Molecularly imprinted graphene based biosensor as effective tool for electrochemical sensing of uric acid

Gowri Soman , Vandana M , Gurumurthy Hegde
{"title":"Molecularly imprinted graphene based biosensor as effective tool for electrochemical sensing of uric acid","authors":"Gowri Soman ,&nbsp;Vandana M ,&nbsp;Gurumurthy Hegde","doi":"10.1016/j.sintl.2023.100243","DOIUrl":null,"url":null,"abstract":"<div><p>Graphene oxide based molecularly imprinted polymer was designed by incorporating vinyltrimethoxysilane into the layers of graphene oxide, which was copolymerized with functional monomers such as Itaconic acid (IA) and methyl methacrylate (MMA) was developed via bulk imprinting technique. The prepared polymer was studied for selective sensing the uric acid (UA) in blood serum. The electrode was constructed by modifying bare glassy carbon electrodes with the prepared molecularly imprinted polymer (MIP) via drop cast method. Electrochemical measurements were made by Cyclic voltammetric (CV) and Differential Pulse Voltammetric (DPV) response of the sensor. The physical and chemical properties of the resultant material will be characterized by FTIR spectroscopy, XRD and FESEM. The constructed sensor showed a regression coefficient (R<sup>2</sup>) of 0.9302 with limit of detection (LOD) of about 0.565 ​μM. The developed sensor is reusable without any compromise in its selectivity. All the results confirm that the constructed biosensor requires no pre-treatment of samples and is suitable for real sample analysis.</p></div>","PeriodicalId":21733,"journal":{"name":"Sensors International","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sensors International","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666351123000177","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

Graphene oxide based molecularly imprinted polymer was designed by incorporating vinyltrimethoxysilane into the layers of graphene oxide, which was copolymerized with functional monomers such as Itaconic acid (IA) and methyl methacrylate (MMA) was developed via bulk imprinting technique. The prepared polymer was studied for selective sensing the uric acid (UA) in blood serum. The electrode was constructed by modifying bare glassy carbon electrodes with the prepared molecularly imprinted polymer (MIP) via drop cast method. Electrochemical measurements were made by Cyclic voltammetric (CV) and Differential Pulse Voltammetric (DPV) response of the sensor. The physical and chemical properties of the resultant material will be characterized by FTIR spectroscopy, XRD and FESEM. The constructed sensor showed a regression coefficient (R2) of 0.9302 with limit of detection (LOD) of about 0.565 ​μM. The developed sensor is reusable without any compromise in its selectivity. All the results confirm that the constructed biosensor requires no pre-treatment of samples and is suitable for real sample analysis.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
分子印迹石墨烯基生物传感器作为尿酸电化学传感的有效工具
将乙烯基三甲氧基硅烷引入氧化石墨烯层中,与衣康酸(IA)、甲基丙烯酸甲酯(MMA)等功能单体共聚,设计了氧化石墨烯分子印迹聚合物。研究了所制备的聚合物对血清尿酸(UA)的选择性传感。用制备的分子印迹聚合物(MIP)通过滴注法对裸玻碳电极进行改性,构建了电极。采用循环伏安法(CV)和微分脉冲伏安法(DPV)对传感器进行了电化学测量。所得材料的物理和化学性质将通过FTIR光谱、XRD和FESEM进行表征。所构建的传感器显示出0.9302的回归系数(R2),检测限(LOD)约为0.565​μM。所开发的传感器是可重复使用的,在选择性方面没有任何妥协。所有结果证实,所构建的生物传感器不需要对样品进行预处理,并且适合于真实样品分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
17.40
自引率
0.00%
发文量
0
期刊最新文献
A method to detect enzymatic reactions with field effect transistor Blue luminescent carbon quantum dots derived from diverse banana peels for selective sensing of Fe(III) ions The application of ultrasonic measurement and machine learning technique to identify flow regime in a bubble column reactor A capacitive sensor-based approach for type-2 diabetes detection via bio-impedance analysis of erythrocytes 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
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1