Graphene and metal organic frameworks (MOFs) hybridization for tunable chemoresistive sensors for detection of volatile organic compounds (VOCs) biomarkers

• Published in: Carbon (New York) Vol. 159; pp. 333 - 344
• Main Authors: Tung, Tran Thanh, Tran, Manh Trung, Feller, Jean-François, Castro, Mickael, Van Ngo, Truc, Hassan, Kamrul, Nine, Md J., Losic, Dusan
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 15.04.2020; Elsevier BV
• Subjects: Acetone; Acetonitrile; Benzene; Biomarkers; Biomedical materials; Chemical sensors; Chloroform; Copper; Ethanol; Gas sensors; Graphene; Graphene composites; Graphene-MOFs; Metal-organic frameworks; Methanol; Nanocomposites; Performance enhancement; Selectivity; Sensitivity enhancement; Sensors; Synergistic effect; VOCs; Volatile organic compounds; Zinc salts; Zirconium; Graphene composites; Chemical sensors; Graphene-MOFs; Graphene; Gas sensors
• ISSN: 0008-6223; 1873-3891
• DOI: 10.1016/j.carbon.2019.12.010

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. [Display omitted]