Litcius/Paper detail

Filament-free memristors for computing

Sanghyeon Choi, Taehwan Moon, Gunuk Wang, J. Joshua Yang

2023Nano Convergence28 citationsDOIOpen Access PDF

Abstract

Memristors have attracted increasing attention due to their tremendous potential to accelerate data-centric computing systems. The dynamic reconfiguration of memristive devices in response to external electrical stimuli can provide highly desirable novel functionalities for computing applications when compared with conventional complementary-metal-oxide-semiconductor (CMOS)-based devices. Those most intensively studied and extensively reviewed memristors in the literature so far have been filamentary type memristors, which typically exhibit a relatively large variability from device to device and from switching cycle to cycle. On the other hand, filament-free switching memristors have shown a better uniformity and attractive dynamical properties, which can enable a variety of new computing paradigms but have rarely been reviewed. In this article, a wide range of filament-free switching memristors and their corresponding computing applications are reviewed. Various junction structures, switching properties, and switching principles of filament-free memristors are surveyed and discussed. Furthermore, we introduce recent advances in different computing schemes and their demonstrations based on non-filamentary memristors. This Review aims to present valuable insights and guidelines regarding the key computational primitives and implementations enabled by these filament-free switching memristors.

Topics & Concepts

MemristorControl reconfigurationComputer scienceResistive random-access memoryNeuromorphic engineeringProtein filamentNanotechnologyCMOSElectronic engineeringMaterials scienceElectrical engineeringEmbedded systemEngineeringArtificial intelligenceArtificial neural networkVoltageComposite materialAdvanced Memory and Neural ComputingFerroelectric and Negative Capacitance DevicesPhotoreceptor and optogenetics research