MXene-Ti₃C₂T_x-Based Neuromorphic Computing: Physical Mechanisms, Performance Enhancement, and Cutting-Edge Computing

Area of Science:

• Materials Science
• Neuroscience
• Computer Engineering

Background:

• Neuromorphic devices mimic biological neurons for efficient, low-power computing.
• MXene-Ti₃C₂T_x, a 2D material, offers excellent electrical and mechanical properties for neuromorphic applications.

Purpose of the Study:

• To review the advantages and properties of MXene-Ti₃C₂T_x in neuromorphic devices.
• To promote the further development and application of MXene-Ti₃C₂T_x-based neuromorphic technology.

Main Methods:

• Categorization of physical mechanisms in MXene-Ti₃C₂T_x neuromorphic devices.
• Systematic summary and classification of optimization techniques (doping, interface, structural engineering).
• Compilation of research results and discussion of challenges and prospects.

Main Results:

• MXene-Ti₃C₂T_x exhibits key physical mechanisms suitable for neuromorphic functions.
• Advanced engineering techniques enhance MXene-Ti₃C₂T_x performance for neuromorphic devices.
• Innovative applications in near-sensor and in-sensor computing are highlighted.

Conclusions:

• MXene-Ti₃C₂T_x is a highly promising material for next-generation neuromorphic devices.
• Further research and development are needed to overcome challenges for practical applications.
• This review provides a foundation for MXene-Ti₃C₂T_x in neuromorphic engineering.