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

Neuromorphic devices have shown great potential in simulating the function of biological neurons due to their efficient parallel information processing and low energy consumption. MXene-TiCT, an emerging two-dimensional material, stands out as an ideal candidate for fabricating neuromorphic devices. Its exceptional electrical performance and robust mechanical properties make it an ideal choice for this purpose. This review aims to uncover the advantages and properties of MXene-TiCT in neuromorphic devices and to promote its further development. Firstly, we categorize several core physical mechanisms present in MXene-TiCT neuromorphic devices and summarize in detail the reasons for their formation. Then, this work systematically summarizes and classifies advanced techniques for the three main optimization pathways of MXene-TiCT, such as doping engineering, interface engineering, and structural engineering. Significantly, this work highlights innovative applications of MXene-TiCT neuromorphic devices in cutting-edge computing paradigms, particularly near-sensor computing and in-sensor computing. Finally, this review carefully compiles a table that integrates almost all research results involving MXene-TiCT neuromorphic devices and discusses the challenges, development prospects, and feasibility of MXene-TiCT-based neuromorphic devices in practical applications, aiming to lay a solid theoretical foundation and provide technical support for further exploration and application of MXene-TiCT in the field of neuromorphic devices.