Seung Ryul Lee

Bio: Seung Ryul Lee is an academic researcher from Samsung. The author has contributed to research in topics: Resistive random-access memory & Non-volatile memory. The author has an hindex of 10, co-authored 21 publications receiving 2473 citations.

A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5−x/TaO2−x bilayer structures

Abstract: Numerous candidates attempting to replace Si-based flash memory have failed for a variety of reasons over the years. Oxide-based resistance memory and the related memristor have succeeded in surpassing the specifications for a number of device requirements. However, a material or device structure that satisfies high-density, switching-speed, endurance, retention and most importantly power-consumption criteria has yet to be announced. In this work we demonstrate a TaO(x)-based asymmetric passive switching device with which we were able to localize resistance switching and satisfy all aforementioned requirements. In particular, the reduction of switching current drastically reduces power consumption and results in extreme cycling endurances of over 10(12). Along with the 10 ns switching times, this allows for possible applications to the working-memory space as well. Furthermore, by combining two such devices each with an intrinsic Schottky barrier we eliminate any need for a discrete transistor or diode in solving issues of stray leakage current paths in high-density crossbar arrays.

Physical electro-thermal model of resistive switching in bi-layered resistance-change memory

Abstract: Tantalum-oxide-based bi-layered resistance-change memories (RRAMs) have recently improved greatly with regard to their memory performances. The formation and rupture of conductive filaments is generally known to be the mechanism that underlies resistive switching. The nature of the filament has been studied intensively and several phenomenological models have consistently predicted the resistance-change behavior. However, a physics-based model that describes a complete bi-layered RRAM structure has not yet been demonstrated. Here, a complete electro-thermal resistive switching model based on the finite element method is proposed. The migration of oxygen vacancies is simulated by the local temperature and electric field derived from carrier continuity and heat equations fully coupled in a 3-D geometry, which considers a complete bi-layered structure that includes the top and bottom electrodes. The proposed model accurately accounts for the set/reset characteristics, which provides an in-depth understanding of the nature of resistive switching.

Multi-level switching of triple-layered TaOx RRAM with excellent reliability for storage class memory

Abstract: A highly reliable RRAM with multi-level cell (MLC) characteristics were fabricated using a triple-layer structure (base layer/oxygen exchange layer/barrier layer) for the storage class memory applications. A reproducible multi-level switching behaviour was successfully observed, and simulated by the modulated Schottky barrier model. Morevoer, a new programming algorithm was developed for more reliable and uniform MLC operation. As a result, more than 107 cycles of switching endurance and 10 years of data retention at 85°C for all the 2 bit/cell operation were archieved.

Bi-layered RRAM with unlimited endurance and extremely uniform switching

Abstract: We demonstrate resistive random access memory (RRAM) architecture with bi-layered switching element for reliable resistive switching memory. Based on the modulated Schottky barrier modeling, several key functions to achieve a realiable bipolar switching property are extracted. Our device shows an excellent memory performance such as enduracne of 1011 cycles at 30ns, data retention of >104s at 200°C, and calculated bit error rate below 10−11.

Self‐Limited Switching in Ta2O5/TaOx Memristors Exhibiting Uniform Multilevel Changes in Resistance

Abstract: To facilitate the development of memristive devices, it is essential to resolve the problem of non-uniformity in switching, which is caused by the random nature of the filamentary switching mechanism in many resistance switching memories based on transition metal oxide. In addition, device parameters such as low- and high-state resistance should be regulated as desired. These issues can be overcome if memristive devices have switching limits for both the low- and high-resistance states and if their resistance values are highly controllable. In this study, a method termed self-limited switching for uniformly regulating the values of both the low- and high-resistance states is suggested, and the circuit configuration required for the self-limited switching is established in a Ta2O5/TaOx memristive structure. A method of improving the uniformity of multi-level resistance states in this memristive system is also proposed.

Memristive devices for computing

Abstract: Memristive devices are electrical resistance switches that can retain a state of internal resistance based on the history of applied voltage and current. These devices can store and process information, and offer several key performance characteristics that exceed conventional integrated circuit technology. An important class of memristive devices are two-terminal resistance switches based on ionic motion, which are built from a simple conductor/insulator/conductor thin-film stack. These devices were originally conceived in the late 1960s and recent progress has led to fast, low-energy, high-endurance devices that can be scaled down to less than 10 nm and stacked in three dimensions. However, the underlying device mechanisms remain unclear, which is a significant barrier to their widespread application. Here, we review recent progress in the development and understanding of memristive devices. We also examine the performance requirements for computing with memristive devices and detail how the outstanding challenges could be met.

Metal–Oxide RRAM

Abstract: In this paper, recent progress of binary metal-oxide resistive switching random access memory (RRAM) is reviewed. The physical mechanism, material properties, and electrical characteristics of a variety of binary metal-oxide RRAM are discussed, with a focus on the use of RRAM for nonvolatile memory application. A review of recent development of large-scale RRAM arrays is given. Issues such as uniformity, endurance, retention, multibit operation, and scaling trends are discussed.

PRIME: a novel processing-in-memory architecture for neural network computation in ReRAM-based main memory

Abstract: Processing-in-memory (PIM) is a promising solution to address the "memory wall" challenges for future computer systems. Prior proposed PIM architectures put additional computation logic in or near memory. The emerging metal-oxide resistive random access memory (ReRAM) has showed its potential to be used for main memory. Moreover, with its crossbar array structure, ReRAM can perform matrix-vector multiplication efficiently, and has been widely studied to accelerate neural network (NN) applications. In this work, we propose a novel PIM architecture, called PRIME, to accelerate NN applications in ReRAM based main memory. In PRIME, a portion of ReRAM crossbar arrays can be configured as accelerators for NN applications or as normal memory for a larger memory space. We provide microarchitecture and circuit designs to enable the morphable functions with an insignificant area overhead. We also design a software/hardware interface for software developers to implement various NNs on PRIME. Benefiting from both the PIM architecture and the efficiency of using ReRAM for NN computation, PRIME distinguishes itself from prior work on NN acceleration, with significant performance improvement and energy saving. Our experimental results show that, compared with a state-of-the-art neural processing unit design, PRIME improves the performance by ~2360× and the energy consumption by ~895×, across the evaluated machine learning benchmarks.

In-memory computing with resistive switching devices

Abstract: Modern computers are based on the von Neumann architecture in which computation and storage are physically separated: data are fetched from the memory unit, shuttled to the processing unit (where computation takes place) and then shuttled back to the memory unit to be stored. The rate at which data can be transferred between the processing unit and the memory unit represents a fundamental limitation of modern computers, known as the memory wall. In-memory computing is an approach that attempts to address this issue by designing systems that compute within the memory, thus eliminating the energy-intensive and time-consuming data movement that plagues current designs. Here we review the development of in-memory computing using resistive switching devices, where the two-terminal structure of the devices, their resistive switching properties, and direct data processing in the memory can enable area- and energy-efficient computation. We examine the different digital, analogue, and stochastic computing schemes that have been proposed, and explore the microscopic physical mechanisms involved. Finally, we discuss the challenges in-memory computing faces, including the required scaling characteristics, in delivering next-generation computing. This Review Article examines the development of in-memory computing using resistive switching devices.

Recent progress in resistive random access memories: Materials, switching mechanisms, and performance

Abstract: This review article attempts to provide a comprehensive review of the recent progress in the so-called resistive random access memories (RRAMs) First, a brief introduction is presented to describe the construction and development of RRAMs, their potential for broad applications in the fields of nonvolatile memory, unconventional computing and logic devices, and the focus of research concerning RRAMs over the past decade Second, both inorganic and organic materials used in RRAMs are summarized, and their respective advantages and shortcomings are discussed Third, the important switching mechanisms are discussed in depth and are classified into ion migration, charge trapping/de-trapping, thermochemical reaction, exclusive mechanisms in inorganics, and exclusive mechanisms in organics Fourth, attention is given to the application of RRAMs for data storage, including their current performance, methods for performance enhancement, sneak-path issue and possible solutions, and demonstrations of 2-D and 3-D crossbar arrays Fifth, prospective applications of RRAMs in unconventional computing, as well as logic devices and multi-functionalization of RRAMs, are comprehensively summarized and thoroughly discussed The present review article ends with a short discussion concerning the challenges and future prospects of the RRAMs