Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/124711
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Type: Journal article
Title: Graphene and metal organic frameworks (MOFs) hybridization for tunable chemoresistive sensors for detection of volatile organic compounds (VOCs) biomarkers
Author: Tung, T.
Tran, M.
Feller, J.
Castro, M.
Van Ngo, T.
Hassan, K.
Nine, M.
Losic, D.
Citation: Carbon, 2020; 159:333-344
Publisher: Elsevier
Issue Date: 2020
ISSN: 0008-6223
1873-3891
Statement of
Responsibility: 
Tran Thanh Tung, Manh Trung Tran, Jean-François Feller, Mickael Castro, Truc Van Ngo, Kamrul Hassan, Md J.Nine, Dusan Losic
Abstract: The paper presents the tuning of sensitivity and selectivity performance of volatile organic compounds (VOCs) chemoresistive sensors for biomarker detection using the hybridization of pristine graphene (pG) and metal organic frameworks (MOFs). The synergistic effect of this nanocomposite material was discovered showing improved sensing performances where graphene acts as a highly conductive sensing element, and MOFs, with a high surface area and adsorption capacity provide an enhanced sensitivity and selectivity for specific VOCs. By combining and selecting different MOFs, we proposed that is possible to tailor sensing performances of chemoresistive sensors for VOC biomarkers detection. To prove that graphene hybrid nanocomposite with selected MOFs including copper–benzene-1,3,5-tricarboxylate (pG-Cu BTC), zirconium 1,4-dicarboxybenzene (pG-UiO 66) and 2-methylimidazole zinc salt (pG-ZIF 8), were investigated to enhance the sensing performance and capability of distinguishing different VOC biomarkers (e.g., methanol, ethanol, chloroform, acetone, acetonitrile and THF). Results showed that the pG-Cu BTC sensor has the highest sensitivity and selectivity towards chloroform and methanol VOCs at 2.82–22.6 ppm level. The proposed concept presents a valuable contribution for the development of low-cost and high-performing VOC biomarker sensors for monitoring human health from metabolic human breath and further implementation for non-invasive biomedical diagnostics for personalized telehealth monitoring.
Keywords: Graphene; graphene-MOFs; graphene composites; chemical sensors; gas sensors
Rights: ©2019 Published by Elsevier Ltd.
RMID: 1000011771
DOI: 10.1016/j.carbon.2019.12.010
Grant ID: http://purl.org/au-research/grants/arc/IH150100003
Appears in Collections:Chemical Engineering publications

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