Dear Colleagues,

Resistive memories (also known as resistive random-access memories, RRAM) are outstanding electron devices that are being scrutinized both by academia and industry for their great potential in different applications in the electronics realm. They are a subgroup of a large family of devices known as memristors. In general, they are made of a simple structure formed by two electrodes (metal or semiconductors) with a dielectric in between (different materials have been employed for this, such as transition metal oxides, 2D material-based dielectric such as h-BN, multilayer stacks, etc.). Their conductance can be easily changed in a non-volatile manner, and their operation is known as resistive switching. The simplicity and stackability of these structures, their good endurance, reliability, and compatibility with the standard electronic technology make these devices attractive and promising in the semiconductor industry landscape. They have been used for the implementation of storage-class memories, but in this application facet, there is still a long way to go. Another application that shows a great future is linked to neuromorphic circuits. In this case, these resistive switching devices can be used to mimic biological synapses. Neuromorphic computing can step forward with circuits based on resistive switching devices due to their low power operation and their versatility to play the role of artificial synapses. In this manner, von Neumann bottlenecks could be overcome in computing solutions related to artificial intelligence. Finally, applications devoted to cryptography and the implementation of physical unclonable functions are of great interest due to the intrinsic stochastic nature of RRAM operation.

Resistive memories are key devices in this Special Issue where the most representative features of this technology will be tackled from different perspectives. Therefore, the scope will range from materials and device processing technologies to circuit and applications. We will pay special attention to simulations, including all the different approaches that can be employed to describe device physics and internal variables. In addition, compact modeling will be addressed, along with advanced electrical characterization methodologies and reliability studies. A detailed description of the topics is given below:

Topic list

• Fabrication of resistive switching materials, devices, and advanced material characterization
• Electrical characterization techniques and reliability for resistive memories
• Multilevel operation algorithms
• Resistive memories physical simulation (kinetic Monte Carlo, Ab initio approach, macroscopic description, etc.)
• Resistive memory compact modeling (kinetic, thermal, noise modeling; Verilog-A implementation, modules for SPICE based circuit simulation, etc.)
• Memristor modeling approach (current versus voltage, charge versus flux, first and second order memristors, etc.)
• Emerging device applications: neuromorphic devices and circuits, hardware security, digital logic circuits, etc.

Prof. Dr. Juan B. Roldán Aranda
Prof. Dr. Francisco Jiménez-Molinos
Dr. Mireia Bargalló Gonzalez
Guest Editors

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