Nanomaterial-Based Biosensors: From Theoretical Modelling to Practical Applications

Nanomaterial-based biosensors have emerged as a revolutionary approach to detecting biological and chemical analytes, offering unparalleled sensitivity, selectivity, and versatility. This study explores the integration of advanced nanomaterials, such as graphene, carbon nanotubes, and metal nanoparticles, into biosensor technologies. Employing theoretical modeling techniques, including Density Functional Theory (DFT), the research elucidates the interaction mechanisms between nanomaterials and target analytes, providing critical insights into adsorption energy, charge transfer, and electronic structure modifications. The experimental phase synthesizes and characterizes nanomaterials, focusing on optimizing their structural, chemical, and electronic properties for biosensing applications. These materials are incorporated into electrochemical, optical, and field-effect transistor (FET) sensor platforms, demonstrating enhanced performance metrics, including ultra-low detection limits, rapid response times, and exceptional specificity. Applications span healthcare diagnostics, environmental monitoring, and food safety, addressing pressing global challenges such as disease detection, pollutant monitoring, and quality control. The study highlights the scalability and reproducibility of nanomaterial-based biosensors and discusses integration with emerging technologies like artificial intelligence for real-time data analysis. This work establishes a comprehensive framework for designing next-generation biosensors, leveraging the unique properties of nanomaterials to achieve breakthroughs in sensitivity, miniaturization, and multifunctionality.