TiO₂ Nanowire Array Memristive Devices Emulating Functionalities of Biological Synapses

Abstract

Memristors are deemed to be the electrical twin to biological synapses. They enable emulation of human memory functionalities such as learning, memorizing, and forgetting. The present hydrothermally grown titanium dioxide nanowire array memristive devices have shown to be able to mimic synaptic behaviors. As well as spike‐rate dependent plasticity, excitatory postsynaptic currents, and paired pulse facilitation, high endurance, and on/off ratios for the nanowire arrays are presented. Decay fitting of postsynaptic currents with Kohlrausch's equation shows lifetimes of few milliseconds up to several hundred seconds, offering the possibility of a short‐term to long‐term memory transition. Furthermore, a strong dependence of the lifetime of the signals on the frequency and amplitude of the stimulation pulses is observed.

Highly Reliable 3D Channel Memory and Its Application in a Neuromorphic Sensory System for Hand Gesture Recognition

“…Figure 6c demonstrates that the PSC at the second pulse is increased compared to that at the first pulse. The enhancement ratio, defined as the PPF index, 87,88 exponentially increases as the interval (Δt) between successive pulses decreases (Figure 6d), similar to the behavior observed in biological neurons. 89,90 The correlation between the PPF index and interval time is fitted using the equation PPF = 1 + C 1 exp(−Δt/τ 1 ) + C 2 exp(−Δt/τ 2 ), where C 1 and C 2 represent the initial facilitation of the rapid and slow phases, and τ 1 and τ 2 represent the relaxation time of the rapid and slow phases.…”

Emerging Optical In‐Memory Computing Sensor Synapses Based on Low‐Dimensional Nanomaterials for Neuromorphic Networks

“…The retention curves after removing consecutive optical pulses were plot and the decay tendency of current followed the Kohlrausch equation, which was described as the "Forgetting Function" in the field of psychology. [83,[90][91][92][93][94][95] The linear performance of the relaxation time with optical stimuli in the plot verified the transition from STP to LTP. The performance of STP and LTP could be observed in Figure 4f,g.…”

Promising Materials and Synthesis Methods for Resistive Switching Memory Devices: A Status Review

“…Their results suggested that the preparative parameters affect the quality of the switching layer, which directly influences the memory properties of the TiO 2 -based memristive devices . In recent years, synaptic learning properties were also demonstrated by using TiO 2 -based Rs devices. − These results suggested that the properly tuned TiO 2 nanomaterials are useful for both memory and neuromorphic computing applications. Apart from TiO 2 , other organic and inorganic materials are also worked as an active switching layer of RS devices, as shown in Figure .…”