Resistive switching characteristics of manganese oxide thin film and nanoparticle assembly hybrid devices

Kang

et al. 2019

Jpn. J. Appl. Phys.

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Resistive switching properties of hafnium oxide and manganese oxide double-layer films sandwiched between Pt bottom electrode and Ag top electrode have been investigated. The devices exhibited bipolar resistive switching. As compared with the devices with hafnium oxide and manganese oxide single layer, the double-layered devices showed better resistive switching behaviors, including forming-free behavior, a high resistance ratio (>105–6), and good retention properties. The forming-free behavior of the bilayer device is very useful for resistive random access memory applications. The high resistance ratio is beneficial to distinguish the storage information. The formation and disruption of Ag conductive filament in the oxide layers led to the resistance changes.

Section: Resultsmentioning

confidence: 86%

Forming-free resistive switching characteristics in manganese oxide and hafnium oxide devices

Kang

et al. 2019

Jpn. J. Appl. Phys.

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“…The electroforming process is a phenomenon of resistive memories where the initial conductive filaments begin to grow by the progression of oxidized metal ions migration within the insulating medium by the application of applied voltage. [ 56 ] As a result of the continuous growth of these filaments, the top and bottom conducting electrodes connect together by virtue of which the insulating high resistance (OFF) state changes to conductive low resistance (ON) state. It is usually a preparatory step in most of the memristors before the actual switching cycles and voltages for SET (ON) and RESET (OFF) are observed.…”

Section: Resultsmentioning

confidence: 99%

Cellulose Nanocrystal Based Bio‐Memristor as a Green Artificial Synaptic Device for Neuromorphic Computing Applications

Hussain

Adv Materials Technologies

Youn

et al. 2021

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sustainable materials and green electronics. [1,2] In particular, eco-friendly, renewable, bio-compatible, and bio-degradable natural biomaterials are potential alternatives to emerging green electronics that can reduce harmful electronic waste. The use of natural biomaterials greatly aids the sustainable development of the electronics industry. [2][3][4][5] In fact, natural biomaterials such as (e.g., silk fibroin, spider silk, cellulose, chitosan, etc.) have been widely employed in a variety of green-electronic systems, such as energy storage devices, biosensors, and bio-memristor, benefiting from unique biological structure, biocompatibility, biodegradability, transparency, and flexibility. [6][7][8] However, biomaterials often exhibit degradable and unstable performance due to their weak electrical function. Therefore, recent investigations into biocomposites containing one or more naturally-derived content combined with other functional materials have shown the improved performance of bioelectronic elements. [2,[9][10][11] In addition, increasing demand for green information storage and computation technology has accelerated the rapid development of nonvolatile memory devices based on biocomposite materials. Among the emerging nonvolatile memory technologies, resistive switching random access memory (RRAM), in which the resistance states can be switched between the high resistance state (HRS) and the low resistance state (LRS) by applying an electric field, has

“…RRAM offers easy fabrication and high-density memory owing to a simple metal-insulator-metal (MIM) structure. Each memory cell compromises a switching material (insulator/semiconductor) sandwiched between two metal electrodes [ 7 , 8 ]. Due to the simple structure, it also offers the best scalability features.…”

Section: Introductionmentioning

confidence: 99%

Conductive Bridge Random Access Memory (CBRAM): Challenges and Opportunities for Memory and Neuromorphic Computing Applications

Ang

2022

Micromachines

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Due to a rapid increase in the amount of data, there is a huge demand for the development of new memory technologies as well as emerging computing systems for high-density memory storage and efficient computing. As the conventional transistor-based storage devices and computing systems are approaching their scaling and technical limits, extensive research on emerging technologies is becoming more and more important. Among other emerging technologies, CBRAM offers excellent opportunities for future memory and neuromorphic computing applications. The principles of the CBRAM are explored in depth in this review, including the materials and issues associated with various materials, as well as the basic switching mechanisms. Furthermore, the opportunities that CBRAMs provide for memory and brain-inspired neuromorphic computing applications, as well as the challenges that CBRAMs confront in those applications, are thoroughly discussed. The emulation of biological synapses and neurons using CBRAM devices fabricated with various switching materials and device engineering and material innovation approaches are examined in depth.