Advanced physical modeling of SiOx resistive random access memories

We apply a three-dimensional (3D) physical simulator, coupling self-consistently stochastic kinetic Monte Carlo descriptions of ion and electron transport, to investigate switching in silicon-rich silica (SiOx) redox-based resistive random-access memory (RRAM) devices. We explain the intrinsic nature of resistance switching of the SiOx layer, and demonstrate the impact of self-heating effects and the initial vacancy distributions on switching. We also highlight the necessity of using 3D physical modelling to predict correctly the switching behavior. The simulation framework is useful for exploring the little-known physics of SiOx RRAMs and RRAM devices in general. This proves useful in achieving efficient device and circuit designs, in terms of performance, variability and reliability

Physical Simulation of Si-Based Resistive Random-Access Memory Devices

We present a newly-developed three-dimensional (3D) physical simulator suitable for the study of resistive random-access memory (RRAM) devices. We explore the switching behavior of Si-rich silica (SiOx) RRAM structures, whose operation has been successfully demonstrated experimentally at ambient conditions [1]. The simulator couples self-consistently a simulation of oxygen ion and electron transport to a self-heating model and the `atomistic' simulator GARAND. The electro-thermal simulation model provides many advantages compared to the classical phenomenological models based on the resistor breaker network. The simulator is validated with respect to experimental data and captures successfully the memristive behavior of the simulated SiOx RRAMs, by reconstructing the conductive filament formation and destruction phenomena in the 3D space. The simulation framework is useful for exploring the little-known physics of SiOx RRAMs, and providing efficient designs, in terms of performance, variability and reliability, for both memory devices and circuits

Investigation of resistance switching in SiOx RRAM cells using a 3D multi-scale kinetic Monte Carlo simulator

We employ an advanced three-dimensional (3D) electro-thermal simulator to explore the physics and potential of oxide-based resistive random-access memory (RRAM) cells. The physical simulation model has been developed recently, and couples a kinetic Monte Carlo study of electron and ionic transport to the self-heating phenomenon while accounting carefully for the physics of vacancy generation and recombination, and trapping mechanisms. The simulation framework successfully captures resistance switching, including the electroforming, set and reset processes, by modeling the dynamics of conductive filaments in the 3D space. This work focuses on the promising yet less studied RRAM structures based on silicon-rich silica (SiOx) RRAMs. We explain the intrinsic nature of resistance switching of the SiOx layer, analyze the effect of self-heating on device performance, highlight the role of the initial vacancy distributions acting as precursors for switching, and also stress the importance of using 3D physics-based models to capture accurately the switching processes. The simulation work is backed by experimental studies. The simulator is useful for improving our understanding of the little-known physics of SiOx resistive memory devices, as well as other oxide-based RRAM systems (e.g. transition metal oxide RRAMs), offering design and optimization capabilities with regard to the reliability and variability of memory cells

A thorough investigation of the switching dynamics of TiN/Ti/10 nm-HfO2/W resistive memories

Producción CientíficaThe switching dynamics of TiN/Ti/HfO2/W-based resistive memories is investigated. The analysis consisted in the systematic application of voltage sweeps with different ramp rates and temperatures. The obtained results give clear insight into the role played by transient and thermal effects on the device operation. Both kinetic Monte Carlo simulations and a compact modeling approach based on the Dynamic Memdiode Model are considered in this work with the aim of assessing, in terms of their respective scopes, the nature of the physical processes that characterize the formation and rupture of the filamentary conducting channel spanning the oxide film. As a result of this study, a better understanding of the different facets of the resistive switching dynamics is achieved. It is shown that the temperature and, mainly, the applied electric field, control the switching mechanism of our devices. The Dynamic Memdiode Model, being a behavioral analytic approach, is shown to be particularly suitable for reproducing the conduction characteristics of our devices using a single set of parameters for the different operation regimes.Ministerio de Ciencia e Innovación de España - FEDER [PID2022-139586NB-C41, PID2022-139586NB-C42, PID2022-139586NB-C43, PID2022-139586NB-C44]Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía [B-TIC-624-UGR20]Consejo Superior de Investigaciones Científicas (CSIC)- FEDER [20225AT012]Ramón y Cajal grant number RYC2020-030150-IEuropean project MEMQuD (code 20FUN06) which has received funding from the EMPIR programme co-financed by the Participating States and from the European Union's Horizon 2020 research and innovation programme

A thorough investigation of the switching dynamics of TiN/Ti/10 nm-HfO2/W resistive memories

The switching dynamics of TiN/Ti/HfO2/W-based resistive memories is investigated. The analysis consisted in the systematic application of voltage sweeps with different ramp rates and temperatures. The obtained results give clear insight into the role played by transient and thermal effects on the device operation. Both kinetic Monte Carlo simulations and a compact modeling approach based on the Dynamic Memdiode Model are considered in this work with the aim of assessing, in terms of their respective scopes, the nature of the physical processes that characterize the formation and rupture of the filamentary conducting channel spanning the oxide film. As a result of this study, a better understanding of the different facets of the resistive switching dynamics is achieved. It is shown that the temperature and, mainly, the applied electric field, control the switching mechanism of our devices. The Dynamic Memdiode Model, being a behavioral analytic approach, is shown to be particularly suitable for reproducing the conduction characteristics of our devices using a single set of parameters for the different operation regimesFEDER program [PID2022-139586NB-C41, PID2022- 139586NB-C42PID2022-139586NB-C43PID2022-139586NB-C44]The Consejería de Conocimiento, Investigaci´on y UniversidadJunta de Andalucía (Spain) [B-TIC-624-UGR20]Spanish Consejo Superior de Investigaciones Científicas (CSIC) [20225AT012]FEDER fundsRamón y Cajal grant number RYC2020-030150-IEuropean project MEMQuD, code 20FUN06EMPIR programme co-financed by the Participating StatesEuropean Union’s Horizon 2020 research and innovation programm

Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective

Acknowledgments The authors thank the support of the Spanish Ministry of Science, Innovation and Universities and the FEDER program through projects TEC2017-84321-C4-1-R, TEC2017-84321-C4-3-R, and projects A.TIC.117.UGR18, IE2017-5414 and B.TIC.624.UGR20 funded by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program. Funding for open access charge: Universidad de Granada/CBUAWe have analyzed variability in resistive memories (Resistive Random Access Memories, RRAMs) making use of advanced numerical techniques to process experimental measurements and simulations based on the kinetic Monte Carlo technique. The devices employed in the study were fabricated using the TiN/Ti/HfO2/W stack. The switching parameters were obtained making use of new developed extraction methods. The appropriateness of the advanced parameter extraction methodologies has been checked by comparison to kinetic Monte Carlo simulations; in particular, the reset and set events have been studied and detected. The data obtained were employed to shed light on the resistive switching operation and the cycle-to-cycle variability. It has been shown that variability depends on the numerical technique employed to obtain the set and reset voltages, therefore, this issue must be taken into consideration in RS characterization and modeling studies. The proposed techniques are complementary and depending on the technology and the curves shape the features of a particular method could make it to be the most appropriate.Spanish Ministry of Science, Innovation and Universities and the FEDER program through projects TEC2017-84321-C4-1-R, TEC2017-84321-C4-3-RConsejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program, projects A.TIC.117.UGR18, IE2017-5414 and B.TIC.624.UGR20Funding for open access charge: Universidad de Granada/CBU

Self-consistent physical modeling of SiOx-based RRAM structures

We apply a unique three-dimensional (3D) physics-based atomistic simulator to study silicon-rich (SiOx, x<;2) resistive switching nonvolatile memory (RRAM) devices. We couple self-consistently a simulation of ion and electron transport to the `atomistic' simulator GARAND and a self-heating model to explore the switching processes in these structures. The simulation model is more advanced than other available phenomenological models based on the resistor breaker network. The simulator is calibrated with experimental data, and reconstructs accurately the formation and rupture of the conductive filament in the 3D space. We demonstrate how the simulator is useful for exploring the little-known physics of these promising devices, and show that switching is an intrinsic property of the SiOx layer. In general, the simulation framework is useful for providing efficient designs, in terms of performance, variability and reliability, for memory devices and circuits. The simulator validity is not limited to SiOx-based devices, and can be used to study other promising RRAM systems based, e.g., on transition metal oxides

An experimental and simulation study of the role of thermal effects on variability in TiN/Ti/HfO2/W resistive switching nonlinear devices

An in-depth simulation and experimental study has been performed to analyze thermal effects on the variability of resistive memories. Kinetic Monte Carlo (kMC) simulations, that reproduce well the nonlinearity and stochasticity of resistive switching devices, have been employed to explain the experimental results. The series resistance and the transition voltages and currents have been extracted from devices based on the TiN/Ti/HfO2/W stack we have fabricated and measured at temperatures ranging from 77 K to 350 K. We observed that the variability for all the magnitudes analyzed was much higher at low temperatures. In the kMC simulations, we obtained conductive filaments (CFs) with less compactness at low temperatures. This led us to explain the higher variability, based on the variations of the CF morphology and density seen at low temperatures

Physics-based modeling approaches of resistive switching devices for memory and in-memory computing applications

The semiconductor industry is currently challenged by the emergence of Internet of Things, Big data, and deep-learning techniques to enable object recognition and inference in portable computers. These revolutions demand new technologies for memory and computation going beyond the standard CMOS-based platform. In this scenario, resistive switching memory (RRAM) is extremely promising in the frame of storage technology, memory devices, and in-memory computing circuits, such as memristive logic or neuromorphic machines. To serve as enabling technology for these new fields, however, there is still a lack of industrial tools to predict the device behavior under certain operation schemes and to allow for optimization of the device properties based on materials and stack engineering. This work provides an overview of modeling approaches for RRAM simulation, at the level of technology computer aided design and high-level compact models for circuit simulations. Finite element method modeling, kinetic Monte Carlo models, and physics-based analytical models will be reviewed. The adaptation of modeling schemes to various RRAM concepts, such as filamentary switching and interface switching, will be discussed. Finally, application cases of compact modeling to simulate simple RRAM circuits for computing will be shown

Recommended Methods to Study Resistive Switching Devices

Resistive switching (RS) is an interesting property shown by some materials systems that, especially during the last decade, has gained a lot of interest for the fabrication of electronic devices, with electronic nonvolatile memories being those that have received the most attention. The presence and quality of the RS phenomenon in a materials system can be studied using different prototype cells, performing different experiments, displaying different figures of merit, and developing different computational analyses. Therefore, the real usefulness and impact of the findings presented in each study for the RS technology will be also different. This manuscript describes the most recommendable methodologies for the fabrication, characterization, and simulation of RS devices, as well as the proper methods to display the data obtained. The idea is to help the scientific community to evaluate the real usefulness and impact of an RS study for the development of RS technology. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinhei