Atomic switches: atomic-movement-controlled nanodevices for new types of computing

Hino, Takami; Hasegawa, Tsuyoshi; Terabe, Kazuya; Tsuruoka, Tohru; Nayak, Alpana; Ohno, Takeo; Aono, Masakazu

doi:10.1088/1468-6996/12/1/013003

Cited by 41 publications

(36 citation statements)

References 65 publications

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“…Depending on the chalcogenide material, the conductance switching is caused by phase transitions 1,2 or ionic transport processes. [3][4][5][6] The amplitude of the voltage necessary to switch an M/C/M system from the low conductance state to the high conductance state has a threshold value (V th ). This value is the voltage at which the energy barrier for nucleation of a metallic phase inside the chalcogenide material is overcome.…”

Section: Introductionmentioning

confidence: 99%

Bulk and surface nucleation processes in Ag2S conductance switches

et al. 2011

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We studied metallic Ag formation inside and on the surface of Ag 2 S thin films, induced by the electric field created with a scanning tunnel microscope (STM) tip. Two clear regimes were observed: cluster formation on the surface at low bias voltages, and full conductance switching at higher bias voltages (V > 70 mV). The bias voltage at which this transition is observed is in agreement with the known threshold voltage for conductance switching at room temperature. We propose a model for the cluster formation at low bias voltage. Scaling of the measured data with the proposed model indicates that the process takes place near steady state, but depends on the STM tip geometry. The growth of the clusters is confirmed by tip retraction measurements and topography scans. This study provides improved understanding of the physical mechanisms that drive conductance switching in solid electrolyte memristive devices.

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Section: Introductionmentioning

confidence: 99%

Bulk and surface nucleation processes in Ag2S conductance switches

et al. 2011

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“…By looking to the published papers which have discussed behavior of atomic switch or Metal/Oxide/Metal junctions to show the interesting behavior and extract the relationships between different environment and processed variables, a conclusions comes to our mind that behavior of atomic switch or Metal/Oxide/Metal junctions shows an interesting behavior that movement of dopants (for example -oxygen vacancies in TiO 2 ) produces conduction filaments which are nonvolatile, affecting the device resistance and capacitance which shape the device characteristics [10,13]. These conduction filaments are affected by the applied electric field, passing charge and temperature in a logarithmic fashion [6].…”

Section: Memristor Modelingmentioning

confidence: 99%

“…The first exponential model gives general model by using hyperbolic sine function for ion migration change calculation (filament length change), while second exponential model comes to give more specific results by using Simmons' tunneling formula which considers the tunneling behavior is the dominant one. Therefore, we are in need of general model to fit all different behaviors and also to include hidden effects like memcapacitance effect which has been shown in recent papers [6,13]. Therefore, we developed two models to calculate device memristance as for and memcapacitance to be added for determining the whole current considering the memristor device as two parallel elements as shown in figure 3a.…”

Section: Progression Of Memristor Modelmentioning

confidence: 99%

“…To calculate the junction capacitance, we are considering filament growth is partially through device cross section area as published before [10,13]. Hence, we can model the device into two parallel capacitors: a small one representing the capacitance between two metal plates (practically: between and ) where there is no filament constructed within this area, and another variable one representing the gap between the top surface of the filament and facing electrode ( and ) (figure 3b and 3c).…”

Section: B Memcapacitance Modelmentioning

confidence: 99%

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Memristance and memcapacitance modeling of thin film devices showing memristive behavior

Ahmed

Cho

2012

2012 13th International Workshop on Cellular Nanoscale Networks and Their Applications

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Abstract-In 2008, the fourth passive element "Memristor" was implemented as a device having both passivity and nonvolatile properties opening the way into new possibilities in the design and fabrication of innovative memory, arithmetic and logic architectures. Nano-features and ionic transport mechanism inherent in memristor device introduce new challenges into modeling, characterization and, in particular, in the related circuit simulation needs with system constructs. Therefore, in this paper, we analyze memristor device fundamentally to characterize the memristance paying particular attention to the hidden memcapacitance effect. Our proposed macro-model modifies takes into account some of the non ideal effects like tunneling current and the hidden memcapacitor constructed across non conducting materials. The model provides the insight for building a device as either memristive or memcapacitive system. The simulation results have been compared with HP published data which show good agreement.

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“…Most of these paradigms require physics different from the physics of CMOS. For instance, computation has been demonstrated with devices based on the laws of photonics [3], spintronics [4], or nanoionics [5].…”

Section: Introductionmentioning

confidence: 99%