Tailoring Conductive MXene@MOF Interfaces: New Generation of Synapse Devices for Neuromorphic Computing

Synapse devices, pivotal components in neuromorphic computing, demonstrate unique properties that are essential for advanced computing systems. These devices, characterized by their metal/resistive layer/metal structure, rely heavily on active layer material. One important challenge in developing synapse devices for artificial neural networks lies in constructing these networks at a hardware level to achieve in-memory computing, enabling the efficient processing of information while minimizing power consumption. Herein, we present a rational design and in situ synthesis of two-dimensional (2D/2D) heteronanostructures intricately integrating Ti-based metal carbide as Ti-MXene (Ti3C2) with copper-based metal–organic framework as Cu-tetrakis (4-carboxyphenyl) porphyrin (Cu-TCPP) through van der Waals interactions to form a hybrid as [Ti3C2@Cu-TCPP] (1). The hybrid exhibits synergistic properties of both counterparts with an intricate hierarchical structure, ensuring exceptional stability and remarkable conductivity, fundamental for the progression of advanced neuromorphic devices. The resultant hybrids show an advanced neuromorphic device with comprehensive comparative analysis using DC I–V sweeps was conducted to evaluate different device types, focusing on parameters such as the high-resistance state, low-resistance state, and on/off ratio. Results demonstrated that Ti3C2@Cu-TCPP@PVA-based devices exhibited an impressive on/off ratio of approximately 102, outperforming Cu-TCPP@PVA and Ti3C2@PVA-based devices. This highlights the superior performance of Ti3C2@Cu-TCPP@PVA and its potential for advanced applications in neural network systems. Furthermore, the conduction mechanism was elucidated, revealing the dominance of the space-charge limited conduction mechanism during the SET process and the Schottky emission mechanism during the RESET process.