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Surface-engineering of carbon fibre paper electrode through molecular imprinting technique towards electrochemical sensing of food additive in shrimps
Excessive usage of food additives needs to be extensively examined and regulated. Herein, we report the development of an exceptionally proficient and practical electrochemical sensor for the quantitative determination of 4-hexylresorcinol (4-HR) in shrimps using a molecularly imprinted conducting polymer. By electropolymerizing 2-aminothiazole (AT) on the surface of a carbon fibre paper electrode (CFP) in the presence of 4-HR imprinted polymer films were developed. Bulk-electrolysis was used to produce definite imprinting sites and regulate the release of 4-hexylresorcinol templates. Voltammetric study reveals that the synthesized conducting polymer has outstanding electroactivity towards 4-HR and enables quick electron transfer kinetics. This MIP sensor has a detection limit of 6.03 nM for 4-HR. The modified CFP electrode has been found to be extremely selective to 4-HR due to its intensive contact via intermolecular hydrogen bonding. The modified electrodes were characterized by Scanning Electron Microscopy, Fourier Transform Infrared spectroscopy, Optical profilometry, and X-ray Photoelectron Spectroscopy. 2022 Elsevier B.V. -
Surface water detection and delineation using remote sensing images: a review of methods and algorithms
Multispectral and hyperspectral images captured by remote sensing satellites or airborne sensors contain abundant information that can be used to study and analyze objects of interest on the surface of earth and their properties. The potential of remotely sensed images for studying natural resources like water has been studied by researchers over the past many years. As water is an important natural resource that needs to be conserved, such studies have been of great interest to the scientific community. By employing appropriate digital image processing techniques on images taken from remote sensing satellites or airborne sensors, an effective system can be developed to study the quantitative and qualitative changes happening to surface water bodies over a period of time. Surface water detection and mapping is a crucial and necessary step in such studies and different automated and semi-automated methods have been developed over the years for mapping water in remotely sensed images. Remote sensing sensors capture images at multiple bands corresponding to different wavelength ranges in the EM spectrum. Digital image processing based techniques for water mapping falls predominantly into four categories; (i) single band based methods, (ii) spectral index based methods, (iii) machine learning based methods and (iv) spectral mixture analysis based methods. This paper presents a review of techniques, methods, algorithms and the sensors/satellites that have been developed and experimented with to perform surface water body detection and delineation from remote sensing images. 2020, Springer Nature Switzerland AG. -
Surface tuning of nanostructured graphitic carbon nitrides for enhanced electrocatalytic applications: a review
The precursors for developing sustainable and environment-friendly energy conversion and storage devices requires the utilization of advanced, highly efficient, and economical nano-structured electrocatalysts instead of conventional and expensive noble metals. Therefore, graphitic carbon nitride (g-C3N4) as a material has gained wide attention due to its relative ease of synthesis, high nitrogen content, conductivity, and tuneable band gap energy. In recent years, their tunable electronic properties along with physicochemical stability have given rise to numerous research delving into their diverse range of applications. With the advancement in the tuning of their electrochemical performance, the electrical conductivity of g-C3N4 can be enhanced by structurally modifying the g-C3N4 framework accordingly. This review focuses on various structural modifications of g-C3N4 by functionalization, elemental doping, and hybridizing techniques for ameliorating the number of active sites resulting in enhanced electrocatalytic performance. Herein, the prospective researchers are given a concise perspective regarding the surface tuning of g-C3N4 for improving their electrocatalytic applications. 2023 Elsevier Ltd -
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.