Developing the electrical biosensor by controlling the crystallinity of carbon nanotube film through solution-process

Abstract

Biosensors are used in various applications such as disease diagnosis, environmental monitoring, new drug development, and food hygiene. As the aging society is accelerating, the recent medical paradigm is changing to prevention through early diagnosis of disease. In addition, as the COVID-19 infection becomes prevalent worldwide, the rapid diagnosis of new diseases is also in the spotlight. It is important to construct a biosensor system that can be applied not only to one specific disease, but to be more diverse. In this thesis, we fabricated an electrical biosensor based on a thin film of carbon nanotubes formed by the solution-process to build such a system. Because carbon nanotubes have high electrical conductivity, a size of several nanometers similar to biomolecules, and a high surface area ratio, they are suitable materials for detecting minute changes occurring on the surface. In order to maximize the advantages of these carbon nanotubes, a sensor with very high uniformity and low detection limit was produced by aligning the carbon nanotubes into a single molecular layer by Langmuir-Blodgett process. It was applied for early diagnosis of Alzheimer's Disease with a diagnostic accuracy of 88.6%. Because it is not possible to determine the relationships between the thin film properties (film thickness, uniformity, alignment, and surface coverage) of the carbon nanotube thin film with this process, we fabricated a CNT-based biosensor by solution shearing process, which is flexible system and simple to control process variables. In addition, for efficient variable control, a CNT-based electrical biosensor with high sensitivity and versatility was produced by effectively optimizing sensor performance by introducing the Design of Experiment. This device was applied to detection the nucleocapsid protein of the COVID-19 virus, showing the establishment of a general-purpose sensing system.