亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

MXene-based nano(bio)sensors for the detection of biomarkers: A move towards intelligent sensors

MXenes公司 纳米技术 材料科学 计算机科学 可扩展性 耐久性 数据库 复合材料
作者
Danial Khorsandi,Jiawei Yang,Zeynep Ülker,Kenz Bayraktaroğlu,Atefeh Zarepour,Siavash Iravani,Arezoo Khosravi
出处
期刊:Microchemical Journal [Elsevier]
卷期号:197: 109874-109874 被引量:29
标识
DOI:10.1016/j.microc.2023.109874
摘要

MXene-based nano(bio)sensors have emerged as promising tools for detecting different biomarkers. These sensors utilize MXene materials, a class of two-dimensional transition metal carbides, nitrides, and carbonitrides, to enable highly sensitive and selective detection. One of the key advantages of MXene-based materials is their high surface area, allowing for efficient immobilization of biomolecules. They also exhibit excellent electrical conductivity, enabling rapid and sensitive detection of biomarkers. The combination of high surface area and conductivity makes MXene-based sensors ideal for detecting biomarkers at low concentrations. Furthermore, MXene-based materials possess unique mechanical properties, ensuring the durability of the sensors. This durability enables repeated use without compromising the sensor performance, making MXene-based sensors suitable for continuous monitoring applications. Despite their advantages, MXene-based nano(bio)sensors face certain challenges for practical biomedical and clinical applications. One challenge lies in the synthesis of MXene materials, which can be complex and time-consuming. Developing scalable synthesis methods is crucial to enable large-scale production and widespread use of MXene-based sensors. In addition, ensuring the stability of MXene layers under various environmental conditions remains a challenge for their practical application. Another limitation is the specificity of MXene-based sensors towards targeted biomarkers. Interfering substances or cross-reactivity with similar biomolecules can lead to false-positive or false-negative results. Enhancing the selectivity of MXene-based sensors through optimization and functionalization is essential to improve their reliability and accuracy. The integration of these sensors with emerging technologies, such as artificial intelligence (AI) and internet of things, opens up new possibilities in biomarker detection. The combination of MXene sensors with AI algorithms can enable real-time monitoring, remote data analysis, and personalized healthcare solutions. Herein, the significant challenges and future prospects of MXene-based nano(bio)sensors for the detection of biomarkers are deliberated. The key obstacles have been highlighted, such as ensuring the stability and biocompatibility of MXene-based sensors, as well as addressing scalability issues. The promising future prospects of these sensors have also been explored, including their potential for high sensitivity, selectivity, and rapid response.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
建议保存本图,每天支付宝扫一扫(相册选取)领红包
实时播报
HYQ完成签到 ,获得积分10
3秒前
dominic12361完成签到 ,获得积分0
7秒前
9秒前
10秒前
16秒前
无情的水香完成签到 ,获得积分10
18秒前
zw发布了新的文献求助10
34秒前
kokishi完成签到,获得积分10
49秒前
49秒前
53秒前
1分钟前
vitamin完成签到 ,获得积分10
1分钟前
1分钟前
浮游应助科研通管家采纳,获得10
1分钟前
浮游应助科研通管家采纳,获得10
1分钟前
1分钟前
1分钟前
2分钟前
2分钟前
2分钟前
2分钟前
2分钟前
汉堡包应助有魅力的半蕾采纳,获得10
3分钟前
3分钟前
miooo发布了新的文献求助10
3分钟前
3分钟前
深情安青应助剧院的饭桶采纳,获得30
3分钟前
Demi_Ming完成签到,获得积分10
3分钟前
万邦德完成签到,获得积分10
3分钟前
浮游应助科研通管家采纳,获得10
3分钟前
浮游应助科研通管家采纳,获得10
3分钟前
浮游应助科研通管家采纳,获得10
3分钟前
科研通AI2S应助科研通管家采纳,获得10
3分钟前
浮游应助科研通管家采纳,获得10
3分钟前
3分钟前
3分钟前
3分钟前
3分钟前
敏敏9813完成签到,获得积分10
3分钟前
4分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
List of 1,091 Public Pension Profiles by Region 1041
Mentoring for Wellbeing in Schools 1000
Binary Alloy Phase Diagrams, 2nd Edition 600
Atlas of Liver Pathology: A Pattern-Based Approach 500
A Technologist’s Guide to Performing Sleep Studies 500
EEG in Childhood Epilepsy: Initial Presentation & Long-Term Follow-Up 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5493999
求助须知:如何正确求助?哪些是违规求助? 4591889
关于积分的说明 14434935
捐赠科研通 4524492
什么是DOI,文献DOI怎么找? 2478803
邀请新用户注册赠送积分活动 1463758
关于科研通互助平台的介绍 1436579