scholarly journals Memristive Non-Volatile Memory Based on Graphene Materials

Micromachines ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 341 ◽  
Author(s):  
Zongjie Shen ◽  
Chun Zhao ◽  
Yanfei Qi ◽  
Ivona Z. Mitrovic ◽  
Li Yang ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Large Scale ◽  
Surface Effect ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Atomic Diffusion ◽  
Promising Alternative ◽  
Operation Speed ◽  
Non Volatile Memory ◽  
Volatile Memory

Resistive random access memory (RRAM), which is considered as one of the most promising next-generation non-volatile memory (NVM) devices and a representative of memristor technologies, demonstrated great potential in acting as an artificial synapse in the industry of neuromorphic systems and artificial intelligence (AI), due its advantages such as fast operation speed, low power consumption, and high device density. Graphene and related materials (GRMs), especially graphene oxide (GO), acting as active materials for RRAM devices, are considered as a promising alternative to other materials including metal oxides and perovskite materials. Herein, an overview of GRM-based RRAM devices is provided, with discussion about the properties of GRMs, main operation mechanisms for resistive switching (RS) behavior, figure of merit (FoM) summary, and prospect extension of GRM-based RRAM devices. With excellent physical and chemical advantages like intrinsic Young’s modulus (1.0 TPa), good tensile strength (130 GPa), excellent carrier mobility (2.0 × 105 cm2∙V−1∙s−1), and high thermal (5000 Wm−1∙K−1) and superior electrical conductivity (1.0 × 106 S∙m−1), GRMs can act as electrodes and resistive switching media in RRAM devices. In addition, the GRM-based interface between electrode and dielectric can have an effect on atomic diffusion limitation in dielectric and surface effect suppression. Immense amounts of concrete research indicate that GRMs might play a significant role in promoting the large-scale commercialization possibility of RRAM devices.

scholarly journals Overview of radiation effects on emerging non-volatile memory technologies

2017 ◽  
Vol 32 (4) ◽  
pp. 381-392
Author(s):  
Irfan Fetahovic ◽  
Edin Dolicanin ◽  
Djordje Lazarevic ◽  
Boris Loncar
Keyword(s):  
Radiation Effects ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Access Memory ◽  
High Radiation ◽  
Different Types ◽  
Non Volatile Memory ◽  
Volatile Memory ◽  
Change Memory

In this paper we give an overview of radiation effects in emergent, non-volatile memory technologies. Investigations into radiation hardness of resistive random access memory, ferroelectric random access memory, magneto-resistive random access memory, and phase change memory are presented in cases where these memory devices were subjected to different types of radiation. The obtained results proved high radiation tolerance of studied devices making them good candidates for application in radiation-intensive environments.

scholarly journals Energy-Efficient Non-Von Neumann Computing Architecture Supporting Multiple Computing Paradigms for Logic and Binarized Neural Networks

2021 ◽  
Vol 11 (3) ◽  
pp. 29
Author(s):  
Tommaso Zanotti ◽  
Francesco Maria Puglisi ◽  
Paolo Pavan
Keyword(s):  
Neural Networks ◽  
High Performance ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Hardware Accelerators ◽  
Memory Architecture ◽  
Ultra Low Power ◽  
Von Neumann ◽  
Non Volatile Memory ◽  
Volatile Memory

Different in-memory computing paradigms enabled by emerging non-volatile memory technologies are promising solutions for the development of ultra-low-power hardware for edge computing. Among these, SIMPLY, a smart logic-in-memory architecture, provides high reconfigurability and enables the in-memory computation of both logic operations and binarized neural networks (BNNs) inference. However, operation-specific hardware accelerators can result in better performance for a particular task, such as the analog computation of the multiply and accumulate operation for BNN inference, but lack reconfigurability. Nonetheless, a solution providing the flexibility of SIMPLY while also achieving the high performance of BNN-specific analog hardware accelerators is missing. In this work, we propose a novel in-memory architecture based on 1T1R crossbar arrays, which enables the coexistence on the same crossbar array of both SIMPLY computing paradigm and the analog acceleration of the multiply and accumulate operation for BNN inference. We also highlight the main design tradeoffs and opportunities enabled by different emerging non-volatile memory technologies. Finally, by using a physics-based Resistive Random Access Memory (RRAM) compact model calibrated on data from the literature, we show that the proposed architecture improves the energy delay product by >103 times when performing a BNN inference task with respect to a SIMPLY implementation.

scholarly journals Improved Synaptic Device Properties of HfAlOx Dielectric on Highly Doped Silicon Substrate by Partial Reset Process

Metals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 772
Author(s):  
Seunghyun Kim ◽  
Osung Kwon ◽  
Hojeong Ryu ◽  
Sungjun Kim
Keyword(s):  
Resistive Switching ◽  
Silicon Substrate ◽  
Photoelectron Spectroscopy ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Alloy Type ◽  
Switching Type ◽  
Neuromorphic System ◽  
Device Properties ◽  
Partial Reset

This work demonstrates the synaptic properties of the alloy-type resistive random-access memory (RRAM). We fabricated the HfAlOx-based RRAM for a synaptic device in a neuromorphic system. The deposition of the HfAlOx film on the silicon substrate was verified by X-ray photoelectron spectroscopy (XPS) analysis. It was found that both abrupt and gradual resistive switching could be implemented, depending on the reset stop voltage. In the reset process, the current gradually decreased at weak voltage, and at strong voltage, it tended to decrease rapidly by Joule heating. The type of switching determined by the first reset process was subsequently demonstrated to be stable switching by successive set and reset processes. A gradual switching type has a much smaller on/off window than abrupt switching. In addition, retention maintained stability up to 2000 s in both switching cases. Next, the multiple current states were tested in the gradual switching case by identical pulses. Finally, we demonstrated the potentiation and depression of the Cu/HfAlOx/Si device as a synapse in an artificial neural network and confirmed that gradual resistive switching was suitable for artificial synapses, using neuromorphic system simulation.

Transparent resistive random access memory and its characteristics for nonvolatile resistive switching

2008 ◽  
Vol 93 (22) ◽  
pp. 223505 ◽  
Author(s):  
Jung Won Seo ◽  
Jae-Woo Park ◽  
Keong Su Lim ◽  
Ji-Hwan Yang ◽  
Sang Jung Kang
Keyword(s):  
Resistive Switching ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Access Memory

Resistive switching characteristics of all-solution-based Ag/TiO2/Mo-doped In2O3devices for non-volatile memory applications

2016 ◽  
Vol 4 (46) ◽  
pp. 10967-10972 ◽  
Author(s):  
Sujaya Kumar Vishwanath ◽  
Jihoon Kim
Keyword(s):  
Resistive Switching ◽  
Retention Time ◽  
Elevated Temperatures ◽  
Switching Behavior ◽  
Memory Devices ◽  
Bipolar Switching ◽  
Non Volatile Memory ◽  
Volatile Memory ◽  
Switching Characteristics ◽  
Memory Applications

The all-solution-based memory devices demonstrated excellent bipolar switching behavior with a high resistive switching ratio of 103, excellent endurance of more than 1000 cycles, stable retention time greater than 104s at elevated temperatures, and fast programming speed of 250 ns.

Resistive Switching Characteristics in TiO2 ReRAM with Top Electrode of Co Selectively Formed on SAMs Printed Patterns

2007 ◽  
Vol 124-126 ◽  
pp. 603-606
Author(s):  
Sang Hee Won ◽  
Seung Hee Go ◽  
Jae Gab Lee
Keyword(s):  
Resistive Switching ◽  
Random Access ◽  
Atomic Layer ◽  
High Resistance State ◽  
Resistive Random Access Memory ◽  
Tio2 Thin Films ◽  
Selective Deposition ◽  
Precise Control ◽  
Resistance State ◽  
Switching Characteristics

Simple process for the fabrication of Co/TiO2/Pt resistive random access memory, called ReRAM, has been developed by selective deposition of Co on micro-contact printed (μ-CP) self assembled monolayers (SAMs) patterns. Atomic Layer Deposition (ALD) was used to deposit TiO2 thin films, showing its ability of precise control over the thickness of TiO2, which is crucial to obtain proper resistive switching properties of TiO2 ReRAM. The fabrication process for Co/TiO2/Pt ReRAM involves the ALD of TiO2 on sputter-deposited Pt bottom electrode, followed by μ-CP with SAMs and then selective deposition of Co. This results in the Co/TiO2/Pt structure ReRAM. For comparison, Pt/TiO2/Pt ReRAM was produced and revealing the similar switching characteristics as that of Co/TiO2/Pt, thus indicating the feasibility of Co replacement with Pt top electrode. The ratios between the high-resistance state (Off state) and the low-resistance state (On state) were larger than 102. Consequently, the selective deposition of Co with μ-CP, newly developed in this study, can simplify the process and thus implemented into the fabrication of ReRAM.

Fabrication of Semi-transparent Resistive Random Access memory and Its Characteristics of Nonvolatile Resistive Switching

2011 ◽  
Vol 1292 ◽  
Author(s):  
Jung Won Seo ◽  
Seung Jae Baik ◽  
Sang Jung Kang ◽  
Koeng Su Lim
Keyword(s):  
Metal Oxide ◽  
Resistive Switching ◽  
Current Density ◽  
Random Access ◽  
Random Access Memory ◽  
Resistive Random Access Memory ◽  
Access Memory ◽  
Promising Candidate ◽  
Forward Current ◽  
Switching Characteristics

ABSTRACTThis report covers the resistive switching characteristics of cross-bar type semi-transparent (or see-through) resistive random access memory (RRAM) devices based on ZnO. In order to evaluate the transmittance of the devices, we designed the memory array with various electrode sizes and spaces between the electrodes. To prevent read disturbance problems due to sneak currents, we employed a metal oxide based p-NiO/n-ZnO diode structure, which exhibited good rectifying characteristics and high forward current density. Based on these results, we found that the combined metal oxide diode/RRAM device could be promising candidate with suppressed read disturbances of cross-bar type ZnO RRAM device.

Reliable analog resistive switching behaviors achieved using memristive devices in AlOx/HfOx bilayer structure for neuromorphic systems

2021 ◽  
Author(s):  
Meng Qi ◽  
Tianquan Fu ◽  
Huadong Yang ◽  
ye tao ◽  
Chunran Li ◽  
...  
Keyword(s):  
Resistive Switching ◽  
Learning Experience ◽  
Random Access ◽  
Resistive Random Access Memory ◽  
Spike Timing ◽  
Information Storage ◽  
Bilayer Structure ◽  
Neuromorphic Computing ◽  
Von Neumann ◽  
Simulation Based

Abstract Human brain synaptic memory simulation based on resistive random access memory (RRAM) has an enormous potential to replace traditional Von Neumann digital computer thanks to several advantages, including its simple structure, high-density integration, and the capability to information storage and neuromorphic computing. Herein, the reliable resistive switching (RS) behaviors of RRAM are demonstrated by engineering AlOx/HfOx bilayer structure. This allows for uniform multibit information storage. Further, the analog switching behaviors are capable of imitate several synaptic learning functions, including learning experience behaviors, short-term plasticity-long-term plasticity transition, and spike-timing-dependent-plasticity (STDP). In addition, the memristor based on STDP learning rules are implemented in image pattern recognition. These results may offer a promising potential of HfOx-based memristors for future information storage and neuromorphic computing applications.

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