• Applied Microscopy
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• v.46 no.4
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• pp.206-216
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• 2016

This communication is to elucidate the state-of-the-art of techniques necessary to gather information on a new class of nanoelectronic devices known as memristors and related resistive switching devices, respectively. Unlike classical microelectronic devices such as transistors, the chemical and structural variations occurring upon switching of memristive devices require cutting-edge electron microscopy techniques. Depending on the switching mechanism, some memristors call for the acquisition of atomically resolved structural data, while others rely on atomistic chemical phenomena requiring the application of advanced X-ray and electron spectroscopy to correlate the real structure with properties. Additionally, understanding resistive switching phenomena also necessitates the application not only of pre- and post-operation analysis, but also during the process of switching. This highly challenging in situ characterization also requires the aforementioned techniques while simultaneously applying an electrical bias. Through this review we aim to give an overview of the possibilities and challenges as well as an outlook onto future developments in the field of nanoscopic characterization of memristive devices.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.174-174
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• 2014

Memristor devices are one of the most promising candidate approaches to next-generation memory technologies. Memristive switching phenomena usually rely on repeated electrical resistive switching between non-volatile resistance states in an active material under the application of an electrical stimulus, such as a voltage or current. Recent reports have explored the use of variety of external operating parameters, such as the modulation of an applied magnetic field, temperature, or illumination conditions to activate changes in the memristive switching behaviors. Among these possible choices of signal controlling factors of memristor, photon is particularly attractive because photonic signals are not only easier to reach directly over long distances than electrical signal, but they also efficiently manage the interactions between logic devices without any signal interference. Furthermore, due to the inherent wave characteristics of photons, the facile manipulation of the light ray enables incident light angle controlled memristive switching. So that, in the tautological sense, device orienting position with regard to a photon source determines the occurrence of memristive switching as well. To demonstrate this position controlled memory device functionality, we have fabricated a metal-semiconductor-metal memristive switching nanodevice using ZnO nanorods. Superhydrophobicity employed in this memristor gives rise to illumination direction selectivity as an extra controlling parameter which is important feature in emerging. When light irradiates from a point source in water to the surface treated device, refraction of light ray takes place at the water/air interface because of the optical density differences in two media (water/air). When incident light travels through a higher refractive index medium (water; n=1.33) to lower one (air; n=1), a total reflection occurs for incidence angles over the critical value. Thus, when we watch the submerged NW arrays at the view angles over the critical angle, a mirror-like surface is observed due to the presence of air pocket layer. From this processes, the reversible switching characteristics were verified by modulating the light incident angle between the resistor and memristor.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.113-117
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• 2021

A composite active layer was designed based on graphene quantum dots, which is a low-dimensional structure, and a heterogeneous active layer of graphene quantum dots was applied to the interfacial defect structure to overcome the limitations. Increasing to 1.5~3.5 wt % PVP GQD, Vf changed from 2.16 ~ 2.72 V. When negative deflection is applied to the lower electrode, electrons travel through the HfOx/ITO interface. The Al + ions are reduced and the device dominates at low resistance. In addition, as the PVP GQD concentration increased, the depth of the interfacial defect decreased, and the repetition of appropriate electrical properties was confirmed through Al and HfOx/ITO. The low interfacial defects help electrophoresis of Al+ ions to the PVP GQD layer and the HfOx thin film. A local electric field increase occurred, resulting in the breakage of the conductive filament in the defect.

• Journal of the Semiconductor & Display Technology
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• v.20 no.1
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• pp.54-58
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• 2021

The RGO with controllable oxygen functional groups is a novel material as the active layer of resistive switching memory through a reduction process. We designed a nanoscale conductive channel induced by local oxygen ion diffusion in an Au / RGO+GQD / Al resistive switching memory structure. A strong electric field was locally generated around the Al metal channel generated in BIL, and the local formation of a direct conductive low-dimensional channel in the complex RGO graphene quantum dot region was confirmed. The resistive memory design of the complex RGO graphene quantum dot structure can be applied as an effective structure for charge transport, and it has been shown that the resistive switching mechanism based on the movement of oxygen and metal ions is a fundamental alternative to understanding and application of next-generation intelligent semiconductor systems.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.11
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• pp.59-65
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• 2015

By harnessing the thermal hysteresis behavior of vanadium dioxide($VO_2$), we demonstrated multi-resistance states in a two-terminal electronic device based on a $VO_2$ thin film by using a 966nm infrared laser diode as an excitation light source for resistance modulation. Before stimulating the device using 966nm laser pulses, the thermal hysteresis behavior of the device resistance was measured by using a temperature chamber. After that, the $VO_2$ device was thermally biased at ${\sim}71.6^{\circ}C$ so that its temperature fell into the thermal hysteresis region of the device resistance. Six multi-states of the device resistance could be obtained in the fabricated $VO_2$ device by five successive laser pulses with equal 10ms duration and increasing power. Each resistance states were maintained while the temperature bias was applied. And, the resistance fluctuation level was within 2.2% of the stabilized resistance and decreased down to less than 0.9% of the stabilized resistance 5s after the illumination.

• Journal of the Semiconductor & Display Technology
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• v.23 no.1
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• pp.1-6
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• 2024

Recently, artificial neural networks have been playing a crucial role and advancing across various fields. Artificial neural networks are typically categorized into feedforward neural networks and recurrent neural networks. However, feedforward neural networks are primarily used for processing static spatial patterns such as image recognition and object detection. They are not suitable for handling temporal signals. Recurrent neural networks, on the other hand, face the challenges of complex training procedures and requiring significant computational power. In this paper, we propose memristors suitable for an advanced form of recurrent neural networks called reservoir computing systems, utilizing a mask processor. Using the characteristic equations of Ti/TiOx/TaOy/Pt, Pt/TiOx/Pt, and Ag/ZnO-NW/Pt memristors, we generated current-voltage curves to verify their memristive behavior through the confirmation of hysteresis. Subsequently, we trained and inferred reservoir computing systems using these memristors with the NIST TI-46 database. Among these systems, the accuracy of the reservoir computing system based on Ti/TiOx/TaOy/Pt memristors reached 99%, confirming the Ti/TiOx/TaOy/Pt memristor structure's suitability for inferring speech recognition tasks.