Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to variability and reliability issues, which are usually evaluated through switching endurance tests. However, we note that most studies that claimed high endurances >106 cycles were based on resistance versus cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device. We recommend not to use such a characterization method because it is highly inaccurate and unreliable (i.e., it cannot reliably demonstrate that the device effectively switches in every cycle and it ignores cycle-to-cycle and device-to-device variability). This has created a blurry vision of the real performance of RS devices and in many cases has exaggerated their potential. This article proposes and describes a method for the correct characterization of switching endurance in RS devices; this method aims to construct endurance plots showing one data point per cycle and resistive state and combine data from multiple devices. Adopting this recommended method should result in more reliable literature in the field of RS technologies, which should accelerate their integration in commercial products.

A simulation study has been performed to analyze resistive switching (RS) phenomena in valence change memories (VCM) based on a HfO2 dielectric. The kernel of the simulation tool consists of a 3D kinetic Monte Carlo (kMC) algorithm implemented self-consistently with the 3D Poisson and heat equations. These VCM devices show filamentary conduction, their RS operation is based on the destruction and regeneration of an ohmic conductive filament (CF) composed of oxygen vacancies. The physics underlying the RS operation is described by means of processes linked to generation of oxygen vacancies, oxygen ion migration and recombination between vacancies and oxygen ions that can be accurately described by using the electric field and temperature distributions in the dielectric. The studied devices consist of TiN/Ti/HfO2/W stacks where the Ti capping layer plays the role of oxygen ion getter material. The simulation tool is useful for obtaining information of internal physical variables, explaining RS dynamics and the CFs evolution from the microscopic viewpoint in terms of their size and shape under different electrical input signals; particularly, the pulsed operation regime has been studied in depth. Furthermore, interesting phenomena, such as partial SETs within overall RESET processes can be accurately reproduced.

An in-depth study of reset processes in RRAMs (Resistive Random Access Memories) based on Ni/HfO2/Si-n+ structures has been performed. To do so, we have developed a physically based simulator where both ohmic and tunneling based conduction regimes are considered along with the thermal description of the devices. The devices under study have been successfully fabricated and measured. The experimental data are correctly reproduced with the simulator for devices with a single conductive filament as well as for devices including several conductive filaments. The contribution of each conduction regime has been explained as well as the operation regimes where these ohmic and tunneling conduction processes dominate.

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A physical simulation procedure was used to describe the processes behind the operation of devices based on TiN/Ti/HfO2/W structures. The equations describing the creation and destruction of conductive filaments formed by oxygen vacancies are solved in addition to the heat equation. The resistances connected with the metal electrodes were also considered. Resistive random access memories analyzed were fabricated, and many of the characteristics of the experimental data were reproduced with accuracy. Truncated-cone shaped filaments were employed in the model developed with metallic-like transport characteristics. A hopping current was also taken into account to describe the electron transport between the filament tip and the electrode. Hopping current is an essential component in the device high resistance state.

In this work, a study of the influence of the processing conditions on the blistering of Al2O3 layers grown by atomic layer deposition (ALD) on silicon substrates is presented. The phenomenon occurs when the as-deposited layers are annealed at high temperature in a N2 atmosphere. The characterization of the blistering in terms of density and dimensions indicates that the higher the annealing temperature the higher the density but also the smaller the blister diameter, while the thicker the oxide the larger the blisters. The processing of the blistered layers to obtain Al-Al2O3-Si structures enhances the blistering phenomenon and at the same time affects the silicon surface underneath the blister. This has been evidenced by chemical etching of the deposited layers that have revealed in circular silicon voids of the size of the blister. The influence of the oxygen precursor used in the ALD process has also been investigated, showing that the blister size is reduced when using O3 instead of H2O. Finally, the use of a thin thermally grown SiO2 layer is shown to avoid blistering of Al2O3 films.

The relevance of the intrinsic series resistance effect in the context of resistive random access memory (RRAM) compact modeling is investigated. This resistance notably affects the conduction characteristic of resistive switching memories so that it becomes an essential factor to consider when fitting experimental data, especially those coming from devices exhibiting the so-called snapback and snapforward effects. A thorough description of the resistance value extraction procedure and an analysis of the connection of this value with the set and reset transition voltages in HfO 2 -based valence change memories are presented. Furthermore, in order to illustrate the importance of this feature in the shape of the I-V curve, the Stanford model for RRAM devices is enhanced by incorporating the series resistance as an additional parameter in the Verilog-A model script.

A multivariate analysis of the parameters that characterize the reset process in RRAMs has been performed. The different correlations obtained can help to shed light on the current components that contribute in the Low Resistance State (LRS) of the technology considered. In addition, a screening method for the Quantum Point Contact (QPC) current component is presented. For this purpose the second derivative of the current has been obtained using a novel numerical method which allows determining the QPC model parameters. Once the procedure is completed, a whole RS series of thousands of curves is studied by means of a genetic algorithm. The extracted QPC parameter distributions are characterized in depth to get information about the filamentary pathways associated with LRS in the low voltage conduction regime.