ECS sensors plus最新文献_第5页

Expanding the Monolayer Scope for Nucleic Acid-Based Electrochemical Sensors Beyond Thiols on Gold: Alkylphosphonic Acids on ITO. 扩大基于核酸的电化学传感器的单层范围，超越金上的硫醇:ITO上的烷基膦酸。

ECS sensors plus Pub Date : 2023-03-01 Epub Date: 2023-03-29 DOI: 10.1149/2754-2726/acc4d9

Alexander Shaver, Netzahualcóyotl Arroyo-Currás

{"title":"Expanding the Monolayer Scope for Nucleic Acid-Based Electrochemical Sensors Beyond Thiols on Gold: Alkylphosphonic Acids on ITO.","authors":"Alexander Shaver, Netzahualcóyotl Arroyo-Currás","doi":"10.1149/2754-2726/acc4d9","DOIUrl":"10.1149/2754-2726/acc4d9","url":null,"abstract":"<p><p>Electrochemical biosensors are a powerful and rapidly evolving molecular monitoring technology. Evidenced by the success of the continuous glucose monitor in managing Type 1 Diabetes, these sensors are capable of precise, accurate measurements in unprocessed biological environments. Nucleic acid-based electrochemical sensors (NBEs) are a specific type of biosensor that employs the target binding and conformational dynamics of nucleic acids for signal transduction. Currently, the vast majority of NBEs are fabricated via self-assembly of alkylthiols on Au electrodes. However, this architecture is limited in scope, as Au electrodes are not universally deployable for all potential NBE applications. Here, to expand the repertoire of materials on which NBEs can be made, we describe the multistep procedure for creating sensing monolayers of alkylphosphonic acids on a conductive oxide surface. Using such monolayers on indium tin oxide (ITO)-coated glass slides, we couple redox reporter-modified nucleic acids and demonstrate signaling of procaine-binding NBE sensors in buffer and human serum. We investigate the operational stability of these NBE sensors to reveal faster signal loss relative to benchmark thiol-on-gold sensing layers, a result that arises due to poor stability of the underlying ITO. Finally, we discuss future directions to continue expansion of NBE sensor materials and applications.</p>","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":"2 1","pages":"010601"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10053865/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10348772","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}

引用次数: 0

Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays 混合电位电化学传感器阵列识别天然气的机器学习算法比较

ECS sensors plus Pub Date : 2023-02-22 DOI: 10.1149/2754-2726/acbe0c

Neal Ma, Sleight Halley, K. Ramaiyan, F. Garzon, L. Tsui

{"title":"Comparison of Machine Learning Algorithms for Natural Gas Identification with Mixed Potential Electrochemical Sensor Arrays","authors":"Neal Ma, Sleight Halley, K. Ramaiyan, F. Garzon, L. Tsui","doi":"10.1149/2754-2726/acbe0c","DOIUrl":"https://doi.org/10.1149/2754-2726/acbe0c","url":null,"abstract":"Mixed-potential electrochemical sensor arrays consisting of indium tin oxide (ITO), La0.87Sr0.13CrO3, Au, and Pt electrodes can detect the leaks from natural gas infrastructure. Algorithms are needed to correctly identify natural gas sources from background natural and anthropogenic sources such as wetlands or agriculture. We report for the first time a comparison of several machine learning methods for mixture identification in the context of natural gas emissions monitoring by mixed potential sensor arrays. Random Forest, Artificial Neural Network, and Nearest Neighbor methods successfully classified air mixtures containing only CH4, two types of natural gas simulants, and CH4+NH3 with >98% identification accuracy. The model complexity of these methods were optimized and the degree of robustness against overfitting was determined. Finally, these methods are benchmarked on both desktop PC and single-board computer hardware to simulate their application in a portable internet-of-things sensor package. The combined results show that the random forest method is the preferred method for mixture identification with its high accuracy (>98%), robustness against overfitting with increasing model complexity, and had less than 10 ms training time and less than 0.1 ms inference time on single-board computer hardware.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49121417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

The Era of Biosensors and Diagnostics 生物传感器和诊断的时代

ECS sensors plus Pub Date : 2023-01-23 DOI: 10.1149/2754-2726/acb3de

N. Arroyo-Currás

引用次数: 0

AI Enabled Ensemble Deep Learning Method for Automated Sensing and Quantification of DNA Damage in Comet Assay 人工智能集成深度学习方法用于彗星检测中DNA损伤的自动传感和量化

ECS sensors plus Pub Date : 2023-01-13 DOI: 10.1149/2754-2726/acb2da

Prateek Mehta, Srikanth Namuduri, L. Barbé, Stephanie Lam, Zohreh Faghihmonzavi, Vivek Kamat, S. Finkbeiner, S. Bhansali

{"title":"AI Enabled Ensemble Deep Learning Method for Automated Sensing and Quantification of DNA Damage in Comet Assay","authors":"Prateek Mehta, Srikanth Namuduri, L. Barbé, Stephanie Lam, Zohreh Faghihmonzavi, Vivek Kamat, S. Finkbeiner, S. Bhansali","doi":"10.1149/2754-2726/acb2da","DOIUrl":"https://doi.org/10.1149/2754-2726/acb2da","url":null,"abstract":"Comet assay is a widely used technique to assess and quantify DNA damage in individual cells. Recently, researchers have applied various deep learning techniques to automate the analysis of comet assay. Image analysis using deep learning allows combining multiple parameters of images and performing computation at a pixel level to provide quantifiable information about the comets. The current deep learning analysis algorithms use a single neural network as a standard method, which relies on many comet images and prone to high variance in predictions. Here, we propose a new ensemble model consisting of a collection of deep learning networks with different configurations and different initial random weights trained on the same dataset to calculate one weighted prediction for DNA damage quantification. To develop this model, we curated a trainable comet assay image dataset consisting of1309 images with 9204 extracted features of cell head and tail length, area, etc With the proposed method we could achieve significantly higher accuracy (R2 = 89.3%, compared to 74% with the standard single neural network as reported in data published by M. D. Zeiler and R Fergus (European conference on computer vision, pp. 818–833 2014). Furthermore, deep regression with the proposed architecture produced much more reliable and accurate results than conventional method.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48258673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Perspective—Supercapacitor-Powered Flexible Wearable Strain Sensors 透视-超级电容器供电的柔性可穿戴应变传感器

ECS sensors plus Pub Date : 2023-01-12 DOI: 10.1149/2754-2726/acb27a

C. Manjunatha, K. Shwetha, Y. Athreya, S. G. Kumar, M. K. S. Kamath

引用次数: 7

Electromechanical Fatigue Properties of Dielectric Elastomer Capacitive Sensors Based on Plantarflexion of the Human Ankle Joint 基于人踝关节跖屈的介质弹性电容传感器的机电疲劳特性

ECS sensors plus Pub Date : 2023-01-11 DOI: 10.1149/2754-2726/acb21e

A. Persons, Carver Middleton, Erin Parker, J. Ball, R. Burch V., David Macias, C. L. Simpson, S. Elder

{"title":"Electromechanical Fatigue Properties of Dielectric Elastomer Capacitive Sensors Based on Plantarflexion of the Human Ankle Joint","authors":"A. Persons, Carver Middleton, Erin Parker, J. Ball, R. Burch V., David Macias, C. L. Simpson, S. Elder","doi":"10.1149/2754-2726/acb21e","DOIUrl":"https://doi.org/10.1149/2754-2726/acb21e","url":null,"abstract":"Wearable stretch sensors have potential applications across many fields including medicine and sports, but the accuracy of the data produced by the sensors over repeated uses is largely unknown due to a paucity of high-cycle fatigue (HCF) studies on both the materials comprising the sensors and the signal produced by the sensors. To overcome these limitations, using human physiologically-based parameters, stretch sensors were subjected to quasi-static testing and HCF with simultaneous capture of the signal. The strain produced by the sensor was then compared to the strain produced by testing instrument, and the results suggest that the output from the stretch sensors is strongly correlated with output from the testing instrument under quasi-static conditions; however, this correlation deteriorates under fatigue conditions. Such deterioration may be the result of several factors, including a mismatch between the material response to fatiguing and the signal response to fatiguing. From a materials perspective, the shape of the stress-life curve for the polymers comprising the sensors conforms to the Rabinowitz-Beardmore model of polymer fatigue. Based on these results, consideration of the material properties of a stretch sensor are necessary to determine how accurate the output from the sensor will be for a given application.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47715777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flexible Graphite-Based Humidity Sensor Using Green Technology 采用绿色技术的柔性石墨基湿度传感器

ECS sensors plus Pub Date : 2022-12-22 DOI: 10.1149/2754-2726/acadee

A. Mansoori, S. Bansal, Munish Vashishath, Shamim Ahmad

引用次数: 2

Perspective—6G and IoT for Intelligent Healthcare: Challenges and Future Research Directions 透视——智能医疗的6G与物联网：挑战与未来研究方向

ECS sensors plus Pub Date : 2022-12-15 DOI: 10.1149/2754-2726/acabd4

Abdul Ahad, Mohammad Tahir

引用次数: 6

Molecular Anchoring with 4-Mercaptobenzoic Acid and 4-Aminothiophenol for Using Active Nanorods in the Detection of Dopamine 4-巯基苯甲酸和4-氨基噻吩分子锚定在活性纳米棒检测多巴胺中的应用

ECS sensors plus Pub Date : 2022-12-15 DOI: 10.1149/2754-2726/acabd3

S. Ramírez, F. Díaz, Carlos P. Silva, J. Pavez, J. F. Silva

{"title":"Molecular Anchoring with 4-Mercaptobenzoic Acid and 4-Aminothiophenol for Using Active Nanorods in the Detection of Dopamine","authors":"S. Ramírez, F. Díaz, Carlos P. Silva, J. Pavez, J. F. Silva","doi":"10.1149/2754-2726/acabd3","DOIUrl":"https://doi.org/10.1149/2754-2726/acabd3","url":null,"abstract":"The incorporation and effective anchorage of gold nanorods in a gold (111) substrate is applied to electrochemical systems to detect dopamine. Gold nanorods (AuNRs) were synthesized in dispersion. They were then incorporated in a metal substrate mediated by self-assembled monolayers (SAMs) which act as structural anchors. Two molecular anchors, 4-mercaptobenzoic acid (4-MBA) and 4 aminothiophenol (4-ATP) are compared by means of the charge density (Q) in desorption of the SAMs, where 4-MBA presented a greater coverage on the metal surface. Both SAMs allowed the effective confinement and communication of the nanostructure to a greater or lesser extent. Characterizations were made to confirm the constructed system. First, the nanostructures synthesized in dispersion were characterized by UV-visible spectroscopy, Transmission electron microscopy and atomic force microscopy. Second, an electrochemical characterization of the working electrodes include impedance was made. The results focus on the impact of the molecular anchor on the activity of the electrochemical sensor, it was determined. Reducing the charge transfer resistance (by at least 90% with appropriate SAMs) of molecularly anchored gold nanorods increases the sensitivity of the electrochemical sensor (at least 20%), the detection of dopamine was studied by square wave voltammetry through a calibration curve, where better sensitivity and detection limit was obtained with the Au/4-MBA/AuNRs system compared to Au/4-ATP/AuNRs.","PeriodicalId":72870,"journal":{"name":"ECS sensors plus","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42776634","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Review—Micro-Fuel Cell Principal Biosensors for Monitoring Transdermal Volatile Organic Compounds in Humans 微燃料电池主要生物传感器监测人体经皮挥发性有机化合物

ECS sensors plus Pub Date : 2022-12-07 DOI: 10.1149/2754-2726/aca95b

T. Benhaddouch, Sofia K. Pinzon, D. Landi, John Marcial, Prateek Mehta, Karen Romero, T. Rockward, S. Bhansali, D. Dong

引用次数: 3