Silver Nanowire-Tungsten Oxide Hybrids: Rapid-Kinetic Amine Sensor for Food Freshness Monitoring

IF 8 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Junxuan Liang, Weiliang Tian, Fengzhen Gao, Zhihui Zhao, Bin Hui, Ding Zhang, Kewei Zhang
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Abstract

Pork, shrimp, and milk are common staples but are prone to spoilage, leading to food safety issues. Traditional methods for spoilage detection are often inefficient and impractical for rapid on-site use. Herein, silver nanowires interwoven with hierarchical tungsten oxide (Ag/WO3) is explored as high charge-transfer material for rapid-kinetic gas sensors. The as-fabricated Ag/WO3 sensor demonstrates 3-fold increase in sensitivity and 3-fold reduction in response time to triethylamine (C6H15N) as compared with pristine WO3 sensors. Owing to exceptional sensitivity, repeatability, and long-term stability, the Ag/WO3 sensor enables effective detection of spoilage in shrimp, pork and milk by monitoring amine release in real applications. Furthermore, an artificial neural network (ANN) model is established for predicting food spoilage with 98% accuracy. The presented sensor not only shows great potential for efficient and sensitive food safety monitoring but also offers an easy solution to rationally design advanced gas sensors by utilizing high charge-transfer hybrids.

Abstract Image

银纳米线-氧化钨混合物:用于食品新鲜度监测的快速动力学胺传感器
猪肉、虾和牛奶是常见的主食,但容易变质,导致食品安全问题。传统的腐败检测方法往往效率低下,不适合现场快速使用。本文研究了用分层氧化钨(Ag/WO3)交织的银纳米线作为快速动力学气体传感器的高电荷转移材料。与原始WO3传感器相比,制备的Ag/WO3传感器的灵敏度提高了3倍,对三乙胺(C6H15N)的响应时间降低了3倍。Ag/WO3传感器具有卓越的灵敏度、可重复性和长期稳定性,通过监测实际应用中的胺释放,可以有效地检测虾、猪肉和牛奶中的腐败情况。在此基础上,建立了预测食品腐败的人工神经网络模型,预测准确率达98%。该传感器不仅在高效灵敏的食品安全监测方面具有很大的潜力,而且为利用高电荷转移混合动力合理设计先进的气体传感器提供了一种简单的解决方案。
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来源期刊
Sensors and Actuators B: Chemical
Sensors and Actuators B: Chemical 工程技术-电化学
CiteScore
14.60
自引率
11.90%
发文量
1776
审稿时长
3.2 months
期刊介绍: Sensors & Actuators, B: Chemical is an international journal focused on the research and development of chemical transducers. It covers chemical sensors and biosensors, chemical actuators, and analytical microsystems. The journal is interdisciplinary, aiming to publish original works showcasing substantial advancements beyond the current state of the art in these fields, with practical applicability to solving meaningful analytical problems. Review articles are accepted by invitation from an Editor of the journal.
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