Theory and Technology of Memristive Devices

Abstract

CMOS scaling is progressively and inevitably approaching atomic boundaries. The industry is thus exploring the potential of novel disruptive nanotechnologies, based on multifunctional materials, which may allow the development of integrated circuits keeping the trend predicted by Moore in 1965 in the years to come, despite further transistor shrinking being no longer possible. Memristors, originally postulated only theoretically out of a brilliant line of thought by Chua in 1971 and identified at the nanoscale almost 40 years later, back in 2008, by a team of engineers supervised by R.S. Williams at Hewlett Packard Labs, represent the key nanotechnology of the future, enabling novel forms of computation, which are closer to the principles underlying the functionalities of the human brain, given the extraordinarily peculiar capability of these devices to sense, store, and process data in the same physical miniaturized volume. Achieving progress in memristor circuit design crucially calls for the development of synergies among researchers with different academic backgrounds. In fact, only combining the technical knowledge, acquired by memristor theoreticians, with the practical know‐how of experimenters will enable to foster progress in memristor circuit and system development in the near future. In line with this necessity, the present article is the fruit of a joint cooperation between two leading memristor research units from Germany, one based at TU Dresden, which has contributed to establish solid theoretical foundations on resistance switching memories and their circuits since 2008, and the other one based at RWTH Aachen University, which has been the leading experimental research unit on nanostructures of this kind over the same time span. This article first presents a comprehensive overview of the theory of memristors, starting off from the early achievements in the pioneering studies of their father Chua, then classifies and analyses in depth the main physical mechanisms underlying the inherently nonlinear behavior of their physical realizations, and, finally, discusses their most promising applications, from the development of new nonvolatile memories based on resistance switching phenomena to the realization of novel neuromorphic circuits, capable to mimic the complex dynamics of biological entities closer than conventional purely CMOS hardware, without leaving aside an excursus on the potential to leverage the unique features of these devices for the circuit implementation of unconventional brain‐inspired time‐ and energy‐efficient sensing and memcomputing strategies, which is a great appeal for the realization of portable light‐weight technical systems for the Internet‐of‐Things industry, especially but not only to the benefit of healthcare, well‐being, and automotive market sectors.