Open Access
Resistance Switching Memories are Memristors.
Leon O. Chua
- pp 197-230
TLDR
The goal of this tutorial is to introduce some fundamental circuit-theoretic concepts and properties of the memristor that are relevant to the analysis and design of non-volatile nano memories where binary bits are stored as resistances manifested by the Memristor’s continuum of equilibrium states.Abstract:
All 2-terminal non-volatile memory devices based on resistance switching are memristors, regardless of the device material and physical operating mechanisms. They all exhibit a distinctive “fingerprint” characterized by a pinched hysteresis loop confined to the first and the third quadrants of the v–i plane whose contour shape in general changes with both the amplitude and frequency of any periodic “sine-wave-like” input voltage source, or current source. In particular, the pinched hysteresis loop shrinks and tends to a straight line as frequency increases. Though numerous examples of voltage vs. current pinched hysteresis loops have been published in many unrelated fields, such as biology, chemistry, physics, etc., and observed from many unrelated phenomena, such as gas discharge arcs, mercury lamps, power conversion devices, earthquake conductance variations, etc., we restrict our examples in this tutorial to solid-state and/or nano devices where copious examples of published pinched hysteresis loops abound. In particular, we sampled arbitrarily, one example from each year between the years 2000 and 2010, to demonstrate that the memristor is a device that does not depend on any particular material, or physical mechanism. For example, we have shown that spin-transfer magnetic tunnel junctions are examples of memristors. We have also demonstrated that both bipolar and unipolar resistance switching devices are memristors.read more
Citations
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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.
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Memory devices and applications for in-memory computing
TL;DR: This Review provides an overview of memory devices and the key computational primitives enabled by these memory devices as well as their applications spanning scientific computing, signal processing, optimization, machine learning, deep learning and stochastic computing.
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Short-term memory to long-term memory transition in a nanoscale memristor.
Ting Chang,Sung Hyun Jo,Wei Lu +2 more
TL;DR: This study shows experimentally that the retention loss in a nanoscale memristor device bears striking resemblance to memory loss in biological systems and confirms that not only the shape or the total number of stimuli is influential, but also the time interval between stimulation pulses plays a crucial role in determining the effectiveness of the transition.
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Stochastic phase-change neurons
Tomas Tuma,Angeliki Pantazi,Manuel Le Gallo,Manuel Le Gallo,Abu Sebastian,Evangelos Eleftheriou +5 more
TL;DR: This work shows that chalcogenide-based phase-change materials can be used to create an artificial neuron in which the membrane potential is represented by the phase configuration of the nanoscale phase- change device and shows that the temporal integration of postsynaptic potentials can be achieved on a nanosecond timescale.
Journal ArticleDOI
TEAM: ThrEshold Adaptive Memristor Model
TL;DR: It is shown that the proposed TEAM, ThrEshold Adaptive Memristor model is reasonably accurate and computationally efficient, and is more appropriate for circuit simulation than previously published models.
References
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Journal ArticleDOI
The missing memristor found
TL;DR: It is shown, using a simple analytical example, that memristance arises naturally in nanoscale systems in which solid-state electronic and ionic transport are coupled under an external bias voltage.
Journal ArticleDOI
Memristor-The missing circuit element
TL;DR: In this article, the memristor is introduced as the fourth basic circuit element and an electromagnetic field interpretation of this relationship in terms of a quasi-static expansion of Maxwell's equations is presented.
Journal ArticleDOI
Nanoionics-based resistive switching memories
TL;DR: A coarse-grained classification into primarily thermal, electrical or ion-migration-induced switching mechanisms into metal-insulator-metal systems, and a brief look into molecular switching systems is taken.
Journal ArticleDOI
Memristive devices and systems
Leon O. Chua,Sung-Mo Kang +1 more
TL;DR: In this article, a broad generalization of memristors to an interesting class of nonlinear dynamical systems called memristive systems is introduced, which are unconventional in the sense that while they behave like resistive devices, they can be endowed with a rather exotic variety of dynamic characteristics.
Book
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