Litcius/Paper detail

Multifunctional Artificial Electric Synapse of MoSe<sub>2</sub>-Based Memristor toward Neuromorphic Application

Yumo Li, Yumo Li, Hao Sun, Langchun Yue, Fengxia Yang, Xiaofei Dong, Jianbiao Chen, Jiangtao Chen, Xuqiang Zhang, Yun Zhao, Kai Chen, Yan Li, Yan Li

2025The Journal of Physical Chemistry Letters18 citationsDOI

Abstract

Research on memristive devices to seamlessly integrate and replicate the dynamic behaviors of biological synapses will illuminate the mechanisms underlying parallel processing and information storage in the human brain, thereby affording novel insights for the advancement of artificial intelligence. Here, an artificial electric synapse is demonstrated on a one-step Mo-selenized MoSe 2 memristor, having not only long-term stable resistive switching characteristics (reset 0.51 ± 0.01 V, on/off ratio > 30, retention > 10 3 s) but also diverse electrically adjustable synaptic behaviors, including multilevel conductance (synaptic weight), excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), long-term potentiation/depression (LTP/D), spike-timing-dependent plasticity (STDP), and especially activity-dependent synaptic plasticity (ADSP). More significantly, neuromorphic functions of both image edge extraction and biological perception imitation have been successfully achieved. These results present a promising design toward synaptic devices for advancing neuromorphic systems with integrated brain-like neural sensing, memory, and recognition.

Topics & Concepts

Neuromorphic engineeringMemristorSynapseMaterials scienceArtificial intelligenceComputer scienceArtificial neural networkNanotechnologyEngineeringElectrical engineeringNeurosciencePsychologyAdvanced Memory and Neural ComputingNeuroscience and Neural EngineeringConducting polymers and applications