A spectre is haunting the globe—the spectre of a revolution in electronic devices. The inevitability of this revolution is dictated by the emergence of new paradigms of electronics, such as neuromorphic computing, which cannot be implemented on existing hardware. One of the key enablers of the new paradigms is the memristor (resistor with memory). The latter is often based on the electrical resistive switching (RS) phenomenon. However, the memristive systems include also capacitive and inductive elements, namely, capacitors and inductors whose properties depend on the state and history of the system. Besides the classical resistive memories, quantum effects may open up new horizons for the implementation of new information storage and processing capabilities, e.g., in superconducting quantum circuits, quantum photonic devices, or using tunnelling and exciton-polariton interaction processes. The respective devices may find application in neuromorphic systems to simulate learning, adaptive, and spontaneous behavior. The symposium “Resistive switching: physics, devices and applications” held in the framework of the 16th International Conference on Nanostructured Materials (NANO 2022, 6–10 June 2022, Seville, Spain) was dedicated to all aspects of resistive switching from theory and modelling through novel materials to circuit elements and system design. The program of the symposium comprised a total of 10 invited and 33 oral talks, as well as 14 poster presentations. The presenters came from 16 countries located on 4 continents: Asia, Europe, and North and South America. Seven presentations have been selected for publication in a dedicated Special Section of physica status solidi (a). Maldonado et al. (article no. 2200520) address the most important hurdle to progress in the development of resistive memories which is the so-called cycle-to-cycle variability which is inherently rooted in the resistive switching mechanism behind the operational principle of these devices. To achieve the whole picture, variability must be assessed from different viewpoints going from the experimental characterization to the adequation of modelling and simulation techniques. The authors show how this variability can be extracted and analyzed for such main parameters of resistive switching as the SET and RESET voltages/currents and how it depends on the methodology used and experimental conditions. The following three papers treat the modelling and simulation of memristive structures. Busygin et al. (article no. 2200478) developed a one-dimensional mathematical model of memristor switching that includes a full physical model of steady-state heat and mass transfer processes. The model considers ions and vacancies generation, recombination and drift in an electric field in the metal-oxide-metal structure with a dominant charge transport mechanism of electron tunnel hopping through vacancies. Catarina Dias and João Ventura (article no. 2200730) applied numerical modelling to study the influence of metal oxide layer thickness and defects on resistive switching behavior. The Random Circuit Breaker model was implemented and the dependence of the forming, set and reset voltages on the oxide thickness and defect percentage was compared with experimental data. Sparvoli et al. (article no. 2200591) simulated the behavior of neuronal membranes based on graphene oxide memristors and validated the operation of an RC circuit as a possible tool for the analysis of memristor devices. The important effect of training pulse parameters on the synaptic plasticity of a ZrO2(Y)-based memristive device was investigated by Koryazhkina et al. (article no. 2200742). The observed result was explained in terms of the work required to change the resistive state. Moreover, the ZrO2(Y)-based memristive device under study exhibited distinguishable potentiation and depression for at least 1000 cycles. The last two articles describe memristors based on unusual materials. The Pershin group (article no. 2200643) took advantage of the fact that when a drop of Glenlivet whisky evaporates, it leaves behind a uniform deposit. The authors utilized this finding in the fabrication of electrochemical metallization memory (ECM) cells. The top (Ag) and bottom (Co) electrodes were separated by a layer of Glenlivet whisky deposit (an insulator). The device response was typical of ECM cells that involve threshold-type switching, pinched hysteresis loops, and a large difference between the high- and low-resistance states. The surface coating process results in a biodegradable insulating layer, which may facilitate the recovery of recyclable materials at the end of the device's use. And, last but not least, Prudnikov et al. (article no. 2200700) introduce polyaniline-based organic memristive devices with volatile resistive switching and complex temporal behavior, which are capable of processing 4-bit sequences of data with reliable separation of states. Thanks to this ability, such devices could be a valuable element for the realization of a reservoir computing system for the classification of handwritten digits from the MNIST dataset. The proposed model suggests that the electrical properties of the polyaniline-based organic memristive devices ensure the realization of a system able to correctly classify handwritten digits and to be tolerant to considerable overlapping of neighboring reservoir states. The Symposium was a very exciting and fruitful event, a forum for reporting and discussing new findings, exchanging new ideas, and inspiring new concepts and designs. I hope that the present article collection will provide the reader with insights at least into some rapidly developing areas of RS physics and applications. Wiley-VCH is greatly acknowledged for kindly arranging the symposium publication. Nikolai A. Sobolev The Guest Editor