Distribution projecting the reliability for 40 nm ReRAM and beyond based on stochastic differential equation

Wei, Zhiqiang; Eriguchi, Koji; Muraoka, S.; Kawasaki, Koji; Yasuhara, Ryo; Kawai, K.; Ikeda, Y.; Yoshimura, Masato; Hayakawa, Y.; Shimakawa, K.; Mikawa, Takumi; Yoneda, Shigeo

doi:10.1109/iedm.2015.7409650

Cited by 12 publications

(10 citation statements)

References 3 publications

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“…Interestingly, the latter expressions for U s and U ms predict numerical values consistent with the data in the order of magnitude, [17][18][19][20][21][22]…”

Section: The Standard Fin Scenariosupporting

confidence: 65%

Field induced nucleation in nano-structures

Karpov,

Niraula

2018

Preprint

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We predict the probability of field induced nucleation (FIN) of conductive filaments across the nano-thin dielectric layers in memory and switching devices. The novelty of our analysis is that it deals with a dielectric layer of thickness below the critical nucleation length. We show how the latter constraint can make FIN a truly threshold phenomenon possible only for voltage (not the field) exceeding a certain critical value that does not depend on the dielectric thickness. Our analysis predicts the possibility of threshold switching without memory under certain thickness dependent voltages. In parallel, the thermal runaway mechanism of electronic switching is described analytically leading to results consistent with the earlier published numerical modeling. Our predictions offer the possibility of experimental verifications deciding between FIN and thermal runaway switching.

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“…Interestingly, the latter expressions for U s and U ms predict numerical values consistent with the data in the order of magnitude, [17][18][19][20][21][22]…”

Section: The Standard Fin Scenariosupporting

confidence: 65%

Field induced nucleation in nano-structures

Karpov,

Niraula

2018

Preprint

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“…As for endurance performance in the integrated memory array, Wei et al demonstrated highly reliable 8 Kb TaO x RRAM with endurance over 10 9 cycles using the standard 0.18 μm CMOS process . Later, Wei proposed a reliability projecting method based on stochastic differential equation and verified the method on a 2 Mbit RRAM array fabricated using 40 nm technology …”

Section: High‐speed and Scalable Rram Cells And Systemsmentioning

confidence: 99%

“…85 Later, Wei proposed a reliability projecting method based on stochastic differential equation and verified the method on a 2 Mbit RRAM array fabricated using 40 nm technology. 106…”

Section: Critical Performance Metricsmentioning

confidence: 99%

Memory materials and devices: From concept to application

Zhang

Wang

Shi

et al. 2020

InfoMat

212

142

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Memory cells have always been an important element of information technology. With emerging technologies like big data and cloud computing, the scale and complexity of data storage has reached an unprecedented peak with a much higher requirement for memory technology. As is well known, better data storage is mostly achieved by miniaturization. However, as the size of the memory device is reduced, a series of problems, such as drain gate‐induced leakage, greatly hinder the performance of memory units. To meet the increasing demands of information technology, novel and high‐performance memory is urgently needed. Fortunately, emerging memory technologies are expected to improve memory performance and drive the information revolution. This review will focus on the progress of several emerging memory technologies, including two‐dimensional material‐based memories, resistance random access memory (RRAM), magnetic random access memory (MRAM), and phase‐change random access memory (PCRAM). Advantages, mechanisms, and applications of these diverse memory technologies will be discussed in this review.

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“…A sketch of the typical current voltage characteristics [2][3][4][5][6] showing various domains in Table I. U is the voltage across the device different from the power source voltage V due to the series load resistor; USTOP is determined by the maximum absolute value of voltage V during the reset process.…”

Section: Figmentioning

confidence: 99%

“…The latter prediction is consistent with the data. [2][3][4][5][6] Comparing free energies in Eqs. ( 22) and ( 25) shows that the complete gap rupture is energetically more favorable when ρ c /ρ i < (E 2 /8πδµ max ) 1/2 ∼ 0.01 where we have used E ∼ 10 6 V/cm and δµ max ∼ 10 9 J/m 3 .…”

Section: Nucleation Of Insulating Gapmentioning

confidence: 99%

A thermodynamic theory of filamentary resistive switching

Karpov,

Niraula,

Karpov

et al. 2017

Preprint

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We present a phenomenological theory of filamentary resistive random access memory (RRAM) describing the commonly observed features of their current-voltage characteristics. Our approach follows the approach of thermodynamic theory developed earlier for chalcogenide memory and threshold switches and largely independent of their microscopic details. It explains, without adjustable parameters, such features as the domains of filament formation and switching, voltage independent current in SET and current independent voltage in RESET regimes, the relation between the set and reset voltages, filament resistance independent of its length, etc. Furthermore, it expresses the observed features through the material and circuitry parameters thus paving a way to device improvements.

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Distribution projecting the reliability for 40 nm ReRAM and beyond based on stochastic differential equation

Cited by 12 publications

References 3 publications

Field induced nucleation in nano-structures

Field induced nucleation in nano-structures

Memory materials and devices: From concept to application

A thermodynamic theory of filamentary resistive switching

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