Ti₃C₂-Based MXene Oxide Nanosheets for Resistive Memory and Synaptic Learning Applications

Area of Science:

• Materials Science
• Nanotechnology
• Computer Engineering

Background:

• MXenes are novel 2D nanomaterials with exceptional properties.
• MXene device engineering for computing is underexplored.
• Ti₃C₂ MXene shows promise for electronic applications.

Purpose of the Study:

• To engineer Ti₃C₂ MXene for digital and analog computing.
• To investigate the impact of top electrodes on resistive switching (RS) properties.
• To explore Ti₃C₂ MXene for non-volatile memory and synaptic learning.

Main Methods:

• Synthesized Ti₃C₂ MXene using a chemical process.
• Analyzed structural, compositional, and morphological properties.
• Fabricated and tested memory devices with different top electrodes (Ag, Pt, Al).

Main Results:

• The Al/Ti₃C₂/Pt device demonstrated superior resistive switching and reliability.
• The device successfully mimicked synaptic properties and Hebbian learning.
• Electron transport followed a filamentary RS mechanism.

Conclusions:

• Ti₃C₂ MXene is a viable material for advanced memory and neuromorphic computing.
• Electrode engineering is crucial for optimizing MXene-based device performance.
• The Al/Ti₃C₂/Pt memristor shows potential for future electronic applications.