Synaptic memory devices from CoO/Nb:SrTiO ₃ junction

Abstract

Non-volatile memristors are promising for future hardware-based neurocomputation application because they are capable of emulating biological synaptic functions. Various material strategies have been studied to pursue better device performance, such as lower energy cost, better biological plausibility, etc. In this work, we show a novel design for non-volatile memristor based on CoO/Nb:SrTiO 3 heterojunction. We found the memristor intrinsically exhibited resistivity switching behaviours, which can be ascribed to the migration of oxygen vacancies and charge trapping and detrapping at the heterojunction interface. The carrier trapping/detrapping level can be finely adjusted by regulating voltage amplitudes. Gradual conductance modulation can therefore be realized by using proper voltage pulse stimulations. And the spike-timing-dependent plasticity, an important Hebbian learning rule, has been implemented in the device. Our results indicate the possibility of achieving artificial synapses with CoO/Nb:SrTiO 3 heterojunction. Compared with filamentary type of the synaptic device, our device has the potential to reduce energy consumption, realize large-scale neuromorphic system and work more reliably, since no structural distortion occurs.

Learning to Approximate Functions Using Nb-Doped SrTiO3 Memristors

“…A less studied class of materials for synaptic device applications are interface-type memristors where electric field controlled resistive switching results from changes occurring at interfaces. While the resistive switching in for example metal/Nb-doped SrTiO 3 (Nb:STO) Schottky junctions, is well-documented in literature, there are not many reports in which they are considered as individual neuromorphic components (Yin et al, 2016;Jang et al, 2018;Zhao et al, 2019), and to the best of our knowledge, no reports of their use as components in neural networks. Often, memristive devices require forming processes, which can be unfavorable for device performance and network integration (Amer et al, 2017;).…”

Multi-Level Analog Resistive Switching Characteristics in Tri-Layer HfO2/Al2O3/HfO2 Based Memristor on ITO Electrode

“…During the application of the negative pulse train, again gradually the weak filaments formed at both interfaces. To implement more accurately synaptic efficiency, of the tri-layer TaN/HfO 2 /Al 2 O 3 /HfO 2 /ITO memristor, negative pulse, and positive depression pulse with increasing amplitude were applied for potentiation and depression characteristics [ 47 , 48 , 49 ]. For potentiation and depression, increasing the pulse amplitude from −0.6 to −1.4 V, with a −0.05 V step, and 0.8 to 1.6 V, with a 0.05 V step, respectively, was applied to each tri-layer RRAM device.…”

Organic iontronic memristors for artificial synapses and bionic neuromorphic computing

“…If the resistance state of the device can be well maintained even after the removal of voltage, this device demonstrates typical nonvolatile memory behaviors. 113 Until now, some mechanisms have been promoted, including conductive filament formation, [114][115][116][117][118] charge trapping modulation, [119][120][121][122] etc.…”

“…119 Some certain carriers become trapped in defects or impurities in the insulating layer, leading to reduced resistance of the memristor. 120 Conversely, when a reverse bias is applied, the trapped charge carriers are released from their confinement, resulting in an increased resistance of the memristor. This charge-trapping modulation serves as a fundamental mechanism for the operation of specific types of memristors such as organic and amorphous oxide variants.…”