Work

Thermally Activated Negative Differential Resistance VO x Memristor with Switchable Rate and Leaky Integrate-and-Fire Spiking Dynamics

Year: 2025

Type: article

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.

Source: ACS Nano

DOI: 10.1021/acsnano.5c11481

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

Institutions: National Cheng Kung University, Technische Universität Darmstadt

Language: English

Topic: Advanced Memory and Neural Computing

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,500