Physical electro-thermal model of resistive switching in bi-layered resistance-change memory
Sungho Kim,Sae-jin Kim,Kyung-min Kim,Seung Ryul Lee,Man Chang,Eun-ju Cho,Young-Bae Kim,Chang Jung Kim,U. In Chung,In-Kyeong Yoo +9 more
TLDR
A complete electro-thermal resistive switching model based on the finite element method is proposed that accurately accounts for the set/reset characteristics, which provides an in-depth understanding of the nature of resistive Switching.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.read more
Citations
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Journal ArticleDOI
Resistive switching memories based on metal oxides: mechanisms, reliability and scaling
TL;DR: This work provides an overview of the current understanding of bipolar-switching RRAM operation, reliability and scaling, and the stability of the low- and high-resistance states will be discussed in terms of conductance fluctuations and evolution in 1D filaments containing only a few atoms.
Journal ArticleDOI
Resistive Random Access Memory (RRAM): an Overview of Materials, Switching Mechanism, Performance, Multilevel Cell (mlc) Storage, Modeling, and Applications
TL;DR: Recent progress in the area of resistive random access memory (RRAM) technology which is considered one of the most standout emerging memory technologies owing to its high speed, low cost, enhanced storage density, potential applications in various fields, and excellent scalability is comprehensively reviewed.
Journal ArticleDOI
Comprehensive Physical Model of Dynamic Resistive Switching in an Oxide Memristor
Sungho Kim,Shinhyun Choi,Wei Lu +2 more
TL;DR: The proposed model reveals the roles of electric field, temperature, oxygen vacancy concentration gradient, and different material and device parameters on RS and allows accurate predictions of diverse set/reset, analog switching, and complementary RS behaviors using only material-dependent device parameters.
Journal ArticleDOI
Three-dimensional observation of the conductive filament in nanoscaled resistive memory devices.
Umberto Celano,Ludovic Goux,Attilio Belmonte,Karl Opsomer,Alexis Franquet,Andreas Schulze,Christophe Detavernier,Christophe Detavernier,Olivier Richard,Hugo Bender,Malgorzata Jurczak,Wilfried Vandervorst +11 more
TL;DR: This Letter reports for the first time on the three-dimensional (3D) observation of the shape of the conductive filament and concludes that the dynamic filament-growth is limited by the cation transport.
Journal ArticleDOI
Brain-inspired computing with memristors: Challenges in devices, circuits, and systems
Yang Zhang,Yang Zhang,Zhongrui Wang,Jiadi Zhu,Yuchao Yang,Mingyi Rao,Wenhao Song,Ye Zhuo,Xumeng Zhang,Xumeng Zhang,Menglin Cui,Linlin Shen,Ru Huang,Jianhua Yang +13 more
TL;DR: This article provides a review of current development and challenges in brain-inspired computing with memristors and survey the progress of memristive spiking and artificial neural networks.
References
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Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges
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Memristive devices for computing
TL;DR: The performance requirements for computing with memristive devices are examined and how the outstanding challenges could be met are examined.
Journal ArticleDOI
A fast, high-endurance and scalable non-volatile memory device made from asymmetric Ta2O5−x/TaO2−x bilayer structures
Myoung-Jae Lee,Chang Bum Lee,Dongsoo Lee,Seung Ryul Lee,Man Chang,Ji-Hyun Hur,Young-Bae Kim,Chang-Jung Kim,David H. Seo,Sunae Seo,U-In Chung,In-Kyeong Yoo,Kinam Kim +12 more
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Journal ArticleDOI
Atomic structure of conducting nanofilaments in TiO2 resistive switching memory
Deok-Hwang Kwon,Kyung-min Kim,Jae Hyuck Jang,Jong Myeong Jeon,Min Hwan Lee,Gun Hwan Kim,Xiang-Shu Li,Gyeong-Su Park,Bora Lee,Seungwu Han,Miyoung Kim,Cheol Seong Hwang +11 more
TL;DR: In situ current-voltage and low-temperature conductivity measurements confirm that switching occurs by the formation and disruption of Ti(n)O(2n-1) (or so-called Magnéli phase) filaments, which will provide a foundation for unravelling the full mechanism of resistance switching in oxide thin films.