2 nanoparticles. Graphene oxide (GO)sheets are obtained by the surface functionalization of powdered carbon black. A facile hydrothermal method is employed to integrate SnO2 nanostructures over the graphene surface. All the samples exhibited long term stability and unique fluorescence response with no sign of photobleaching even after a storage of 30 months. Antibacterial activity of the samples at each stage is tested against Pseudomonas aeruginosa, which is a highly resilient bacterial strain possessing very high attributable mortality rate and causes a variety of ailments from diarrhea to meningitis. Bactericidal activity of carbon black, GO derived from carbon black and graphene-SnO2 nanocomposite is tested against Pseudomonas aeruginosa using disk diffusion assay for the first time. Comparing the zone of inhibition produced by carbon black, GO and the nanocomposite, highest antibacterial performance is exhibited by the nanocomposite sample (25 0.3 mm)followed by GO (16 0.5 mm)and pristine carbon black (14 0.3 mm). The bactericidal ability of the nanocomposite increased by ?79% compared to pristine carbon black. MIC analysis revealed that the nanocomposite could inhibit the bacterial growth at a much lower concentration (250 ?g/mL)compared to the precursors. The high antibacterial efficacy and long-term stability of graphene-tin oxide nanocomposite synthesized from carbon black facilitates its usage as a potent antibacterial agent in disinfectant and sanitation industry. 2019 Elsevier B.V. -
Surface modified CaO nanoparticles with CMC/D-carvone for enhanced anticancer, antimicrobial and antioxidant activities
The rising prevalence of antimicrobial resistance and the continued challenge to cancer therapy are in desperate need of developing innovative therapeutic strategies. In this regard, the present research work focuses on the development of CaO NPs and CaO-CMC-Dcar nanocomposites for enhanced antimicrobial and anti-cancer activities. CaO nanoparticles were synthesized by facile one pot chemical approach and eventually functionalized with CMC and D-carvone biomolecules. XRD analysis revealed that the crystallite size for CaO and CaO-CMC-Dcar nanoparticles was found to be 21.18 nm and 17.02 nm respectively. The band gap values obtained for CaO and CaO-CMC-Dcar nanoparticles were 4.44 eV, and 4.25 eV respectively. The CaO-CMC-Dcar nanoparticles show absorption maxima at 292 nm, slightly red-shifted from bare CaO nanoparticles. HRTEM and SEM analysis revealed that the prepared samples were roughly spherical and agglomerated in nature. Antimicrobial activity was evaluated against methicillin-resistant Staphylococcus aureus (MRSA) and Candida albicans. The zone of inhibition (ZOI) for CaO-CMC-Dcar nanoparticles against MRSA and C. albicans was 20.1 0.3 mm and 21.1 0.2 mm, respectively, significantly higher than that of pure CaO nanoparticles (14.1 0.2 mm and 13.2 0.1 mm) and comparable to standard anti-bacterial streptomycin and antifungal fluconazole discs. Anticancer activity was assessed via MTT assay against MOLT-4 blood cancer cells, where the IC50 values for CaO and CaO-CMC-Dcar nanoparticles were 22.6 ?g/mL and 21.54 ?g/mL, respectively. Additionally, CaO-CMC-Dcar nanoparticles exhibited enhanced antioxidant activity (80 %) compared to CaO (70 %) at 20 ?g/mL, with performance comparable to that of Vitamin C. Experimental results revealed that the CaO-CMC-Dcar nanoparticles exhibited superior biological activity compared to pure CaO nanoparticles. 2025 Indian Chemical Society -
Surface functionalized fluorescent carbon nanoparticles and their applications
Fluorescent carbon nanoparticles or carbon dots (CDs) are zero-dimensional nanomaterials embodying physicochemical characteristics appropriate for novel and improved applications in various disciplines. Tunable photoluminescence, photostability, small size, low cost, biocompatibility, etc., are some of the promising features of CDs. The CDs are usually composed of a graphitic core surrounded by shell layers containing various functional groups. Surface functionalization of CDs is known to customize, and regulate the properties of CDs, thereby proliferating their applications. A variety of physical and chemical methods have been used for the preparation of CDs with tailored surfaces. The choice of the synthetic strategy generally depends on the type of surface modification required and the fluorescence behavior expected. This chapter summarizes and discusses the existing strategies for preparing surface functionalized CDs and the resultant fluorescence phenomena. The surface functionalization of CDs can decisively influence their suitability in several applications. In some applications, surface functionalization improves the existing utility, while novel utilities are emerging in others. The influence of surface functionalities of CDs on biomedical and catalytic applications has been discussed in detail in this chapter. CDs have emerged as a promising material for enhancing the performance, sustainability, and safety of various energy storage devices like batteries, supercapacitors etc. Continued research and development in this area could lead to the realization of more efficient and environmentally friendly energy storage solutions. The chapter concludes by discussing the challenges in synthesizing surface functionalized CDs and their acceptability in biomedical and industrial applications. 2025 Elsevier Inc. All rights are reserved including those for text and data mining AI training and similar technologies. -
Surface adsorption and anticorrosive behavior of benzimidazolium inhibitor in acid medium for carbon steel corrosion /
Journal of Applied Electrochemistry, Vol.52, Issue 11, pp.1659–1674, ISSN No: 0021-891X (Print) 1572-8838 (Online).
Corrosion inhibition property of a newly synthesized 3-(4-chlorobenzoylmethyl) benzimidazolium bromide inhibitor against carbon steel corrosion in 1 N hydrochloric acid solution was studied and analyzed utilizing various electrochemical methods. Electrochemical impedance study inferred that the inhibition efficiency increased with increasing inhibitor concentration and give 93.5% at 250 ppm. Potentiodynamic polarization study emphasized that inhibitor acted as a mixed type inhibitor and the adsorption of inhibitor on the metal surface followed Langmuir adsorption isotherm. The noise results were in good correlation with other electrochemical results obtained. -
Surface adsorption and anticorrosive behavior of benzimidazolium inhibitor in acid medium for carbon steel corrosion
Corrosion inhibition property of a newly synthesized 3-(4-chlorobenzoylmethyl) benzimidazolium bromide inhibitor against carbon steel corrosion in 1N hydrochloric acid solution was studied and analyzed utilizing various electrochemical methods. Electrochemical impedance study inferred that the inhibition efficiency increased with increasing inhibitor concentration and give 93.5% at 250ppm. Potentiodynamic polarization study emphasized that inhibitor acted as a mixed type inhibitor and the adsorption of inhibitor on the metal surface followed Langmuir adsorption isotherm. The noise results were in good correlation with other electrochemical results obtained. The increase of inhibition efficiency with concentrations of inhibitor is attributed to the blocking of the active area by the inhibitor adsorption on the metal surface. The thermodynamic parameter values were calculated and discussed to explain the adsorption mechanism of inhibitor in an acidic medium. The protective surface morphology governed by the inhibited medium was investigated using the scanning electron microscopic technique. The surface roughness of the sample in the absence and presence of inhibitor was obtained using atomic force microscopic study. The effect and reactivity of the inhibitor are further clarified with quantum chemical analysis. Finally, the corrosion protection mechanism is proposed on the ground of experimental and theoretical studies. Graphical abstract: [Figure not available: see fulltext.] 2022, The Author(s), under exclusive licence to Springer Nature B.V. -
Supreme court dialogue classification using machine learning models
Legal classification models help lawyers identify the relevant documents required for a study. In this study, the focus is on sentence level classification. To be more precise, the work undertaken focuses on a conversation in the supreme court between the justice and other correspondents. In the study, both the nae Bayes classifier and logistic regression are used to classify conversations at the sentence level. The performance is measured with the help of the area under the curve score. The study found that the model that was trained on a specific case yielded better results than a model that was trained on a larger number of conversations. Case specificity is found to be more crucial in gaining better results from the classifier. 2023 Institute of Advanced Engineering and Science. All rights reserved. -
Suppression and redfinition of self in the selct novels of Toni Morrison and ALice Walker
Literature is a mirror held onto the society that reflects the culture, history and socio-political issues of specific periods. Books have the uniqueness of transforming lives by weaving characters, to whom we are able to relate their trials, tribulations and achievements become our own. Although confined to the Afro-American milieu, Alice Walker s The Color Purple and Toni Morrison s The Bluest Eye, Sula and Beloved raises issues and concerns that are universal to women across the globe. These writers try to lend voice to an otherwise marginalized and newlinesuppressed group of women, who have been denied a dignified existence. This research, through the methodology of critical analysis and interpretation of texts, tries to understand the concept of self, from the western and eastern perspectives. In the due process, the various factors that contribute to the formation of an individual s self are also identified. Through an analysis of the newlinefemale protagonists in the works of Morrison and Walker, this study examines how it is possible for a woman to progress from the margins to a position that is central, from object to subject. newlineMost often, women are not even conscious that they too have an individuality of their own and need to lead a dignified life. Having got so habituated to oppression, it has almost become a way of life for them. They need to be conscious and aware of the fact that they have to create a space of their own, without compromising on their individuality and dignity. When they fail to do this,they just stagnate and become mere pawns in the hands of men and tend to get exploited. Most of newlinethe female protagonists discussed in this study, go through this phase and are unable to extricat themselves from the traumatized conditions that engulf them. newlineThis study clearly focuses on how women need to be conscious of what is happening to them and realize that they are being deprived of their individuality and dignity. -
Support Vector Machine Performance Improvements by Using Sine Cosine Algorithm
The optimization of parameters has a crucial influence on the solution efficacy and the accuracy of the support vector machine (SVM) in the machine learning domain. Some of the typical approaches for determining the parameters of the SVM consider the grid search approach (GS) and some of the representative swarm intelligence metaheuristics. On the other side, most of those SVM implementations take into the consideration only the margin, while ignoring the radius. In this paper, a novel radiusmargin SVM approach is implemented that incorporates the enhanced sine cosine algorithm (eSCA). The proposed eSCA-SVM method takes into the account both maximizing the margin and minimizing the radius. The eSCA has been used to optimize the penalty and RBF parameter in SVM. The proposed eSCA-SVM method has been evaluated against four binary UCI datasets and compared to seven other algorithms. The experimental results suggest that the proposed eSCA-SVM approach has superior performances in terms of the average classification accuracy than other methods included in the comparative analysis. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Support value based convultional neural networks system for internet of things /
Patent Number: 202041043751, Applicant: Dr.S.Selvakanmani.
The Traffic Congestion is one of major problem in Internet of Things (IOT) occurs due to insufficient data transfer between the Sensor nodes or due to data perception. Data perception in the IOT guarantee the information being detected by the sensors, information is recouped from the sensor network without having any redundancies. -
Supply chain performance measurement practices of Indian industries
In any industry, the supply chain performance plays a crucial role and it is vital in growth of the industry. Through this study, an attempt is made to find some insight to the supply chain performance measurement practices of Indian industries through an exploratory survey. The study reveals almost all the respondents (84%) felt that supply chain performance measurement system employed in their organisation has a clear purpose. Also, the study reveals that most supply chain performance measurement system provides high importance to quality measurements and includes both financial and non-financial indicators. The Multivariate analysis revealed three factors emerged from this study are 'Strategic Orientation' followed by 'Internal Focus' and 'Motivation and Control'. The study contributes to understanding the objectives of implementing supply chain performance measurement systems and metrics (measures) used in supply chain performance measurement systems. ExcelingTech Pub. -
Supply chain leadership in emerging markets: Understanding the role of trust, information management, and collaboration
The massive growth of emerging economies in last two decades has attracted many global companies to expand their physical presence in these countries. But the ability to take advantage of those opportunities is only available to companies that appreciate the environmental challenges and complexity of the region. The lexicon of extant literature focuses on enhancing supply chain leadership and development of efficient and effective strategies in developed economies, yet the corresponding literature in emerging economies is very fragmented. The aim of this chapter is to synthesize the current literature to understand the phenomenon including its definitions, dimensions, and constructs and to propose a conceptual model for successful supply chain leadership in emerging markets. The study tries to understand and establish the impact of various factors of supply chain leadership, which leads to sustainable supply chain performance. Collaboration and information management emerge as the major drivers for supply chain leadership in emerging markets and identifies trust as a mediating factor. 2020 by IGI Global. All rights reserved. -
Supervised machine learning technique for efficient management of cloud resources /
Patent Number: 202241053590, Applicant: Dr. S Balamurugan.
It is reported in literature that nearly 4.57 billion people access Internet, covering nearly 59% of global population as per 2020 statistics. With huge number of Internet users and large volumes of data, the need for secure and fault-tolerant web applications increases. Huge volumes of data are not only consumed, but are also converted and copied among multiple computing resources. Proposed is a Supervised Machine Learning Technique for efficient management of cloud resources. -
Supervised machine learning technique for efficient management of cloud resources /
Patent Number: 202241053590, Applicant: Dr. S Balamurugan.
It is reported in literature that nearly 4.57 billion people access Internet, covering nearly 59% of global population as per 2020 statistics. With huge number of Internet users and large volumes of data, the need for secure and fault-tolerant web applications increases. Huge volumes of data are not only consumed, but are also converted and copied among multiple computing resources. Proposed is a Supervised Machine Learning Technique for efficient management of cloud resources. -
Supervised Learning-Based Data Classification and Incremental Clustering
Using supervised learning-based data classification and incremental clustering, an unknown example can be classified using the most common class among K-nearest examples. The KNN classifier claims, Tell me who your neighbors are, and it will tell you who you are. The supervised learning-based data classification and incremental clustering technique is a simple yet powerful approach with applications in computer vision, pattern recognition, optical character recognition, facial recognition, genetic pattern recognition, and other fields. Its also known as a slacker learner because it doesnt develop a model to classify a given test tuple until the very last minute. When we say yes or no, there may be an element of chance involved. However, the fact that a diner can recognise an invisible food using his senses of taste, flavour, and smell is highly fascinating. At first, there can be a brief data collection phase: what are the most noticeable spices, aromas, and textures? Is the flavour of the food savoury or sweet? This information can then be used by the diner to compare the bite to other items he or she has had in the past. Earthy flavours may conjure up images of mushroom-based dishes, while briny flavours may conjure up images of fish. We view the discovery process through the lens of a slightly modified adage: if it smells like a duck and tastes like a chicken, youre probably eating chicken. This is a case of supervised learning in action. Machine learning can benefit from supervised learning, which is a concept that can be applied to it (ML). 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Supermarkets and Rural Inequality in India: A Case Study of Reliance Fresh
Drawing upon insights from growing strand of value chain literature, this article examines primary data collected from farmers supplying cauliflower and spinach to Reliance Fresh in the outskirts of Jaipur to understand the implication for farmer households of emergence of supermarket in a smallholder-dominated setting. The article finds that as a lead firm, Reliance Fresh is adopting flexible models of sourcing, devoid of any resource provision, to procure fresh produce of required quality and standards. In such a context, the barrier to participation of smallholders in supermarket-driven agri-food system varies across crops, depending on resource intensity of crops. Participation of smallholders, poorly endowed with human and physical capital, is limited in resource-intensive crop, such as cauliflower, because of high entry barrier in terms of requirement of assets. In contrast, entry barrier is low for smallholders in labour-intensive crop such as spinach, but competition among them, endowed with family labour, bid the rent down to the minimum. Gini decomposition exercise indicates that the emergence of supermarket-driven agri-food system has adverse distributional consequence in rural agrarian setting. Promotion of wholesale market with better infrastructure and encouragement of farmer federation as institutional innovations are suggested for inclusive agri-food marketing system. 2020 Institute of Rural Management.