New Publication: Multi-layer graphene as a selective detector for future lung cancer biosensing platforms

Congratulations to XM² PGR Ben Hogan (4th year) who has co-authored a recently published paper on ‘Multi-layer graphene as a selective detector for future lung cancer biosensing platforms’ in the journal Nanoscale.

Lung cancer is one of the most common and aggressive cancers, with mortality rates of about 1.4 million per year, worldwide. The lack of clinical symptoms of early-stage lung cancer is a critical global challenge which leads to late-stage diagnosis and hence inability to cure patients. One potential solution is to monitor the makeup of people’s breath, in order to detect changes occurring due to the presence of cancer in the lungs. This paper shows that patterned multilayer graphene is a suitable electrode for the specific and selective analysis of breath samples in future devices.

Ben’s previous publications include Probing Raman Scattering for Particle Tracking (co-author) and From colloidal CdSe quantum dots to microscale optically anisotropic supercrystals through bottom-up self-assembly (co-author). Follow on Twitter for his latest research- @BenHoganSci.


Highly selective, fast detection of specific lung-cancer biomarkers (CMs) in exhaled human breath is vital to the development of enhanced sensing devices. Today, e-nose is a promising approach for the diagnosis of lung cancer. Nevertheless, considerable challenges to early-stage disease diagnostics still remain: e.g. decrease in sensor sensitivities in the presence of water vapor, sensor drift leading to the inability to calibrate exactly, relatively short sensor lifetimes, and difficulty discriminating between multiple diseases.

However, there is a wide scope for breath diagnostics techniques, and all advanced electrodes applicable to e-nose devices will benefit them. Here, we present the promising sensing capabilities of bare multi-layer graphene (MLG) as a proof of concept for advanced e-nose devices and demonstrate its utility for biomolecule discrimination of the most common lung CMs (ethanol, isopropanol, and acetone). We report on a comparative study involving exposure of the three CM solutions on flat MLG (f-MLG) and patterned MLG (p-MLG) electrodes, where the electrical conductivity of p-MLG is significantly increased while applying acetone. Based on sensitivity tests, we demonstrate the ability to monitor the electrical response of graphene electrodes employing graphene of various wettabilities. Specifically, the f-MLG electrode displays almost 2 times higher sheet resistance (30 Ω sq−1) compared to the hydrophilic p-MLG (12 Ω sq−1). We show significant sensitivity to selected specific molecules of pristine f-MLG and p-MLG while applying CM solutions with a 1.4 × 105 ppm concentration.

Fig. 1 Chemical vapor deposition growth of multi-layer graphene (a schematic image). Methane was used as a carbon source, which under high temperature and an argon atmosphere decomposed into C and H2, as seen from the chemical reaction (a). Resulted carbon atoms were created in nucleation centers on both sides of the Ni foil through penetration and “dissolution” in the catalyst volume32,33 (b). Following the nucleation stage, the first graphene layers were grown directly on the top and bottom sides of Ni foil (c). Formation of multiple layers of graphene occurred according to the “underlayer growth model” with each newly grown layer pushing up the previously grown one (d).











Finally, we show the selectivity of f-MLG and p-MLG-based sensors when exposed to 2.0 × 105 ppm solutions containing different CM combinations. Both sensors were selective in particular to acetone, since the presence of acetone leads to a sheet resistance increase. We demonstrate that an advanced e-nose approach integrated with MLG electrodes has significant potential as a design concept for utilization of molecular detection at variable concentrations such as in early-stage disease diagnosis. This early-stage approach will provide convenient and reusable complex monitoring of CMs compared to typical contact sensors which require target analysis and are limited by disposable measuring. Moreover, further integration of the Internet of Things will introduce advanced e-nose devices as a biotechnological innovation for disease resilience with the potential for commercialization.

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