Resistive Random Access Memories (RRAMs) are based on resistive switching (RS) operation and exhibit a set of technological features that make them ideal candidates for applications related to non-volatile memories, neuromorphic computing and hardware cryptography. For the full industrial development of these devices different simulation tools and compact models are needed in order to allow computer-aided design, both at the device and circuit levels. Most of the different RRAM models presented so far in the literature deal with temperature effects since the physical mechanisms behind RS are thermally activated; therefore, an exhaustive description of these effects is essential. As far as we know, no revision papers on thermal models have been published yet; and that is why we deal with this issue here. Using the heat equation as the starting point, we describe the details of its numerical solution for a conventional RRAM structure and, later on, present models of different complexity to integrate thermal effects in complete compact models that account for the kinetics of the chemical reactions behind resistive switching and the current calculation. In particular, we have accounted for different conductive filament geometries, operation regimes, filament lateral heat losses, the use of several temperatures to characterize each conductive filament, among other issues. A 3D numerical solution of the heat equation within a complete RRAM simulator was also taken into account. A general memristor model is also formulated accounting for temperature as one of the state variables to describe electron device operation. In addition, to widen the view from different perspectives, we deal with a thermal model contextualized within the quantum point contact formalism. In this manner, the temperature can be accounted for the description of quantum effects in the RRAM charge transport mechanisms. Finally, the thermometry of conducting filaments and the corresponding models considering different dielectric materials are tackled in depth.

A new model for bipolar resistive random-access memories (RRAMs) is presented in this article. Redox and diffusion processes are used to describe in detail the physics behind the filamentary resistive switching (RS) mechanisms of the RRAMs under study. The model includes truncated-cone shaped filaments which are known to be close to the real conductive filament (CF) geometry and a detailed thermal approach, where two temperatures are considered to describe the rupture process at the CF’s narrowest part and also the main CF body’s electrical conductivity variations. Ti/ZrO ₂ /Pt RRAM devices have been fabricated and measured, and the model has allowed us to reproduce the experimental data for all the cases analyzed. Finally, the model has been implemented in Verilog-A code within the ADS circuit simulator, and the response of a device to pulsed external voltages within a characterization circuit has been simulated, producing good results when compared with experimental measurements.

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.

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 HfO₂-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.