Sensors International最新文献

{"title":"Near-field metasurface sensor for an early-stage breast cancer detection","authors":"Maged A. Aldhaeebi ,&nbsp;Thamer Almoneef ,&nbsp;Saeed Bamatraf ,&nbsp;A.O. Aldhaibain ,&nbsp;Osamah Bakhalah ,&nbsp;Saleh Alhdad ,&nbsp;Sumaia Bakhalah ,&nbsp;M. Kamran Saleem","doi":"10.1016/j.sintl.2024.100305","DOIUrl":"10.1016/j.sintl.2024.100305","url":null,"abstract":"<div><div>In this paper, a novel and highly sensitive metasurface sensor for microwave breast tumor detection is proposed. The proposed sensor array comprises 8 × 8 small-size sensor elements that are capable of reacting to changes in both electric and magnetic fields. This allows the sensor to detect even minor variations in the surrounding medium, resulting in improved sensitivity. Additionally, designing a sensor array improves sensitivity by covering all areas of the breast tissues with multiple small sensor elements. Numerical studies have been conducted to assess the sensor sensitivity using realistic healthy and non-healthy breast models with diagnosed tumors placed at different locations within healthy breast models in the CST simulation environment at varying stand-off distances. An experiment was conducted to validate the sensor’s concept. It involved testing a metasurface sensor with phantoms resembling both healthy female breast tissues and those with a 10 mm tumor. The results from simulations and experiments demonstrate that the metasurface sensor is capable of detecting breast tumors at different distances. For safety compliance, specific absorption rate (SAR) values were obtained through both simulation and experimentation. The simulated SAR values were calculated to be 0.357 W/kg and 0.216 W/kg at 1 g and 10 g, respectively, using 17 dBm for safety. The measured SAR values were 0.101 W/kg and 0.1 W/kg at 1 g and 10 g, respectively.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100305"},"PeriodicalIF":0.0,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular engineering of a fluorescent probe for highly efficient detection of human serum albumin in biological fluid","authors":"Raja Chinnappan ,&nbsp;Tanveer Ahmad Mir ,&nbsp;Shanmugam Easwaramoorthi ,&nbsp;Gopika Sunil ,&nbsp;Ancy Feba ,&nbsp;Balamurugan Kanagasabai ,&nbsp;Shadil Ibrahim Wani ,&nbsp;Maram N. Sandouka ,&nbsp;Alaa Alzhrani ,&nbsp;Sandhanasamy Devanesan ,&nbsp;Mohamad S. AlSalhi ,&nbsp;Naresh Kumar Mani ,&nbsp;Wael Al-Kattan ,&nbsp;Ahmed Yaqinuddin ,&nbsp;Abdullah M. Assiri ,&nbsp;Dieter C. Broering","doi":"10.1016/j.sintl.2024.100304","DOIUrl":"10.1016/j.sintl.2024.100304","url":null,"abstract":"<div><div>Human serum albumin (HSA) is synthesized by the liver, accounting for 60 % of total plasma protein in vertebrates' blood. It is the most predominant extracellular plasma protein that acts as a repository and transporter of exogenous and endogenous substances in the blood of healthy humans. Decreased albumin concentration in the human body or its abnormal levels indicate the occurrence of hepatic, renal, and digestive-related diseases. Therefore, accurate quantification of HSA is of great significance in diagnostic testing and routine clinical analysis of albumin-linked diseases. Herein, a class of triphenylamine rhodanine-3-acetic acid (mRA)-a bifunctional fluorescent molecule with twisted intramolecular charge transfer (TICT)-induced emission characteristics is synthesized and employed as a novel sensing probe for the fluorescent detection of human albumin. mRA can be selectively lighted up through site-specific interactions with serum albumin-binding moieties and show enhanced photophysical or biological response efficacy. Understanding the interaction of mRA with HSA at the molecular level was carried out using docking methodology to explore the site-specific interaction phenomenon. The resulting fluorescence strategy produced a dose-dependent signal response enhancement upon interaction with HSA in the concentration range of 0.01–400 μg/ml. The sensor probe exhibits a low detection limit of 10 ng/mL and is found to be a feasible, low-cost, and effective approach for HSA analysis in complex biological fluids for early detection and diagnosis of albumin-related diseases.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100304"},"PeriodicalIF":0.0,"publicationDate":"2024-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Privacy-concerned averaged human activeness monitoring and normal pattern recognizing with single passive infrared sensor using one-dimensional modeling","authors":"Tajim Md. Niamat Ullah Akhund,&nbsp;Kenbu Teramoto","doi":"10.1016/j.sintl.2024.100303","DOIUrl":"10.1016/j.sintl.2024.100303","url":null,"abstract":"<div><div>Detecting human activity through cameras and machine learning methods raises significant privacy concerns, while alternatives like thermal cameras can be expensive. Passive infrared (PIR) sensors present a cost-effective and privacy-preserving solution, commonly used in home settings for motion detection. This study introduces a system for monitoring human activeness using a single PIR sensor, focusing on privacy preservation. The proposed one-dimensional model, based on the Laplace distribution, emphasizes the role of the parameter <span><math><mi>μ</mi></math></span> in defining velocity distributions. Through real-world experiments with a Raspberry Pi and PIR sensor, the effectiveness of the model in capturing human activeness is validated. The study investigates how different <span><math><mi>μ</mi></math></span> values correlate with activity levels and detect abnormalities. Additionally, the paper addresses the stochastic nature of human behavior, and the impact of <span><math><mi>μ</mi></math></span> on predictability and variability, and provides insights into detection thresholds and interval times. The findings highlight the potential for enhancing abnormality detection and suggest a comprehensive understanding of human activeness.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100303"},"PeriodicalIF":0.0,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142427576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A method to detect enzymatic reactions with field effect transistor","authors":"Alexander Kuznetsov ,&nbsp;Mariia Andrianova ,&nbsp;Dmitriy Ryazantsev ,&nbsp;Andrey Sheshil ,&nbsp;Vitaliy Grudtsov ,&nbsp;Valerii Vechorko ,&nbsp;Natalia Komarova","doi":"10.1016/j.sintl.2024.100302","DOIUrl":"10.1016/j.sintl.2024.100302","url":null,"abstract":"<div><div>Study of enzyme-substrate interactions is a task of great practical and scientific importance. This paper describes the application of ion-sensitive field effect transistors in quasi-equilibrium state for examination of enzymatic reactions. A reaction occurring in the liquid gate affects the chemical potential of electrons in this gate, and this phenomenon may be used to explore biochemical interactions. This strategy can be applied to detect interactions of enzymes with substrates, inhibitors and activators regardless of their optical and electrochemical properties. Using the developed method, the reactions catalyzed by the enzymes belonging to six different EC classes were analyzed, and Michaelis constants for their substrates were determibed. <em>K</em>_<em>m</em> values obtained using the proposed method were in good agreement with those obtained with standard colorimetric and fluorimentric assays. Practical potential of the described method was demonstrated by studying the interactions of a diagnostically significant enzyme α-D-galactosidase with its natural and artificial substrates and its inhibitor. <em>K</em>_<em>m</em> values for α-D-galactosidase using melibiose and raffinose as substrates and IC50 value for the enzyme inhibitor 1-deoxygalactonojirimycin were determined. The described method allows rapid and label-free investigation of enzyme interactions with substrates, inhibitors and activators for a wide range of biocatalysts.</div></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100302"},"PeriodicalIF":0.0,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S266635112400024X/pdfft?md5=4d52ee86a1d882d955efddee7d99e5d4&pid=1-s2.0-S266635112400024X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blue luminescent carbon quantum dots derived from diverse banana peels for selective sensing of Fe(III) ions","authors":"Noona Shahada Kunnath Parambil ,&nbsp;Arish Dasan ,&nbsp;Amrutha Thaivalappil Premkumar ,&nbsp;Neeroli Kizhakayil Renuka ,&nbsp;Selwin Joseyphus Raphael","doi":"10.1016/j.sintl.2024.100301","DOIUrl":"10.1016/j.sintl.2024.100301","url":null,"abstract":"<div><p>The eco-friendly production of carbon quantum dots (CQDs) from natural resources remains appealing owing to their superior optical properties. This work presents the synthesis of highly fluorescent CQDs from peels of different varieties of Musa (yellow, green, and red) through a straightforward one-step hydrothermal process, without needing a bit of metal salt or oxidizing agent. The proposed method resulted in quantum yields (QY) of 18.06 %, and 13.06 %, for CQDs from normal yellow banana and green banana, respectively compared to other CQDs derived from natural sources. The QY for the CQDs extracted from the small yellow banana was 7.72 %, while the red banana had a much lower value of 2.6 %. The optical properties of CQDs of different banana peels are also compared. All the CQDs produced a blue color upon exposure to 360 nm UV radiation, and the fluorescence was excitation-dependent. Moreover, each of the four types of CQDs is proven to be an efficient fluorescent probe capable of selectively detecting Fe³⁺ ions. The linear variation of fluorescence with the analyte amount allowed quantification of ions, with a limit of the detection value of 6 μM, across a concentration range of 37–277 μM. Above all, the real-world applications aimed at sensing Fe³⁺ ions in tap water achieved excellent recoveries ranging from 96 to 100 %. Therefore, these tuneable CQDs with good optical properties present an auspicious avenue for developing nano-sensors in real-time applications.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100301"},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000238/pdfft?md5=048be3cb09037da0abdfa379b16ba763&pid=1-s2.0-S2666351124000238-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142163401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A capacitive sensor-based approach for type-2 diabetes detection via bio-impedance analysis of erythrocytes","authors":"Santu Guin ,&nbsp;Debjyoti Chowdhury ,&nbsp;Madhurima Chattopadhyay","doi":"10.1016/j.sintl.2024.100300","DOIUrl":"10.1016/j.sintl.2024.100300","url":null,"abstract":"<div><p>This paper presents a novel capacitive sensor-based device for detecting type-2 diabetes through blood analysis. The proposed methodology measures changes in the complex permittivity of red blood cells (RBCs) caused by elevated glucose levels, affecting their rheological and electrical properties, such as viscosity, volume, relative permittivity, dielectric loss, and AC conductivity. These changes, well-documented in the literature, alter the bio-impedance signature of RBCs, serving as an indicator for type-2 diabetes. The study examines various concentrations of normal and diabetic RBCs within a frequency range of 50 kHz to 200 kHz, chosen for its relevance to bio-impedance responses. Experimental results show that healthy RBCs in a 200 <span><math><mi>μ</mi></math></span>L PBS solution have a complex permittivity (<span><math><msub><mrow><mi>ɛ</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) of 65.12 and conductivity (<span><math><msub><mrow><mi>σ</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) of 0.63 S/m, while diabetic RBCs measure 73.44 and 0.68 S/m, respectively. Additionally, the complex permittivity decreases as the cell concentration increases for both normal and diabetic RBCs. At 100% cell concentration, the average bio-impedance for diabetic blood cells is 50.3 k<span><math><mi>Ω</mi></math></span>, compared to 56.7 k<span><math><mi>Ω</mi></math></span> for healthy blood cells over the entire frequency range. The standard deviation of bio-impedance (<span><math><msub><mrow><mi>Z</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) between 50 kHz and 200 kHz highlights the difference between healthy and diabetic RBCs, with 200 kHz measurements proving more reliable. To detect these bio-impedance changes, an interdigitated electrode (IDE) capacitive sensor with 40 capacitive elements was simulated. The complex bio-impedance (<span><math><msub><mrow><mi>Z</mi></mrow><mrow><mtext>mix</mtext></mrow></msub></math></span>) was measured within the 50 kHz–200 kHz frequency range, providing clear differentiation between healthy and diabetic blood cells. Simulation using Finite Element Method (FEM) through COMSOL® software supports these findings, showcasing the sensor’s efficacy in type-2 diabetes detection.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100300"},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000226/pdfft?md5=0226af151d2c9f55fe118223b4378c18&pid=1-s2.0-S2666351124000226-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142157556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The application of ultrasonic measurement and machine learning technique to identify flow regime in a bubble column reactor","authors":"Wongsakorn Wongsaroj ,&nbsp;Natee Thong-Un ,&nbsp;Jirayut Hansot ,&nbsp;Naruki Shoji ,&nbsp;Weerachon Treenuson ,&nbsp;Hiroshige Kikura","doi":"10.1016/j.sintl.2024.100294","DOIUrl":"10.1016/j.sintl.2024.100294","url":null,"abstract":"<div><p>This paper presents a novel technique to classify the flow regimes in bubble columns. The ultrasonic velocity profiler is employed to detect the velocity deviation and echo characteristic of bubbles rising in the column. This information is set as attribute data for the machine learning algorithm. Classification-based machine learning is utilized to classify the flow regimes: bubbly, transition, and churn turbulent, which are defined as categories of the algorithm. Several classifiers were applied in this work, such as K-nearest neighbors, Decision tree, Support vector machines, Naive bayes, and Logical regression. The experimental demonstration was conducted to verify the performance of the proposed technique. Three kinds of two-phase flow with stagnant liquid that had various viscosities were used for the experiment. The air within the superficial velocity range was injected to alter the flow regime. The flow regime classification model was set. The proposed method was applicable to identify the flow regimes. The classifiers were tested, and their accuracy was evaluated.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100294"},"PeriodicalIF":0.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000160/pdfft?md5=9d84de0129f6d8575eb79192d50010b6&pid=1-s2.0-S2666351124000160-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GA-mADAM-IIoT: A new lightweight threats detection in the industrial IoT via genetic algorithm with attention mechanism and LSTM on multivariate time series sensor data","authors":"Yakub Kayode Saheed ,&nbsp;Adekunle Isaac Omole ,&nbsp;Musa Odunayo Sabit","doi":"10.1016/j.sintl.2024.100297","DOIUrl":"10.1016/j.sintl.2024.100297","url":null,"abstract":"&lt;div&gt;&lt;p&gt;The Industrial Internet of Things (IIoT) is undergoing rapid development, and as a result, security threats have emerged as a significant concern. IIoT networks, while enhancing service quality, are particularly susceptible to security risks because of their intrinsic interconnectedness and the use of low-power devices. The data produced by millions of sensors in the IIoT is highly dynamic, diverse, and of massive magnitude. The risk of dangers to IoT gadgets in a nuclear plant or a petroleum refinery is significantly greater when compared to that of home appliances. Often connected to the internet, IIoT devices and systems lack robust security measures, rendering them susceptible to cyberattacks. A breach in IIoT security could result in data theft, equipment damage, or even physical harm. To mitigate these risks, IIoT systems require secure authentication and encryption protocols, regular software updates, and proactive monitoring and response capabilities. These methods' primary disadvantages are their difficulty in implementation and inability to ensure effective security. Hence, a second line of protection, such as intrusion threat detection in IIoT, is required. In this research, we propose a new threat intrusion detection model in the IIoT through a genetic algorithm with attention mechanism and modified Adam optimized LSTM (GA-mADAM-IIoT). The GA-mADAM-IIoT consists of six modules: the activity receiver, communication module (CM), attention module (AM), intrusion detection module, mitigation module, and alert module. The GA was designed for feature dimensionality and selection trained on network flow data via a Long Short-Term Memory (LSTM) network. The adaptive moment estimation (Adam) optimizer was modified in order to optimize the LSTM (mADAM-LSTM) networks. To enhance the performance of our model, the categorical cross-entropy (CCE) cost function was used to calculate the difference between the predicted output and the actual output. Additionally, the CCE cost function optimized the model's parameters to minimize the difference between predicted and actual values in terms of probability distributions. The Modified Adam (mADAM) optimization algorithm updates the weights and biases of the LSTM to minimize the cost function. Due to the limited availability of real-world datasets containing accurately labelled anomalies, particularly for industrial facilities and manufacturing facilities, we have utilized two sensor datasets derived from physical test-bed systems for water treatment: Secure Water Treatment (SWaT) and Water Distribution (WADI). In these datasets, operators have simulated attack scenarios that occur in real-world water treatment plants and have recorded these instances as the ground truth anomalies. A regularization parameter was added to the cost function to prevent LSTM from overfitting. In order to improve the model's performance, the AM integrates a succinct yet effective attention mechanism that enhances signif","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100297"},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000196/pdfft?md5=0f668b7a84f563684bd248606646127e&pid=1-s2.0-S2666351124000196-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142150759","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PCR-free and minute-scale electrochemical analysis of porcine DNA adulteration via molecularly amplified DNA sandwich assay","authors":"Vasita Lapee-e ,&nbsp;Suphachai Nuanualsuwan ,&nbsp;Sudkate Chaiyo ,&nbsp;Abdulhadee Yakoh","doi":"10.1016/j.sintl.2024.100299","DOIUrl":"10.1016/j.sintl.2024.100299","url":null,"abstract":"<div><p>The increasing incidence of meat adulteration and mislabeling poses significant challenges in terms of food safety and consumer trust. This study proposes an electrochemical DNA biosensor for detecting porcine mitochondrial DNA in tainted meat products, offering a novel approach to address the above challenges. Unlike conventional nucleic acid amplification tests that rely on polymerase chain reactions (PCRs), the proposed biosensor employs a molecularly amplified DNA strategy with DNA tracers that bind to two regions of the target DNA, creating an elongated hybridization structure with multiple redox-tagging molecules. This design catalyzes detection signals autonomously, eliminating the need for PCR amplification. One-step DNA probe immobilization using poly-adenine (poly-A) oligonucleotides significantly improves hybridization efficiency and reduces the necessity for extensive sample purification, thereby simplifying the detection process. The proposed biosensor exhibits a linear detection range of 10¹–10⁶ pM and a limit of detection (LOD) of 2.2 pM in controlled settings. Furthermore, the proposed biosensor distinguishes pork from beef in adulterated samples with a LOD of 1 % w/w. With its stability exceeding 9 weeks and a cost of less than 0.5 USD per test, the proposed biosensor offers a highly sensitive, economically viable solution with significant potential for widespread use in the meat industry and by end-users, effectively combating porcine adulteration.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100299"},"PeriodicalIF":0.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000214/pdfft?md5=868fc1769960450c6e946164df78a50f&pid=1-s2.0-S2666351124000214-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication, catalytic activity, metal sensing ability and electrochemical evaluation of nano silver particles for supercapacitor applications","authors":"Anindita De ,&nbsp;Pawan Singh Dhapola ,&nbsp;Preeti Jain ,&nbsp;Anjali Kathait ,&nbsp;Misbah Shahid ,&nbsp;Eliho Votsa ,&nbsp;Markus Diantoro ,&nbsp;Serguei V. Savilov","doi":"10.1016/j.sintl.2024.100298","DOIUrl":"10.1016/j.sintl.2024.100298","url":null,"abstract":"<div><p>In this work, stable, spherical silver nanoparticles (MAgNp) were prepared via a green synthesis method using flowers of Myristica fragrans (nutmeg). This flower is abundant in phytochemicals such as saponins that can be utilized as reductants to produce silver nanoparticles. The synthesized nanoparticles were examined using a variety of physico-chemical methods, including transmission electron microscopy (TEM), Dynamic light scattering (DLS), elemental dispersive X-ray spectroscopy (EDX), powder X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and UV–VIS spectrometer. EDX study confirmed the crystalline and face-centered cubic (FCC) structure of AgNP. The majority of particles are present with a higher percentage intensity at an average size of 58.77 nm as revealed in the TEM image, PDI was found to be 0.055. MAgNPs demonstrated perfect activity in the catalytic degradation of methylene blue dye (88 %) and para-nitrophenol (98 %), both anthropogenic pollutants. These nanoparticles were further used as plasmonic sensors to detect heavy metals like Fe(II) and Hg(II) in an aqueous solution. The minimum detection limit was found to be 0.2 mM for Hg(II) and 10  μM for Fe(II) with good linearity. The electrochemical properties of MAgNPs were studied using a carbon supercapacitor electrode coated with MAgNPs. Results from cyclic voltammetry were also determined, and they showed a high specific capacitance of 41 F/gm at 5 mV/s scan rate.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":"6 ","pages":"Article 100298"},"PeriodicalIF":0.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666351124000202/pdfft?md5=227c07a67bdb3411c5e8c034606070b6&pid=1-s2.0-S2666351124000202-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}