This review focuses on electrochemical metallization memory cells (ECM), highlighting their advantages as the next generation memories. In a brief introduction, the basic switching mechanism of ECM cells is described and the historical development is sketched. In a second part, the full spectra of materials and material combinations used for memory device prototypes and for dedicated studies are presented. In a third part, the specific thermodynamics and kinetics of nanosized electrochemical cells are described. The overlapping of the space charge layers is found to be most relevant for the cell properties at rest. The major factors determining the functionality of the ECM cells are the electrode reaction and the transport kinetics. Depending on electrode and/or electrolyte material electron transfer, electro-crystallization or slow diffusion under strong electric fields can be rate determining. In the fourth part, the major device characteristics of ECM cells are explained. Emphasis is placed on switching speed, forming and SET/RESET voltage, R(ON) to R(OFF) ratio, endurance and retention, and scaling potentials. In the last part, circuit design aspects of ECM arrays are discussed, including the pros and cons of active and passive arrays. In the case of passive arrays, the fundamental sneak path problem is described and as well as a possible solution by two anti-serial (complementary) interconnected resistive switches per cell. Furthermore, the prospects of ECM with regard to further scalability and the ability for multi-bit data storage are addressed.
20 May 2022 in Neuromorphic Computing and Engineering
Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption. The next generation computer technology is expected to solve problems at the exascale with 1018 calculations each second. Even though these future computers will be incredibly powerful, if they are based on von Neumann type architectures, they will consume between 20 and 30 megawatts of power and will not have intrinsic physically built-in capabilities to learn or deal with complex data as our brain does. These needs can be addressed by neuromorphic computing systems which are inspired by the biological concepts of the human brain. This new generation of computers has the potential to be used for the storage and processing of large amounts of digital information with much lower power consumption than conventional processors. Among their potential future applications, an important niche is moving the control from data centers to edge devices. The aim of this roadmap is to present a snapshot of the present state of neuromorphic technology and provide an opinion on the challenges and opportunities that the future holds in the major areas of neuromorphic technology, namely materials, devices, neuromorphic circuits, neuromorphic algorithms, applications, and ethics. The roadmap is a collection of perspectives where leading researchers in the neuromorphic community provide their own view about the current state and the future challenges for each research area. We hope that this roadmap will be a useful resource by providing a concise yet comprehensive introduction to readers outside this field, for those who are just entering the field, as well as providing future perspectives for those who are well established in the neuromorphic computing community.
27 September 2018 in Advanced Electronic Materials
Resistive switching (RS) is an interesting property shown by some materials systems that, especially during the last decade, has gained a lot of interest for the fabrication of electronic devices, with electronic nonvolatile memories being those that have received the most attention. The presence and quality of the RS phenomenon in a materials system can be studied using different prototype cells, performing different experiments, displaying different figures of merit, and developing different computational analyses. Therefore, the real usefulness and impact of the findings presented in each study for the RS technology will be also different. This manuscript describes the most recommendable methodologies for the fabrication, characterization, and simulation of RS devices, as well as the proper methods to display the data obtained. The idea is to help the scientific community to evaluate the real usefulness and impact of an RS study for the development of RS technology.
Redox-based nanoionic resistive memory cells are one of the most promising emerging nanodevices for future information technology with applications for memory, logic and neuromorphic computing. Recently, the serendipitous discovery of the link between redox-based nanoionic-resistive memory cells and memristors and memristive devices has further intensified the research in this field. Here we show on both a theoretical and an experimental level that nanoionic-type memristive elements are inherently controlled by non-equilibrium states resulting in a nanobattery. As a result, the memristor theory must be extended to fit the observed non-zero-crossing I-V characteristics. The initial electromotive force of the nanobattery depends on the chemistry and the transport properties of the materials system but can also be introduced during redox-based nanoionic-resistive memory cell operations. The emf has a strong impact on the dynamic behaviour of nanoscale memories, and thus, its control is one of the key factors for future device development and accurate modelling.