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通过电泳沉积制备的发Eu@SOF 膜作为荧光传感和人工神经网络模型的超灵敏平台,用于定量监测苯乙烯气体。

A luminescent Eu@SOF film fabricated by electrophoretic deposition as ultrasensitive platform for styrene gas quantitative monitoring through fluorescence sensing and ANNs model.

机构信息

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

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

出版信息

J Hazard Mater. 2023 Jan 5;441:129865. doi: 10.1016/j.jhazmat.2022.129865. Epub 2022 Aug 27.

Abstract

Styrene is a harmful gas widely existing in the air, which can damage human organs. Therefore, it is very crucial to develop a sensitive, portable and simple sensor for monitoring styrene. Herein, we design and fabricate a luminescent Eu@TMA-ME/FTO film (F) through EPD method. F emits bright red light of Eu(III) ions and shows superior fluorescence response to styrene gas as a sensor, which enable real-time and quantitative monitoring for styrene gas. More importantly, F exhibits a linear response to styrene gas in a wide concentration range of 10 to 10 M and a low DL with 0.20 ppm. The efficient PET process to styrene induced by ME and the competitive absorption between styrene and F are responsible for the sensing mechanism. Besides, the detection of styrene solution is also investigated in deionized water, tap water and river water. For the further application, an intelligent ANNs model has been constructed to process the fluorescence sensing results, which can convert fluorescence sensing images to the concentration of styrene gas. The data demonstrates that ANNs model can accurately monitor the concentration of styrene gas via deep ML without tedious data processing.

摘要

苯乙烯是一种空气中广泛存在的有害气体,会损害人体器官。因此,开发一种用于监测苯乙烯的灵敏、便携和简单的传感器非常关键。在这里,我们通过 EPD 法设计并制备了一种发明亮红色光的 Eu@TMA-ME/FTO 薄膜(F)。F 作为传感器发出 Eu(III)离子的明亮红光,并对苯乙烯气体表现出优异的荧光响应,从而能够实时定量监测苯乙烯气体。更重要的是,F 在 10 到 10 M 的宽浓度范围内对苯乙烯气体表现出线性响应,检出限低至 0.20 ppm。ME 引发的对苯乙烯的高效 PET 过程和苯乙烯与 F 之间的竞争吸收是这种传感机制的原因。此外,还研究了 F 在去离子水、自来水和河水中对苯乙烯溶液的检测。为了进一步应用,构建了一个智能人工神经网络 (ANNs) 模型来处理荧光传感结果,该模型可以将荧光传感图像转换为苯乙烯气体的浓度。数据表明,ANNs 模型可以通过深度学习 (ML) 而无需繁琐的数据处理,准确地监测苯乙烯气体的浓度。

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