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

Area of Science:

• Biomolecular Sensing and Diagnostics
• Materials Science for Sensor Technology
• Nanomaterials for Electronic Devices

Background:

• Early detection of lung cancer via breath analysis is crucial but faces challenges like sensor sensitivity and stability.
• Electronic-nose (e-nose) devices offer a promising, non-invasive approach for diagnosing lung cancer using volatile organic compounds (VOCs).
• Existing e-nose technologies require improvement in sensor performance, selectivity, and longevity for reliable early-stage disease detection.

Purpose of the Study:

• To evaluate the sensing capabilities of bare multi-layer graphene (MLG) for detecting lung cancer biomarkers (CMs) in exhaled breath.
• To demonstrate the utility of MLG electrodes in discriminating between common lung cancer-related CMs: ethanol, isopropanol, and acetone.
• To investigate the performance of both flat (f-MLG) and patterned (p-MLG) graphene electrodes for e-nose applications.

Main Methods:

• Comparative study of f-MLG and p-MLG electrodes exposed to solutions of ethanol, isopropanol, and acetone at varying concentrations.
• Electrical conductivity and sheet resistance measurements of MLG electrodes upon exposure to target CMs.
• Assessment of sensor selectivity by exposing electrodes to mixtures of CMs.

Main Results:

• Patterned MLG (p-MLG) exhibited significantly increased electrical conductivity upon exposure to acetone.
• MLG electrodes demonstrated sensitivity to specific CMs, with f-MLG showing higher sheet resistance (30 Ω sq-1) than p-MLG (12 Ω sq-1).
• Both f-MLG and p-MLG sensors showed selectivity, particularly for acetone, indicated by a sheet resistance increase.

Conclusions:

• Multi-layer graphene (MLG) electrodes are a viable proof-of-concept for advanced e-nose devices, enabling molecular detection for early-stage disease diagnosis.
• MLG-based e-nose sensors offer convenient, reusable monitoring of CMs, surpassing limitations of traditional disposable sensors.
• Integration with IoT could position MLG-based e-nose devices as a commercializable biotechnological innovation for disease resilience.