State Key Laboratory of Bio-Fibers and Eco-Textiles, College of Materials Science and Engineering, Qingdao University, Qingdao 266071, P. R. China.
Key Laboratory of Chemical Engineering in South Xinjiang, College of Chemistry and Chemical Engineering, Tarim University, Alar 843300, P. R. China.
ACS Sens. 2024 Aug 23;9(8):4196-4206. doi: 10.1021/acssensors.4c01192. Epub 2024 Aug 3.
Reliable and real-time monitoring of seafood decay is attracting growing interest for food safety and human health, while it is still a great challenge to accurately identify the released triethylamine (TEA) from the complex volatilome. Herein, defect-engineered WO architectures are presented to design advanced TEA sensors for seafood quality assessment. Benefiting from abundant oxygen vacancies, the obtained WO sensor exhibits remarkable TEA-sensing performance in terms of higher response (1.9 times), faster response time (2.1 times), lower detection limit (3.2 times), and higher TEA/NH selectivity (2.8 times) compared with the air-annealed WO sensor. Furthermore, the definite WO sensor demonstrates long-term stability and anti-interference in complex gases, enabling the accurate recognition of TEA during halibut decay (0-48 h). Coupled with the random forest algorithm with 70 estimators, the WO sensor enables accurate prediction of halibut storage with an accuracy of 95%. This work not only provides deep insights into improving gas-sensing performance by defect engineering but also offers a rational solution for reliably assessing seafood quality.
可靠且实时地监测海产品腐败情况，这对于食品安全和人类健康而言越来越受到关注，然而，要从复杂的挥发物中准确识别释放的三乙胺（TEA）仍然是一个巨大的挑战。在此，设计了具有缺陷的 WO 结构，以用于开发先进的 TEA 传感器，从而评估海产品的质量。得益于丰富的氧空位，所获得的 WO 传感器在 TEA 传感性能方面表现出显著的优势，包括更高的响应（提高 1.9 倍）、更快的响应时间（提高 2.1 倍）、更低的检测限（降低 3.2 倍）以及更高的 TEA/NH3 选择性（提高 2.8 倍），优于经空气退火的 WO 传感器。此外，确定的 WO 传感器在复杂气体中表现出长期稳定性和抗干扰性，能够在大比目鱼腐败期间（0-48 h）准确识别 TEA。WO 传感器与具有 70 个估计器的随机森林算法相结合，能够实现大比目鱼储存的准确预测，准确率达到 95%。这项工作不仅深入了解了通过缺陷工程来提高气体传感性能，而且还为可靠地评估海产品质量提供了合理的解决方案。
