微型加热器
电子鼻
量子点
微电子机械系统
纳米技术
材料科学
可扩展性
电阻式触摸屏
可穿戴计算机
传感器阵列
制作
计算机科学
墨水池
压力传感器
人工神经网络
灵敏度(控制系统)
可穿戴技术
电子工程
数码产品
气味
光电子学
光伏系统
领域(数学)
微流控
量子
嵌入式系统
智能传感器
量子传感器
电子元件
电气工程
3D打印
桥接(联网)
作者
Zhu’an Wan,Weiqi Zhang,Suman Ma,Zhilong Song,Chen Wang,Yucheng Ding,Chak Lam Jonathan Chan,Xue Feng,Zixi Wan,Wenhao Ye,Zhiyong Fan
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2025-11-05
卷期号:10 (11): 8447-8457
被引量:2
标识
DOI:10.1021/acssensors.5c01908
摘要
The development of next-generation wearable electronic nose (e-nose) systems for real-time environmental monitoring requires miniaturized gas sensor arrays with high sensitivity and low-power operation. Current limitations persist in the incompatibility between conventional sensing material deposition methods and MEMS microheater architectures. Here, we present an intelligent wristwatch-formatted e-nose system, integrating a printable quantum dot (QD) sensor array fabricated using an optimized colloidal quantum dot (CQD) ink formulation and a precision inkjet printing strategy. We engineered metal cation-surrounded quantum dots (MCSQDs) via liquid-phase ligand exchange with transition metal chlorides (FeCl3, CoCl2, NiCl2, CuCl2), achieving tailored surface functionalities and enhanced gas discrimination capabilities. The engineered MCSQD inks demonstrated exceptional colloidal stability and seamless MEMS microheater integration, enabling gas sensors with parts-per-billion-level detection limits (4 ppb ethanol). A 16-unit sensor array was embedded into a wearable platform incorporating cloud-based neural network processing. System validation achieved 100% classification accuracy in indoor odor recognition tests using a fully connected neural network (FCNN), while field tests at a transportation hub demonstrated reliable monitoring of Total Volatile Organic Compounds (TVOC), NO2, SO2, and CO with <15% deviation from the reference sensors. This work establishes a viable manufacturing framework bridging quantum-confined material engineering to IoT-enabled artificial olfaction, paving the way for scalable production of QD gas sensor array-based e-noses.
科研通智能强力驱动
Strongly Powered by AbleSci AI