Binary metal oxide-based resistive switching memory devices: A status review

Patil, Arun; Dongale, Tukaram D.; Kamat, Rajanish K.; Rajpure, K.Y.

doi:10.1016/j.mtcomm.2023.105356

Cited by 26 publications

(28 citation statements)

References 365 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Set voltage value is ∼0.5 V and reset voltage value is ∼−0.8 V. A wide range of set and reset voltages are found in the literature ranging from 0.22 to 3.5 V [24]. The I ON /I OFF ratio is one order of magnitude, although resistance window values of more than 10 3 can be found in the literature for HfO 2based devices [25].…”

Section: Resultsmentioning

confidence: 99%

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices

García

Vinuesa

García-Ochoa

et al. 2023

J. Phys. D: Appl. Phys.

View full text Add to dashboard Cite

Memristive devices have shown a great potential for non-volatile memory circuits and neuromorphic computing. For both applications it is essential to know the physical mechanisms behind resistive switching; in particular, the time response to external voltage signals. To shed light in these issues we have studied the role played by the applied voltage ramp rate in the electrical properties of TiN/Ti/HfO2/W metal-insulator-metal resistive switching devices. Using an ad hoc experimental set-up, the current-voltage characteristics were measured for ramp rates ranging from 100 mV/s to 1MV/s. These measurements were used to investigate in detail the set and reset transitions. It is shown that the highest ramp rates allow controlling the resistance values corresponding to the intermediate states at the very beginning of the reset process, which is not possible by means of standard quasistatic techniques. Both the set and reset voltages increase with the ramp rate because the oxygen vacancies movement is frequency dependent so that, when the ramp rate is high enough, the conductive filaments neither fully form nor dissolve. In agreement with Chua’s theory of memristive devices, this effect causes the device resistance window to decrease as the ramp rate increases, and even to vanish for very high ramp rates. Remarkably, we demonstrate that the voltage ramp rate can be straightforwardly used to control the conductance change of the switching devices, which opens up a new way to program the synaptic weights when using these devices to mimic synapses for neuromorphic engineering applications. Moreover, the data obtained have been compared with the predictions of the dynamic memdiode model.

show abstract

Section: Resultsmentioning

confidence: 99%

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices

García

Vinuesa

García-Ochoa

et al. 2023

J. Phys. D: Appl. Phys.

View full text Add to dashboard Cite

show abstract

“…[162] When a stimulus voltage is administered to the Ta 2 O 5 RSM layer in an initial low conductance state, oxygen vacancies are created, generating a contrast difference in the dielectric layer. [163][164][165] The Ta 2 O 5 layer functions as an oxygen provisioner as well as a reservoir, [166,167] with a specified region around the top electrode and the bottom electrode increasing with an increase in voltage. [163,168] The specified regions connect to generate the conductive filament.…”

Section: Anion-based Switchingmentioning

confidence: 99%

“…This phenomenon occurs frequently in metal oxide layers, viz., ZnO, SiO 2 , ZrO 2 , and HfO 2 . [167,[182][183][184][185] Moreover, recent studies have demonstrated the growth of the conductive filament in the ZnO layer from the top electrode to the bottom electrode. [186,187]…”

Section: Cation-based Transitionmentioning

confidence: 99%

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Go,

Lim,

Lee

et al. 2024

Small Science

View full text Add to dashboard Cite

Separate memory and processing units are utilized in conventional von Neumann computational architectures. However, regarding the energy and the time, it is costly to shuffle data between the memory and the processing entity, and for data‐intensive applications associated with artificial intelligence, the demand is ever increasing. A paradigm shift in traditional architectures is required, and in‐memory computing is one of the non‐von‐Neumann computing strategies. By harnessing physical signatures of the memory, computing workloads are administered in the same memory element. For in‐memory computing, a wide range of memristive material (MM) systems have been examined. Moreover, developing computing schemes that perform in the same sensory network and that minimize the data shuffle between the processing unit and the sensing element is a requirement, to process large volumes of data efficiently and decrease the energy consumption. In this review, an overview of the switching character and system signature harnessed in three archetypal MM systems is rendered, along with an integrated application survey for developing in‐sensor and in‐memory computing, viz., brain‐inspired or analogue computing, physical unclonable functions, and random number generators. The recent progress in theoretical studies that reveal the structural origin of the fast‐switching ability of the MM system is further summarized.

show abstract

“…Metal oxides such as TiO x , [8,9,[40][41][42] NiO x , [32,[43][44][45][46] HfO 2 , [19,29,42] TaO x , [20,47,48] AlO x , [10,49] ZrO 2 , [15][16][17] ZnO x , [11,31,50] CuO, [6,51,52] SiO x , [18,34,53] and others are frequently used as materials for constructing the resistive layer due to their simple structure, larger bandgap, and better compatibility with the CMOS process. [54,55] At the same time, nitride such as AlN, [56,57] ZrN, [58] NiN, [59] and organic materials like Alq 3 [60] exhibit similar RS mechanisms to metal oxides, making them viable options for resistive materials. It is also important to note that metal ions exhibit higher solubility and diffusion coefficient in sulfide materials, such as As 2 S 3 , [61] Ag 2 S, [62] GeTe, [63] Cu 2 S, [64] GeS, [65] Ag-Ge-Se.…”

Section: Resistive Layer Materialsmentioning

confidence: 99%

Resistive Mechanisms and Microscopic Electrical Models of Metal Oxide Resistive Memory

Pan,

He,

et al. 2023

Physica Status Solidi (a)

View full text Add to dashboard Cite

Resistive random access memory (RRAM) has emerged as a competitive candidate for non‐volatile memory due to its high speed, low power consumption, simple structure, strong scalability and CMOS compatibility. In this paper, an overview of the electrodes and resistive layers is first discussed according to the material properties and structure of RRAM. Then, recent advances in the resistive mechanisms of RRAM are comprehensively discussed and evaluated based on experimental research results and fundamental physics principles. Then, the electrochemical metallization mechanism and the valence change metallization mechanism are thoroughly studied, as well as the formation, fracture and resistance state change behavior of conductive filaments in RRAM based on the ion motion type. Then, various electron transport‐dominated resistance mechanisms are reviewed, and electron transport and resistance switching in the space‐charge‐limited current mode are thoroughly examined using energy band theory. As a result, a theoretical reference is provided for the development of nano‐thin film devices.This article is protected by copyright. All rights reserved.

show abstract

Binary metal oxide-based resistive switching memory devices: A status review

Cited by 26 publications

References 365 publications

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Resistive Mechanisms and Microscopic Electrical Models of Metal Oxide Resistive Memory

Contact Info

Product

Resources

About

Binary metal oxide-based resistive switching memory devices: A status review

Cited by 26 publications

References 365 publications

Effects of the voltage ramp rate on the conduction characteristics of HfO2-based resistive switching devices

Effects of the voltage ramp rate on the conduction characteristics of HfO2-based resistive switching devices

Nonvolatile Memristive Materials and Physical Modeling for In‐Memory and In‐Sensor Computing

Resistive Mechanisms and Microscopic Electrical Models of Metal Oxide Resistive Memory

Contact Info

Product

Resources

About

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices

Effects of the voltage ramp rate on the conduction characteristics of HfO₂-based resistive switching devices