Two-Dimensional Materials for Intelligent Gas Sensors

Area of Science:

• Materials Science
• Nanotechnology
• Computer Engineering

Background:

• The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) necessitates intelligent gas sensors with superior performance and secure data processing.
• Conventional gas sensors face challenges like high energy consumption, latency, and security vulnerabilities due to separate components.

Purpose of the Study:

• To provide a comprehensive review of intelligent gas sensors utilizing two-dimensional (2D) materials.
• To highlight advancements in material engineering for enhanced gas sensing and neuromorphic data processing.

Main Methods:

• Systematic review of recent progress in 2D material-based intelligent gas sensors.
• Examination of graphene, transition metal dichalcogenides (TMDs), MXenes, metal-organic frameworks (MOFs), and covalent organic frameworks (COFs).
• Analysis of material enhancement strategies (defect engineering, surface functionalization) and intelligent data processing techniques (hardware optimization, AI collaboration, bioinspired systems).

Main Results:

• 2D materials offer significant potential for improving gas sensing performance through tailored material engineering.
• Neuromorphic data processing techniques, including sensor-AI integration and bioinspired designs, are advancing intelligent gas sensing capabilities.
• Various 2D material categories show promise for next-generation gas sensing applications.

Conclusions:

• Continued research in material design and neuromorphic computing is crucial for developing next-generation intelligent gas sensors.
• Optimizing 2D materials and integrating advanced processing methods will address limitations of conventional systems.
• The review identifies key challenges and future directions for intelligent gas sensing technologies.