Endurance/Retention Trade Off in HfOx and TaOx Based RRAM

Azzaz, M.; Vianello, E.; Sklénard, B.; Blaise, P.; Roule, A.; Sabbione, C.; Bernasconi, S.; Charpin, C.; Cagli, C.; Jalaguier, E.; Jeannot, S.; Denorme, S.; Candelier, P.; Yu, Minrui; Nistor, Lavinia; Fenouillet-Béranger, C.; Perniola, L.

doi:10.1109/imw.2016.7495268

Cited by 29 publications

(40 citation statements)

References 6 publications

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“…The three switching modes are controllable by the CC during the forming and set processes ( Figure S1) [22]. Next, endurance, cumulative probability, and retention are investigated for the 3 different switching modes in the TaO x /HfO 2 memristor to evaluate its reliability and variability [23]. Figure 3a-c show endurance tests for filamentary, interface-type, and pseudo interface-type switching, respectively.…”

Section: Methodsmentioning

confidence: 99%

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

Ryu

Kim

2020

Nanomaterials

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Memristor-type synaptic devices that can effectively emulate synaptic plasticity open up new directions for neuromorphic hardware systems. Here, a double high-k oxide structured memristor device (TaOx/HfO2) was fabricated, and its synaptic applications were characterized. Device deposition was confirmed through TEM imaging and EDS analysis. During the forming and set processes, switching of the memristor device can be divided into three types by compliance current and cycling control. Filamentary switching has strengths in terms of endurance and retention, but conductance is low. On the other hand, for interface-type switching, conductance is increased, but at the cost of endurance and retention. In order to overcome this dilemma, we proposed pseudo interface-type switching, and obtained excellent retention, decent endurance, and a variety of conductance levels that can be modulated by pulse response. The recognition rate calculated by the neural network simulation using the Fashion Modified National Institute of Standards and Technology database (MNIST) dataset, and the measured conductance values show that pseudo interface-type switching produces results that are similar to those of an interface-type device.

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Section: Methodsmentioning

confidence: 99%

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

Ryu

Kim

2020

Nanomaterials

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“…With present age computing being more and more data driven, there has been demands for a memory technology which is more in-tune with the present and future requirements. Compared to the several emerging devices, RRAM devices are more scalable [ 14 – 18 ], have high density [ 19 – 24 ], consume low power [ 25 – 29 ], are faster [ 30 – 33 ], have higher endurance and retention [ 34 – 37 ] and highly CMOS compatible [ 38 – 42 ]. RRAM devices are one of the most popular non-volatile memory technologies with extensive study being undertaken to understand their mechanism and develop models to realize the device operation and design accurate and simple device structure.…”

Section: Introductionmentioning

confidence: 99%

A Collective Study on Modeling and Simulation of Resistive Random Access Memory

2018

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In this work, we provide a comprehensive discussion on the various models proposed for the design and description of resistive random access memory (RRAM), being a nascent technology is heavily reliant on accurate models to develop efficient working designs and standardize its implementation across devices. This review provides detailed information regarding the various physical methodologies considered for developing models for RRAM devices. It covers all the important models reported till now and elucidates their features and limitations. Various additional effects and anomalies arising from memristive system have been addressed, and the solutions provided by the models to these problems have been shown as well. All the fundamental concepts of RRAM model development such as device operation, switching dynamics, and current-voltage relationships are covered in detail in this work. Popular models proposed by Chua, HP Labs, Yakopcic, TEAM, Stanford/ASU, Ielmini, Berco-Tseng, and many others have been compared and analyzed extensively on various parameters. The working and implementations of the window functions like Joglekar, Biolek, Prodromakis, etc. has been presented and compared as well. New well-defined modeling concepts have been discussed which increase the applicability and accuracy of the models. The use of these concepts brings forth several improvements in the existing models, which have been enumerated in this work. Following the template presented, highly accurate models would be developed which will vastly help future model developers and the modeling community.

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“…ESISTIVE random access memory (ReRAM) is among the most promising candidates to replace conventional nonvolatile memories for embedded applications [1], [2] owing to its high speed, high endurance, low power consumption, high scalability, and 3D integration feasibility [3]. The devices investigated in this work are 1T1R HfO 2based structures that comply with the above requirements [4]- [6] and that have been thoroughly tested for intercell variability [7], forming conditions [8] and characterized using high speed dynamical techniques [6], [9]. The operational principle of ReRAMs relies on the repetitive formation (low resistance state, LRS) and rupture (high resistance state, HRS) of a conductive pathway spanning the oxide film.…”

Section: Introductionmentioning

confidence: 99%

Switching Voltage and Time Statistics of Filamentary Conductive Paths in HfO₂-Based ReRAM Devices

Rodríguez-Fernández

Cagli

Suñé

et al. 2018

IEEE Electron Device Lett.

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Switching voltage and time statistics of HfO2-based one transistor-one resistor (1T1R) structures are investigated with the aim of clarifying the underlying physical mechanism that governs the formation and rupture of filamentary paths in the insulating layer. From the oxide reliability viewpoint, constant and ramped voltage stress experiments provide strong support to the so called E-model, which is shown to be in line with current theories relating the reversibility of the conduction states in ReRAM devices to ionic drift and ultimately to Kramers' escape rate theory. It is shown how the switching statistics can be used to estimate the width and formation energy of the insulating gap along the filament as well as its temperature.

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Endurance/Retention Trade Off in HfOx and TaOx Based RRAM

Cited by 29 publications

References 6 publications

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

A Collective Study on Modeling and Simulation of Resistive Random Access Memory

Switching Voltage and Time Statistics of Filamentary Conductive Paths in HfO₂-Based ReRAM Devices

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Endurance/Retention Trade Off in HfOx and TaOx Based RRAM

Cited by 29 publications

References 6 publications

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

Pseudo-Interface Switching of a Two-Terminal TaOx/HfO2 Synaptic Device for Neuromorphic Applications

A Collective Study on Modeling and Simulation of Resistive Random Access Memory

Switching Voltage and Time Statistics of Filamentary Conductive Paths in HfO2-Based ReRAM Devices

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Switching Voltage and Time Statistics of Filamentary Conductive Paths in HfO₂-Based ReRAM Devices