As the application of artificial vision systems continues to grow, developing efficient and low-power visual sensing devices has become a key challenge. Memristors offer tunable conductivity and integrated in-situ storage and computation functions, making them ideal for low-cost visual systems. However, most memristors currently face the dual challenges of poor stability and limited optoelectronic synaptic plasticity. Here, a Bi2Te2.7Se0.3/SnSe hetero-memristor is designed, which combines the advantages of two-dimensional (2D) topological insulators and 2D ferroelectric materials. The hetero-memristor performance can be tuned by the SnSe ferroelectric polarization and Bi2Te2.7Se0.3 topological surface state, which improve the utilization and mobility of carriers, thereby significantly improving the performance. The high 104-cycle stability, average 0.25 µW on/off power, and 25 conductive states are achieved. Under different signals, the hetero-memristor can enable in situ light-electric conversion and successfully simulate various optoelectronic plasticity behaviors, such as paired-pulse facilitation, post-tetanic potentiation, spike rate-dependent plasticity, etc. Mean while, an efficient in-situ bionic-visual semi-hardware system is constructed based on the 28 × 28 perception hetero-memristor array. This system efficiently performs satellite image recognition and classification, achieving an accuracy of 97.68%. The research shows that the Bi2Te2.7Se0.3/SnSe hetero-memristor is with excellent optoelectronic performances and broad application prospects, particularly in brain-like computing, smart hardware, and storage technologies.
Keywords: 2D ferroelectric; 2D topological; high‐efficiency; high‐stability; memristor; neuromorphic system.
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