Nano-Ionic Solid State Resistive Memories (Re-RAM): A Review

Abstract

Nano-ionic devices based on modest to fast ion conductors as active materials intrigued a revolution in the field of nano solid state resistive memories (the so-called Re-RAM) ever since HP labs unveiled the first solid state memristor device based on titanium dioxide (TiO2). This has brought impetus to the practical implementation of fourth missing element called “Memristor” correlating charge (q) and flux (φ) based on the conceptual thought by Chua in 1971 completing a missing gap between the passive electronic components (R, C and L). It depicts various functional features as memory element in terms of ionic charge transport in solid state by virtue of external electric flux variations. Consequently, a new avenue has been found by manipulating the ionic charge carriers creating a fast switching resistive random access memory (Re-RAM) or the so-called Memristors. The recent research has led to low power, faster switching speed, high endurance and high retention time devices that can be scaled down the order of few nanometers dimension and the 3D stacking is employed that significantly reduces the die area. This review is organized to provide the progress hitherto accomplished in the materials arena to make memristor devices with respect to current research attempts, different stack structures of ReRAM cells using various materials as well as the application of memristive system. Different synthesis approaches to make nano-ionic conducting metal oxides, the fabrication methods for ReRAM cells and its memory performance are reviewed comprehensively.

Neuromorphic Computing with Memristor Crossbar

“…It consists of a switching layer between the first electrode and bottom electrode as shown in Figure . Since it has enormous scientific and commercial potential in the information and computing technologies, especially neuromorphic computing, many types of memristors have been developed and the mechanism, materials, and switching phenomena have been reviewed . Basically, memristors can be loosely grouped into three categories: ionic memristors, spin‐based memristors, and phase‐change memristors (PCM), and each one of them can be further classified according to the mechanism, materials system, and switching phenomena.…”

“…Basically, memristors can be loosely grouped into three categories: ionic memristors, spin‐based memristors, and phase‐change memristors (PCM), and each one of them can be further classified according to the mechanism, materials system, and switching phenomena. An ionic memristor changes its states by applying a voltage or current to move cations or anions in the switching layer, where the movement of the anions or cations is usually accompanied by chemical reactions (redox) . The ionic memristor can be classified into the anion memristor and cation memristor.…”

Наноразмерные флуктуации потенциала в SiO-=SUB=-x-=/SUB=-, синтезированном плазмохимическим осаждением

“…Ключевым преимуществом SiO x перед другими кандидатами на роль активной среды RRAM является совместимость со стандартными техпроцессами современной микроэлектроники. RRAM по сравнению с современной флеш-памятью имеет большое количество циклов переключения (∼ 10 10 ), малое энергопотребление (< 10 fJ), высокое быстродействие (∼ 1 ns) [4]. В разработке RRAM нерешенной на сегодняшний день проблемой является, так называемая, формовка -первое переключение из исходного состояния в низкоомное подачей на структуру импульса напряжения, величина которого, как правило, в несколько раз превышает напряжение последующих переключений.…”

Memristive Anodic Oxides: Production, Properties and Applications in Neuromorphic Computing

“…A variety of alternatives to traditional information processing devices have been proposed, boosting new scientific research in semiconductor principles and technologies [1]. In this frame, memristors-or resistive switching materials, as the two terms identify the same switching behavior [2,3]-were identified as valuable candidates for alternative nanoelectronic devices [4][5][6][7], with particular reference to nonvolatile memories and neuromorphic applications.…”