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Pyrene based chemosensor for carbon dioxide gas – Meticulous investigations and digital image based RGB analysis
Sensors and Actuators Reports Pub Date : 2020-04-23 , DOI: 10.1016/j.snr.2020.100007
Annasamy Gowri , Themmila Khamrang , Marappan Velusamy , Murugavel Kathiresan , Madhu Deepan Kumar , Madhavan Jaccob , Arunkumar Kathiravan

A new pyrene Schiff base (KB-4) was synthesized and demonstrated as simple colorimetric chemosensor for carbon dioxide (CO2) gas activated by fluoride anion. The chemical structure of KB-4 was validated through pivotal characterization methods. A combined quantum chemical calculations and spectroscopic techniques were adopted to understand the photophysical properties of KB-4. The sensitivity of KB-4 chemosensor towards various anions is investigated and showed excellent selectivity towards F anion with a distinct color change. The mechanism of F anion sensing is due to the complete deprotonation of –NH proton in KB-4 as revealed by 1H NMR titration studies as well as DFT calculations. Subsequently, the in-situ deprotonated KB-4 is employed for CO2 gas sensing. Interestingly, deprotonated KB-4 is responded instantaneously to CO2 gas by exhibiting significant colorimetric and fluorimetric changes with a detection limit of 0.4 ml. Further, digital image based RGB analysis using smartphone is introduced for detection of CO2 gas. The digital images of CO2 gas induced fluorimetric changes are captured using smartphone and the RGB analysis of the images are processed using MATLAB. The intensity variation in the color components as an indicative measure for detection of CO2 gas is demonstrated.



中文翻译:

基于的二氧化碳气体化学传感器-细致的研究和基于数字图像的RGB分析

合成了一种新的pyr席夫碱(KB-4),并被证明是一种简单的比色化学传感器,用于氟化物阴离子活化的二氧化碳(CO 2)气体。通过关键表征方法验证了KB-4的化学结构。通过结合量子化学计算和光谱技术来了解KB-4的光物理性质。对各种阴离子KB-4化学传感器的灵敏度进行了研究,并显示向●优异的选择性-带有明显的颜色变化的阴离子。F的机制-阴离子的感测是由于-NH质子的在KB-4完整的去质子化通过所揭示的11 H NMR滴定研究以及DFT计算。随后,将原位去质子化的KB-4用于CO 2气体感测。有趣的是,去质子化的KB-4通过显着的比色和荧光变化(检测限为0.4 ml)对CO 2气体即时响应。此外,引入了使用智能手机的基于数字图像的RGB分析以检测CO 2气体。使用智能手机捕获由CO 2气体引起的荧光变化的数字图像,并使用MATLAB处理图像的RGB分析。作为检测CO 2气体的指标,对颜色成分的强度变化进行了说明。

更新日期:2020-04-23
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