Emulating synaptic plasticity and resistive switching characteristics through amorphous Ta2O5 embedded layer for neuromorphic computing. Issue 21 (1st November 2021) - Ismail, Muhammad; Abbas, Haider; Sokolov, Andrey; Mahata, Chandreswar; Choi, Changhwan; Kim, Sungjun
Abstract: 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 Ta2 O5 embedded layer on RS and synaptic characteristics of ZrO2 memristor. Structural and electronic properties of the memristor without and with-Ta2 O5 are exemplified by x-ray diffraction (XRD) and x-ray photoemission spectroscopy (XPS) measurements. Memristor with-Ta2 O5 exhibits excellent performance in RS parameters such as lower forming/SET-voltage, improved uniformity of switching cycling, admirable pulse endurance (10 4 ), and long retention time (10 4 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-Ta2 O5, 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 Ta2 O5 barrier layer shows significant potential applications in high-performance multilevel data storage and neuromorphic computing systems.