4.8 Article

Green synthesis of carbon quantum dots from purslane leaves for the detection of formaldehyde using quartz crystal microbalance

Journal

CARBON
Volume 179, Issue -, Pages 159-171

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.carbon.2021.03.047

Keywords

Carbon quantum dots; Quartz crystal microbalance (QCM); Sensor; Formaldehyde vapor

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Carbon quantum dots (CQDs) were synthesized using a green and economical hydrothermal method, and their optical and structural properties were studied. The sensing properties of CQDs, particularly towards volatile formaldehyde, were investigated, showing high sensitivity and potential for formaldehyde vapor detection.
Carbon quantum dots (CQDs) were synthesized by using a facile one-step hydrothermal treatment of purslane leaves in a green and economical approach. The optical and structural properties of the CQDs have been studied by using many analytical techniques. The research interest in studying the sensing properties of CQDs is based on their good properties in addition to the combination of the developed graphitic carbon and the active functional groups that present in CQDs, which collectively can lead to the detection of some analytes with good sensitivity. The results of the CQDs-based sensor, using the quartz crystal microbalance (QCM) technique, show a good detection sensitivity toward volatile hazardous formaldehyde. The QCM sensor shows the high impact of the oxygen functionalities of CQDs as sensing antennae on the good sensitivity of volatile formaldehyde via enhanced chemisorption as compared to alcohols. Based on calibration graphs of frequency shift against the vapor concentration, the linear increase of CQDs sensor responses with the increased injection of chemical vapor concentration with a high sensitivity allows CQDs to be used for the detection of formaldehyde vapors. The fabricated QCM sensor exhibits a good reproducibility and reversibility. The kinetics of formaldehyde sensing compared to other analytes vapors were discussed. (C) 2021 Elsevier Ltd. All rights reserved.

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