A Novel Varying-Bias Read Scheme for MLC and Wide Temperature Range TMO ReRAM

Lin, Yu–Hsuan; Lee, Ming-Hsiu; Wu, Jin-Shang; Lin, Yu-Yu; Lee, Feng-Ming; Lee, Dai-Ying; Chiang, Kuang-Hao; Lai, Erh-Kun; Tseng, Tseung‐Yuen; Lu, Chih‐Yuan

doi:10.1109/led.2016.2606515

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…However, the inconsistency of the currents and external voltages in multilevel devices is much more puzzling. The RS behavior, motivating mechanisms, and various latent models have been debated experimentally ,− and theoretically. − The energy band gap between the conduction and valence bands of the oxide insulator used as a RS layer is normally of 1–4 eV. So the resistance of most oxide films is very large, i.e., initially in the HRS.…”

Section: Classification Of Rs Behavior In Memristorsmentioning

confidence: 99%

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Khan,

Rehman,

Iqbal

et al. 2023

ACS Appl. Electron. Mater.

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Due to the fast evolution of information technology, high-speed and scalable memory devices are being investigated for data storage and datadriven computation. Resistive switching random access memory (RRAM) is one of the very popular types of memristors, because of its quick program/erase speed and high density as a result of its simple two-terminal structure, low power consumption, and low cost of fabrication. In this review, the market for promising memristor-based memories for smart systems is examined. The switching memory devices are described and classified according to their I−V behavior to underline the physical switching mechanisms. The various filament mechanisms of the RRAM memristor, including the valence change mechanism (VCM), electrochemical metallization mechanism (ECM), and thermochemical mechanism (TCM), are especially highlighted in various structures. The performance of resistive switching devices with different reported electrode materials and resistive layers is summarized. This study provides a detailed review of materials of the different deposition techniques used for surface modification and coating. The two major areas of interest, physical and chemical vapor deposition techniques and the influence parameter on the resistive switching, are discussed in detail. The prospective applications of RRAM memristors to various fields such as security, neuromorphic computing, and non-volatile logic systems for artificial intelligence are addressed briefly as well as the future outlook.

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Section: Classification Of Rs Behavior In Memristorsmentioning

confidence: 99%

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Khan,

Rehman,

Iqbal

et al. 2023

ACS Appl. Electron. Mater.

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“…These memory-induced reliability issues will result in wrong weight values and lead to inferencing failure. Among many NVM's, resistive random access memory (ReRAM) has advantages of gradual resistance alterability, low operation power, low cost, high scalability, and good CMOS process compatibility, [14][15][16][17][18][19][20][21][22] thus become a common choice for CIM applications.…”

Section: Introductionmentioning

confidence: 99%

Impacts and solutions of nonvolatile-memory-induced weight error in the computing-in-memory neural network system

Lin

Lee

Wang

et al. 2020

Jpn. J. Appl. Phys.

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Nonvolatile-memory-based computing-in-memory architecture is one of the solutions to the massive data movement problem in the conventional von Neumann computing architecture since multiplication-and-accumulation (MAC) operations can be directly performed inside the memory array. This paper investigates the errors from the imperfections of resistive random access memory, including program error, read fluctuation and retention drift, and their impacts on the inference accuracy in convolutional neural network. The influences from weight errors in each convolution layer are evaluated according to the change of neuron distributions. A batch normalization (BN) parameter calibration method is proposed in order to correctly scale-and-shift the MAC results to compensate weight errors. This calibrated BN process drastically improves the inference accuracy not only for as-programmed analog ReRAM array but also for devices after longtime retention. This approach provides an effective direction to deal with the nonvolatile-memory-induced errors in artificial neural networks.

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“…Recently, resistive random access memory (ReRAM) [1][2][3][4][5][6][7][8][9][10][11][12][13] has widely been considered a promising candidate to replace the present flash memory 14,15) for next-generation nonvolatile memory because of its simple structure, simple process, small cell size, easy scaling, high speed operation, low power consumption, and compatibility with a CMOS process. [16][17][18][19] Among many ReRAMs, transition metal oxide (TMO) ReRAM is more convincing than others.…”

Section: Introductionmentioning

confidence: 99%

Sidewall electrode TiO _x /TiO _x N _y resistive random access memory with excellent memory window control and reliability using plasma oxidation and a novel degradation-detecting writing algorithm

Lai

Lee

et al. 2017

Jpn. J. Appl. Phys.

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A TiOx/TiOxNy resistive random access memory (ReRAM) with a sidewall bottom electrode (BE) is demonstrated for the first time. Several interesting characteristics that are very desirable for high reliability memory applications are observed: (1) a stable RESET and SET resistance switching window even without write verification, (2) good 250 °C data retention, (3) ReRAM switching instability after cycling is monitored and corrected, resulting in good reliability, and (4) using only complementary metal oxide semiconductor (CMOS) familiar materials and processes, thus very manufacture-friendly. The thickness and quality of TiOx and TiOxNy are well controlled by plasma oxidation, and a large resistance switching window (>10×), a low operation voltage, and good reliability are realized.

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A Novel Varying-Bias Read Scheme for MLC and Wide Temperature Range TMO ReRAM

Cited by 10 publications

References 17 publications

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Impacts and solutions of nonvolatile-memory-induced weight error in the computing-in-memory neural network system

Sidewall electrode TiO _x /TiO _x N _y resistive random access memory with excellent memory window control and reliability using plasma oxidation and a novel degradation-detecting writing algorithm

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A Novel Varying-Bias Read Scheme for MLC and Wide Temperature Range TMO ReRAM

Cited by 10 publications

References 17 publications

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Resistive Switching Properties in Memristors for Optoelectronic Synaptic Memristors: Deposition Techniques, Key Performance Parameters, and Applications

Impacts and solutions of nonvolatile-memory-induced weight error in the computing-in-memory neural network system

Sidewall electrode TiO x /TiO x N y resistive random access memory with excellent memory window control and reliability using plasma oxidation and a novel degradation-detecting writing algorithm

Contact Info

Product

Resources

About

Sidewall electrode TiO _x /TiO _x N _y resistive random access memory with excellent memory window control and reliability using plasma oxidation and a novel degradation-detecting writing algorithm