Ti3C2Tx -MXene Based Planar Memristors on Flexible Cyclic Olefin Copolymer with Voltage-Controlled Switching Behavior for Neuromorphic Applications
Abstract
Real-time edge artificial intelligence (AI) demands memory elements that are not only energy-efficient and multifunctional, but also compact, tunable, and integrable with flexible substrates. Planar memory architecture offers distinct advantages for neuromorphic computing, including surface accessibility, facile fabrication, and seamless integration with flexible substrates, making it ideal for next-generation synaptic hardware. Traditional metal oxide-based memristors often fail to meet all these requirements simultaneously due to their rigid architecture and limited material versatility. Herein, we present a planar Ti3C2Tx-MXene-based memristor (PMX-memristor) fabricated on a flexible cyclic olefin copolymer (COC) substrate, constituting the first fully planar MXene-based resistive device reported to date. The planar architecture exposes the active MXene channel, which enables direct surface inspection and functionalization while delivering robust analog switching. By tuning the voltage amplitude, the device operates in two modes: (i) a volatile regime based on valence change dynamics with transient conductance states, and (ii) a non-volatile regime driven by voltage-induced Ti→TiOx transformation, supporting eight distinct resistance levels. Detailed EDX and XPS analyses, performed before and after electrical stress, confirm the voltage-induced oxidation pathway that underpins this dual-mode behavior. The memristor’s eight-level precision enables compact 9-bit weight encoding using 3×3-bit multi-level cells in crossbar arrays, reducing area and energy compared to binary implementations. We demonstrate end-to-end deployment of these devices in spiking neural networks for real-time classification of neuromorphic vision datasets, showcasing high-performance, task-relevant learning capabilities on benchmarks such as N-MNIST and DVS-Gesture. These results underscore the potential of the designed PMX-memristor for voltage-controlled, neuromorphic edge computing and provide direct surface accessibility for functionalization, and potential bio-interfacing for next-generation smart wearables.