关键词: 2D materials MXene breath diagnosis flexible and wearable health care sensor device

Mesh : Artificial Intelligence Biomarkers Breath Tests Humans Smart Materials Wearable Electronic Devices

来  源:   DOI:10.1002/adhm.202100970   PDF(Sci-hub)

Abstract:
A fully integrated, flexible, and functional sensing device for exhaled breath analysis drastically transforms conventional medical diagnosis to non-invasive, low-cost, real-time, and personalized health care. 2D materials based on MXenes offer multiple advantages for accurately detecting various breath biomarkers compared to conventional semiconducting oxides. High surface sensitivity, large surface-to-weight ratio, room temperature detection, and easy-to-assemble structures are vital parameters for such sensing devices in which MXenes have demonstrated all these properties both experimentally and theoretically. So far, MXenes-based flexible sensor is successfully fabricated at a lab-scale and is predicted to be translated into clinical practice within the next few years. This review presents a potential application of MXenes as emerging materials for flexible and wearable sensor devices. The biomarkers from exhaled breath are described first, with emphasis on metabolic processes and diseases indicated by abnormal biomarkers. Then, biomarkers sensing performances provided by MXenes families and the enhancement strategies are discussed. The method of fabrications toward MXenes integration into various flexible substrates is summarized. Finally, the fundamental challenges and prospects, including portable integration with Internet-of-Thing (IoT) and Artificial Intelligence (AI), are addressed to realize marketization.
摘要:
一个完全集成的,灵活,用于呼出气分析的功能传感装置将传统医学诊断转变为非侵入性,低成本,实时,个性化医疗保健。与常规半导体氧化物相比,基于MXenes的2D材料提供用于准确检测各种呼吸生物标志物的多个优点。高表面灵敏度,大的表面重量比,室温检测,和易于组装的结构是这种传感设备的重要参数,其中MXenes已经在实验和理论上证明了所有这些特性。到目前为止,基于MXenes的柔性传感器已在实验室规模上成功制造,并有望在未来几年内转化为临床实践。这篇综述介绍了MXenes作为柔性和可穿戴传感器设备的新兴材料的潜在应用。首先描述呼出气的生物标志物,重点是代谢过程和异常生物标志物指示的疾病。然后,讨论了MXenes家族提供的生物标志物传感性能和增强策略。总结了将MXenes集成到各种柔性基板中的制造方法。最后,基本挑战和前景,包括与物联网(IoT)和人工智能(AI)的便携式集成,旨在实现市场化。
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