Litcius/Paper detail

Thermally Activated Negative Differential Resistance VO <sub> <i>x</i> </sub> Memristor with Switchable Rate and Leaky Integrate-and-Fire Spiking Dynamics

Li‐Chung Shih, Zih-Siao Liao, Gennady Cherkashinin, Eszter Piros, Lambert Alff, Jen‐Sue Chen

2025ACS Nano6 citationsDOIOpen Access PDF

Abstract

High Resolution Image Download MS PowerPoint Slide Spiking neural networks (SNNs) require neuron devices that are both compact and capable of supporting continuous-time and event-based dynamics. Here, we demonstrate a VO x -based threshold switching memristor (TSM) that intrinsically enables dual-mode operation, functioning as both a spiking encoder and a leaky integrate-and-fire (LIF) neuron. While such dual behavior is theoretically possible in volatile memristors, it has only been experimentally demonstrated in limited cases. It is achieved intrinsically in a single VO x -based device, arising from a thermally driven insulator-to-metal transition (IMT) within the VO x layer, confirmed by temperature-dependent XRD and correlated with snap-back negative differential resistance (NDR) observed in electrical measurements. Integrated into a passive circuit, the device generates high-frequency spike trains under analog input and tunable LIF responses under pulsed stimulation. The device achieves a maximum spiking frequency of 570 kHz, a time-to-first-spike (TTFS) of 1.6 μs, and energy consumption as low as 4.7 nJ per spike. These results highlight the strong coupling between structural phase dynamics and neuronal functions, positioning the VO x TSM as a promising platform for scalable neuromorphic hardware with biologically realistic spiking capabilities.

Topics & Concepts

Neuromorphic engineeringMemristorMaterials scienceSpiking neural networkEncoderOptoelectronicsCoupling (piping)ScalabilityBiological systemDynamics (music)Energy (signal processing)VoltageDifferential (mechanical device)Spike (software development)Computer scienceModulation (music)Electronic engineeringTopology (electrical circuits)NanotechnologyPhase lockingEnergy consumptionPhase (matter)AmplitudePhysicsChannel (broadcasting)Molecular dynamicsSynaptic weightIntegrated circuitPhase transitionThreshold voltageNanoelectronicsNegative resistanceChemical physicsAdvanced Memory and Neural ComputingPhotoreceptor and optogenetics researchTransition Metal Oxide Nanomaterials