Two-Dimensional Materials for Intelligent Gas Sensors

The rapid advancement of the artificial intelligence (AI) and Internet of Things has intensified the demand for intelligent gas sensors that not only deliver high sensing performance but also enable efficient and secure data processing. Conventional gas sensing systems, which rely on separate sensing, memory, and computing units, suffer from high energy consumption, significant latency, and inherent security risks. This review provides a systematic overview of recent progress in intelligent gas sensors based on two-dimensional (2D) materials, focusing on two key aspects: improving gas sensing performance through material engineering and enabling neuromorphic data processing. We examine three major categories of 2D materials-graphene and transition metal dichalcogenides (TMDs), MXenes, and porous frameworks [metal-organic frameworks (MOFs) and covalent organic frameworks (COFs)]-and discuss their synthesis methods as well as performance enhancement strategies such as defect engineering and surface functionalization. Additionally, we analyze advanced intelligent data processing techniques, including hardware circuit optimization, sensor-AI collaborative design, and the development of bioinspired olfactory and multimodal perception systems. Finally, we outline current challenges and future research directions in material design and neuromorphic computing strategies to support the evolution of next-generation intelligent gas sensing technologies.