Special issue on ‘Advances in Memristive Networks’

The existence of the fourth fundamental circuit element, the ‘memristor’, was postulated by Chua in 1971 [1]. Chua mathematically explored the properties of this new nonlinear circuit element and found that it was essentially a resistor with memory, so he called it memristor. The memristor is a two-terminal circuit element characterised by a nonlinear relation between the time integrals of the current and the voltage applied to its terminals. However, nowadays the term memristor may refer to any resistive switching device that complies with a set of certain properties known as fingerprints of memristors [2]. Unprecedented attention on this device technology has been drawn ever since 2008 and the first demonstration of the well-known TiO 2 -based memristor by a team of Hewlett Packard researchers led by Williams [3], who managed to connect the nature of such devices with Chua’s 1971 theory (although the hysteretic resistive switching property of oxides sandwiched between metal electrodes had been noticed during the ’60s [4]). The HP Labs invention in 2008 was soon followed by the identification of additional material compounds which can be the basis of memristor devices and a wide variety of such materials are being studied. Memristor nanodevices typically adopt a metal–insulator–metal structure and the electrode materials with the switching layer are carefully selected and designed so as to obtain the desirable characteristics. The choice of materials is truly dependent on the application, as clearly some features of specific memristive compounds may be beneficial in some context and disadvantageous otherwise. It is worth noting though that, while this technology is continuously maturing, the first commercially available devices were released recently by Knowm Inc. [5], who provided affordable access to memristors, bringing this technology closer to scientists, researchers, and enthusiasts that might not have access to fabrication facilities. Owing to their plasticity, analog nature, and nonvolatility, memristors constitute an emerging trend in modern electronics, representing a promising technology with an ever growing variety of potential applications including multi-level memory, adaptive and learning circuits and systems, sensing, as well as logic and unconventional computing. Most importantly, in the era of ‘big data’, memristors embedded in novel nanoelectronic platforms constitute perhaps the most promising key-enabling technology for the storage and processing of massive amounts of data. The memristor provides an unconventional computing framework, ideally combining resistance-based information storage and processing in a single device. Moreover, such devices may occupy nanoscale volumes and be arranged in multi-layer highly dense crossbar arrays, ideally suited for massively parallel analog processing, while taking advantage of the programmable conductance, reminiscent of the neural synaptic weights. In this context, networks of memristors working in a parallel/collective manner, received a lot of attention from researchers in the last few years. Several works have been published in the literature, especially concerning the design, fabrication, modelling and implementation of computation in spatially extended discrete media with many memristors [6,7]. This Special Issue on ‘Advances in Memristive Networks’ is particularly devoted to present the most recent results as well as key aspects and perspectives of on-going research on relevant topics, all of them involving large networks of memristor devices used in diverse applications. More specifically, this special issue is composed of five papers, thoroughly reviewed and meticulously revised, making a volume of about one hundred pages.