Challenges in materials and devices for resistive-switching-based neuromorphic computing

Abstract

This tutorial describes challenges and possible avenues for the implementation of the components of a solid-state system, which emulates a biological brain. The tutorial is devoted mostly to a charge-based (i.e. electric controlled) implementation using transition metal oxides materials, which exhibit unique properties that emulate key functionalities needed for this application. In the Introduction, we compare the main differences between a conventional computational machine, based on the Turing-von Neumann paradigm, to a Neuromorphic machine, which tries to emulate important functionalities of a biological brain. We also describe the main electrical properties of biological systems, which would be useful to implement in a charge-based system. In Chapter II, we describe the main components of a possible solid-state implementation. In Chapter III, we describe a variety of Resistive Switching phenomena, which may serve as the functional basis for the implementation of key devices for Neuromorphic computing. In Chapter IV we describe why transition metal oxides, are promising materials for future Neuromorphic machines. Theoretical models describing different resistive switching mechanisms are discussed in Chapter V while existing implementations are described in Chapter VI. Chapter VII presents applications to practical problems. We list in Chapter VIII important basic research challenges and open issues. We discuss issues related to specific implementations, novel materials, devices and phenomena. The development of reliable, fault tolerant, energy efficient devices, their scaling and integration into a Neuromorphic computer may bring us closer to the development of a machine that rivals the brain.

Reconstructing Nonequilibrium Regimes of Quantum Many-Body Systems from the Analytical Structure of Perturbative Expansions

“…is obtained from the G R n (ω) using a formal series expansion order by order of the Dyson equation (8). As an illustration, Fig.…”

Parylene Based Memristive Devices with Multilevel Resistive Switching for Neuromorphic Applications

“…Note that although the question of the nature of RS in M/PPX/ITO structures is extremely interesting, its detailed analysis lies beyond the scope of this study. Here, based on the experimental data and on the related literature, we only make the following conclusion: the bipolar RS behavior of the investigated samples most likely originates from the formation/destruction of metal bridges (filaments) in the dielectric parylene layer due to migration of metal cations (Ag + , Cu + /Cu +2 , Al +3 or Ti +4 ) from the top electrode toward the bottom during the SET process under strong electric field [1,3,30,35,46]. In contrast, according to the molecular dynamics simulations performed by Ielmini et al [30], the conductive bridges can spontaneously break during the RESET switching as a result of atomic surface diffusion driven by the minimization of the system energy.…”

Мемристоры на основе поли-n-ксилилена с внедренными наночастицами серебра

“…Критическими параметрами для использования мемристора в НВС являются число стабильных (без деградации) циклов РП из высокоомного (R o f f ) в низкоомное (R on ) состояние и обратно, отношение R o f f /R on , возможность установления произвольного резистивного состояния структуры в интервале между R on и R o f f , длительность хранения резистивных состояний, а также отсутствие электроформовки [5]. Большинство мемристивных устройств на данный момент изготавливается с использованием неорганических материалов (TiO 2 , ZnO, HfO 2 , WO 3 , SiO 2 и др.)…”