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受生物启发的光致发光“蜘蛛网”作为用于人机交互和智能识别的超快速、超灵敏气流-声学双模式传感器

Bioinspired Photoluminescent "Spider Web" as Ultrafast and Ultrasensitive Airflow-Acoustic Bimodal Sensor for Human-Computer Interaction and Intelligent Recognition.

作者信息

Zhu Kai, Yan Bing

机构信息

School of Chemical Science and Engineering, Tongji University, Siping Road 1239, Shanghai 200092, China.

出版信息

ACS Cent Sci. 2024 Sep 26;10(10):1894-1909. doi: 10.1021/acscentsci.4c01182. eCollection 2024 Oct 23.

Abstract

Nature provides massive biomimetic design inspiration for constructing structural materials with desired performances. Spider webs can perceive vibrations generated by airflow and acoustic waves from prey and transfer the corresponding information to spiders. Herein, by mimicking the perception capability and structure of a spider web, an ultrafast and ultrasensitive airflow-acoustic bimodal sensor (HOF-TCPB@SF) is developed based on the postfunctionalization of hydrogen-bonded organic framework (HOF-TCPB) on silk film (SF) through hydrogen bonds. The "spider web-like" HOF-TCPB@SF possesses light weight and high elasticity, endowing this airflow sensor with superior properties including an ultralow detection limit (DL, 0.0076 m s), and excellent repeatability (480 cycles). As an acoustic sensor, HOF-TCPB@SF exhibits ultrahigh sensitivity (105140.77 cps Pa cm) and ultralow DL (0.2980 dB), with the greatest response frequency of 375 Hz and the ability to identify multiple sounds. Moreover, both airflow and acoustic sensing processes show an ultrafast response speed (40 ms) and multiangle recognition response (0-180°). The perception mechanisms of airflow and acoustic stimuli are analyzed through finite element simulation. This bimodal sensor also achieves real-time airflow monitoring, speech recognition, and airflow-acoustic interoperability based on human-computer interaction, which holds great promise for applications in health care, tunnel engineering, weather forecasting, and intelligent textiles.

摘要

大自然为构建具有理想性能的结构材料提供了大量仿生设计灵感。蜘蛛网能够感知气流和来自猎物的声波产生的振动,并将相应信息传递给蜘蛛。在此,通过模仿蜘蛛网的感知能力和结构,基于氢键有机框架(HOF-TCPB)通过氢键在丝膜(SF)上的后功能化,开发了一种超快且超灵敏的气流-声学双模式传感器(HOF-TCPB@SF)。“蜘蛛网状”的HOF-TCPB@SF具有轻质和高弹性,赋予该气流传感器卓越的性能,包括超低检测限(DL,0.0076 m s)和出色的重复性(480次循环)。作为声学传感器,HOF-TCPB@SF表现出超高灵敏度(105140.77 cps Pa cm)和超低检测限(0.2980 dB),最大响应频率为375 Hz,并且能够识别多种声音。此外,气流和声学传感过程均显示出超快响应速度(40 ms)和多角度识别响应(0 - 180°)。通过有限元模拟分析了气流和声学刺激的感知机制。这种双模式传感器还基于人机交互实现了实时气流监测、语音识别以及气流-声学互操作性,在医疗保健、隧道工程、天气预报和智能纺织品等应用方面具有巨大潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a7ae/11503498/2f092e432022/oc4c01182_0007.jpg

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