仿生双层结构协同高分辨多元分析传感器研究

Benefit from the function integration of cilia and glomeruli, animals can discriminate various odours with their olfactory system even in hostile environments. Inspired by this integration strategy, a sensor combining the universal recognition process of graphene oxide (GO) and the optically selective amplification of photonic crystals (PCs) is fabricated. The GO aerogel effectively captures the analytes and generates abundant sensing signals, function like the olfactory cilia; and the periodic structure of PCs enables selective enhancement of the fluorescence to realize signal processing, functioning as the olfactory glomeruli. This bilayer structure not only retains the non-specific interactions of GO to different analytes, but also retains the specific fluorescence amplification of PCs to various fluorophores. Multiple biogenic amines, drugs, glycemia, or proteins are effectively discriminated in sweat, urine or serum. The integrated sensor strategy of recognition unit and signal manipulation unit combination will promote enormous pursuits in rapid clinical diagnosis or intractable pathology analysis.

本项目拟从仿生科学原理出发，针对复杂体系多元底物的快速分析，模拟鼻黏膜“表面信息收集-皮下信号分类处理”的结构与工作机制，通过构建微/纳米多孔结构与纳米光学结构的双层结构，微/纳米多孔结构（氧化石墨烯或修饰氧化石墨烯）吸附、富集检测分子，光子晶体结构对响应的荧光信号进行选择性增强，实现利用简单、易得的荧光染料对复杂环境内多元底物的辨别分析。通过双层结构设计与分工-集成的原理创新，结合多材料界面融合器件制备的工艺创新，发展“主信号提取-噪音去除”高信噪比分析方法的创新，推动重要生命表达物的快速多元辨别分析重大示范应用的创新。解决现有检测分析技术对复杂多底物样品检测分析效率低下的问题，为高灵敏、高分辨率多元底物的快速辨别分析提供新的思路和方法，推动现代复杂样品快速、高通量分析技术的进步与应用推广。

针对环境与人体的复杂组成体系，本项目从“仿生多元分析”的基本原理出发，1）利用光子晶体、石墨烯等微纳结构材料进行信号增强，提高传感灵敏度；2）发展深度学习等大数据处理算法，实现人工智能辅助的复杂分析；3）集成柔性光学、电学传感器芯片，通过传感信号的特征挖掘，提高辨别分析的分辨率。项目执行期间以通讯作者发表论文13篇，包括：7篇Anal. Chem., 1篇Angew. Chem. Int. Ed., 1篇ACS Nano，申请人发展可穿戴传感器进行人体生理特征的多元监测与分析，实现以短跑为代表的竞技体育训练与士兵体能训练中的应用，特别助力东京奥运会我国100米短跑成绩突破。