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

Caracterizacion y modelado de memorias RRAM basadas en estructuras metal-aislante-semiconductor y metal-aislante-metal

El objetivo de este proyecto es el estudio y posterior analisis del efec- ´ to del campo magnetico aplicado sobre dispositivos de tipo resistivo ´ RRAM, en concreto sobre estructuras metal-aislante-semiconductor y metal-aislante-metal. Los temas a tratar seran la modificaci ´ on del soft- ´ ware de medidas y analisis desde el que se parte para que incluya ´ compatibilidad de trabajo con campo magnetico y desarrollo de distin- ´ tos escenarios para la toma de medidas con campo magnetico unifor- ´ me. Finalmente se llevaran a cabo una serie de medidas precisas y se ´ trataran los resultados. El sistema contar ´ a con el software para la con- ´ figuracion del conexionado y el lanzamiento del proceso de medida ´ controlando el conjunto de la instrumentacion involucrada mediante ´ buses GPIB y RS-232. Finalmente, se concluye que los resultados mues tran que el campo magnetico aumenta los niveles de conducci ´ on de la ´ corriente en el estado de baja resistencia de manera acumulativa, es decir, en series de ciclos RS sucesivos. Ademas, la media de la corrien- ´ te en el estado de alta resistencia tambien se ve incrementada bajo los ´ efectos del campo magnetico.Universidad de Granada. Departamento de Electrónica y Tecnología de Computadores

Variability in Resistive Memories

This research was supported by project B-TIC-624-UGR20 funded by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program. F.J.A. acknowledges grant PGC2018-098860-B-I00 and PID2021-128077NB-I00 financed by MCIN/ AEI/10.13039/501100011033/FEDER and A-FQM-66-UGR20 financed by the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program. M.B.G. acknowledges the Ramón y Cajal Grant No. RYC2020-030150-I. M.L. and M.A.V. acknowl- edge generous support from the King Abdullah University of Science and Technology. A.N.M., N.V.A., A.A.D., M.N.K. and B.S. acknowledge the Government of the Russian Federation under Megagrant Program (agreement no. 074-02-2018-330 (2)) and the Ministry of Science and Higher Education of the Russian Federation under “Priority-2030” Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod (N-466-99_2021-2023). The authors thank D.O. Filatov, A.S. Novikov, and V.A. Shishmakova for their help in studying the dependence of MFPT on external voltage (Section 4). The devices in Section 4 were designed in the frame of the scientific program of the National Center for Physics and Mathematics (project “Artificial intel- ligence and big data in technical, industrial, natural and social systems”) and fabricated at the facilities of Laboratory of memristor nanoelectronics (state assignment for the creation of new laboratories for electronics industry). E.M. acknowledges the support provided by the European proj- ect 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.Resistive memories are outstanding electron devices that have displayed a large potential in a plethora of applications such as nonvolatile data storage, neuro- morphic computing, hardware cryptography, etc. Their fabrication control and performance have been notably improved in the last few years to cope with the requirements of massive industrial production. However, the most important hurdle to progress in their development is the so-called cycle-to-cycle variability, which is inherently rooted in the resistive switching mechanism behind the operational principle of these devices. In order to achieve the whole picture, variability must be assessed from different viewpoints going from the experi- mental characterization to the adequation of modeling and simulation techni- ques. Herein, special emphasis is put on the modeling part because the accurate representation of the phenomenon is critical for circuit designers. In this respect, a number of approaches are used to the date: stochastic, behavioral, meso- scopic..., each of them covering particular aspects of the electron and ion transport mechanisms occurring within the switching material. These subjects are dealt with in this review, with the aim of presenting the most recent advancements in the treatment of variability in resistive memories.Junta de Andalucía B-TIC-624-UGR20 PID2021-128077NB-I00European CommissionMCIN/AEI/FEDER A-FQM-66-UGR20 PGC2018-098860-B-I00Spanish Government RYC2020-030150-IKing Abdullah University of Science & TechnologyGovernment of the Russian Federation under Megagrant Program 074-02-2018-330 (2)Ministry of Science and Higher Education of the Russian Federation under "Priority-2030" Academic Excellence Program of the Lobachevsky State University of Nizhny Novgorod N-466-99_2021-2023European project MEMQuD 20FUN06EMPIR programmeEuropean Union's Horizon 2020 research and innovation programm

Thermal Characterization of Conductive Filaments in Unipolar Resistive Memories

A methodology to estimate the device temperature in resistive random access memories (RRAMs) is presented. Unipolar devices, which are known to be highly influenced by thermal effects in their resistive switching operation, are employed to develop the technique. A 3D RRAM simulator is used to fit experimental data and obtain the maximum and average temperatures of the conductive filaments (CFs) that are responsible for the switching behavior. It is found that the experimental CFs temperature corresponds to the maximum simulated temperatures obtained at the narrowest sections of the CFs. These temperature values can be used to improve compact models for circuit simulation purposesConsejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain)FEDER B-TIC-624-UGR20. M.B.GRamón y Cajal RYC2020-030150-

Modeling the variability of Au/ Ti/h BN/Au memris t ive devices

The variability of memristive devices using multilayer hexagonal boron nitride (h-BN) coupled with Ti and Au electrodes (i.e., Au/Ti/h-BN/Au) is analyzed in depth using different numerical techniques. We extract the reset voltage using three different methods, quantified its cycle-to-cycle variability, calculated the charge and flux that allows to minimize the effects of electric noise and the inherent stochasticity of resistive switching, described the device variability using time series analyses to assess the “memory” effect, and employed a circuit breaker simulator to understand the formation and rupture of the percolation paths that produce the switching. We conclude that the cycle-to-cycle variability of the Au/Ti/h-BN/Au devices presented here is higher than that previously observed in Au/h-BN/Au devices, and hence they may be useful for data encryption.Ministry of Science and Technology of China (2019YFE0124200, 2018YFE0100800)National Natural Science Foundation of China (61874075)Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and European Regional Development Fund (ERDF) under projects A-TIC-117-UGR18, A-FQM-66-UGR20, A-FQM-345- UGR18, B-TIC-624-UGR20 and IE2017-5414Grant PGC2018-098860-B-I00 supported by MCIU/AEI/FEDERMaria de Maeztu” Excellence Unit IMAG, reference CEX2020-001105-M, funded by MCIN/AEI/10.13039/501100011033King Abdullah University of Science and Technolog

One Cut‐Point Phase‐Type Distributions in Reliability. An Application to Resistive Random Access Memories

A new probability distribution to study lifetime data in reliability is introduced in this paper. This one is a first approach to a non‐homogeneous phase‐type distribution. It is built by considering one cut‐point in the non‐negative semi‐line of a phase‐type distribution. The density function is defined and the main measures associated, such as the reliability function, hazard rate, cumulative hazard rate and the characteristic function, are also worked out. This new class of dis‐ tributions enables us to decrease the number of parameters in the estimate when inference is con‐ sidered. Additionally, the likelihood distribution is built to estimate the model parameters by maximum likelihood. Several applications considering Resistive Random Access Memories com‐ pare the adjustment when phase type distributions and one cut‐point phase‐type distributions are considered. The developed methodology has been computationally implemented in R‐cran.This paper is partially supported by the project FQM‐307 of the Government of Andalu‐ sia (Spain), by the project PID2020‐113961GB‐I00 of the Spanish Ministry of Science and Innovation (also supported by the European Regional Development Fund program, ERDF) and by the project PPJIB2020‐01 of the University of Granada. Additionally, the first and second authors acknowledge financial support by the IMAG–María de Maeztu grant CEX2020‐001105‐M/AEI/10.13039/501100011033. They also acknowledge the financial support of the Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER programme for projects A.TIC.117.UGR18, IE2017‐5414, B.TIC.624.UGR20 and A‐FQM‐66‐UGR20

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

Holistic Variability Analysis in Resistive Switching Memories Using a Two-Dimensional Variability Coefficient

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acsami.2c22617We present a new methodology to quantify the variability of resistive switching memories. Instead of statistically analyzing few data points extracted from current versus voltage (I− V) plots, such as switching voltages or state resistances, we take into account the whole I−V curve measured in each RS cycle. This means going from a one-dimensional data set to a two-dimensional data set, in which every point of each I−V curve measured is included in the variability calculation. We introduce a new coefficient (named two-dimensional variability coefficient, 2DVC) that reveals additional variability information to which traditional one-dimensional analytical methods (such as the coefficient of variation) are blind. This novel approach provides a holistic variability metric for a better understanding of the functioning of resistive switching memoriesConsejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain)FEDER: B-TIC-624-UGR20, PID2020-113961GB-I00, A-FQM-66-UGR20, FQM-307IMAG María de Maeztu CEX2020-001105-M/AEI/10.13039/501100011033King Abdullah University of Science and Technolog

TiN/Ti/HfO2/TiN memristive devices for neuromorphic computing: from synaptic plasticity to stochastic resonance

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fnins.2023. 1271956/full#supplementary-materialFunding The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The authors thank the support of the Consejeria de Conocimiento, Investigacion y Universidad, Junta de Andalucia (Spain), and the FEDER program through project B-TIC-624-UGR20. They also thank the support of the Federal Ministry of Education and Research of Germany under Grant 16ME0092.We characterize TiN/Ti/HfO2/TiN memristive devices for neuromorphic computing. We analyze different features that allow the devices to mimic biological synapses and present the models to reproduce analytically some of the data measured. In particular, we have measured the spike timing dependent plasticity behavior in our devices and later on we have modeled it. The spike timing dependent plasticity model was implemented as the learning rule of a spiking neural network that was trained to recognize the MNIST dataset. Variability is implemented and its influence on the network recognition accuracy is considered accounting for the number of neurons in the network and the number of training epochs. Finally, stochastic resonance is studied as another synaptic feature. It is shown that this effect is important and greatly depends on the noise statistical characteristics.Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain), and the FEDER program through project B-TIC-624-UGR20Federal Ministry of Education and Research of Germany under Grant 16ME009

Parameter extraction techniques for the analysis and modeling of resistive memories

A revision of the different numerical techniques employed to extract resistive switching (RS) and modeling parameters is presented. The set and reset voltages, commonly used for variability estimation, are calculated for different resistive memory technologies. The methodologies to extract the series resistance and the parameters linked to the charge-flux memristive modeling approach are also described. It is found that the obtained cycle-to-cycle (C2C) variability depends on the numerical technique used. This result is important, and it implies that when analyzing C2C variability, the extraction technique should be described to perform fair comparisons between different resistive memory technologies. In addition to the use of extensive experimental data for different types of resistive memories, we have also included kinetic Monte Carlo (kMC) simulations to study the formation and rupture events of the percolation paths that constitute the conductive filaments (CF) that allow resistive switching operation in filamentary unipolar and bipolar devices.Consejería de Conocimiento, Investigaci ́on y Universidad, Junta de Andalucía (Spain) and the FEDER program for the projects A.TIC.117.UGR18, B-TIC-624-UGR20 and IE2017-5414Ramón y Cajal grant No. RYC2020-030150-IFunding for open access charge: Universidad de Granada/CBU