Emulating synaptic plasticity and resistive switching characteristics through amorphous Ta₂O₅ embedded layer for neuromorphic computing

Memristors with controllable resistive switching (RS) characteristics gain significant attention for neuromorphic computing applications in high-density memory and artificial synapses. Herein, we present the consequence of an amorphous Ta₂O₅ embedded layer on RS and synaptic characteristics of ZrO₂ memristor. Structural and electronic properties of the memristor without and with-Ta₂O₅ are exemplified by x-ray diffraction (XRD) and x-ray photoemission spectroscopy (XPS) measurements. Memristor with-Ta₂O₅ exhibits excellent performance in RS parameters such as lower forming/SET-voltage, improved uniformity of switching cycling, admirable pulse endurance (10⁴), and long retention time (10⁴ s). Moreover, multilevel storage capability is achieved through limiting the current compliance in SET-operation or stop-voltages in RESET-operation. Likewise, diverse synaptic characteristics such as long-term potentiation (LTP), long-term depression (LTD), spike-rate-dependent plasticity (SRDP), paired-pulse facilitation (PPF), and post-tetanic potentiation (PTP), spike-timing-dependent plasticity (STDP) are effectively mimicked, which is regarded as an imperative learning regime of biological synapses. Owing to improved linearity of LTP/LTD behaviors in memristor with-Ta₂O₅, a solid recognition rate (~85%) is achieved for pattern recognition with the modified national institute of standards and technology database (MNIST) handwritten numbers. Memristor with embedded ~2 nm Ta₂O₅ barrier layer shows significant potential applications in high-performance multilevel data storage and neuromorphic computing systems.