A REVIEW OF RECENT ADVANCES IN NANO-ELECTRONICS FOR HIGH-PERFORMANCE SENSING MATERIALS, ARCHITECTURES, AND FUTURE DIRECTIONS

Objective: Nano-electronic sensors are rapidly developing as the enabling technologies of next-generation systems in the Internet of Things (IoT), biomedical diagnostics, environmental measurements, artificial intelligence (AI) computing devices and personalized electronics. This review gives a system-level and a comparative view on the nano-electronic sensors, and better informs the researchers and the industry interested in ensuring such nano-electronic sensors go beyond being mere demonstrations in the lab to working systems with commercial potential. Method: This review is a synthesis of recent innovations in the materials; device designs and fabrication technology form a coherent whole when it comes to defining high performance nano-electronic sensing. The most important material families among which graphene and transition metal chalcogenides, carbon nanotubes (CNTs), metal oxides such as ZnO and SnO2, and silicon nanowires are considered most importantly with regards to their band structure, charge transport behavior, surface functionalization and sensing mechanisms. The review also notes there is architectural development in the conventional resistive sensors to the FET based sensing platforms, networks of nanowires and nanotubes, and the emerging memristive and neuromorphic sensors scalable fabrication methods of CVD growth, atomic layer deposition (ALD), and heterogeneous integration. Results: Trends in cross-technology show there has been a definite shift to device scaling, ultra-low-energy consumption, and reliability conscious design as sensing platforms are brought even closer to actual deployment. They are persistent problems such as drift, hysteresis, variability of devices, and degradation in the environment that are cited as the main bottlenecks to commercialization. Novelty: Lastly, the review finds strategic future directions such as AI-assisted sensor design, hybrid and flexible sensing platforms, self-powered operation and edge-AI, which will be highlighted.