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

Abstract

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 crossreactivity 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.