Modeling the variability of memristive devices with hexagonal boron nitride as dielectric | Paper Citation Record

Observation 120c23c3-b9ff-4ae1-a235-9a2258f69711 · outbound

This paper cites R., Shi, Y., Mahata, C., Yuan, B., Liang, X.,.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric R., Shi, Y., Mahata, C., Yuan, B., Liang, X.,

Reference 1

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This paper cites The development of integrated circuits based on two -dimensional materials.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric The development of integrated circuits based on two -dimensional materials

Reference 2

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This paper cites Recommended methods to study resistive switching devices.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Recommended methods to study resistive switching devices

Reference 3

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This paper cites Progressive RESET induced by Joule heating in hBN RRAMs.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Progressive RESET induced by Joule heating in hBN RRAMs

Reference 4

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This paper cites Advanced data encryption using two-dimensional materials.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Advanced data encryption using two-dimensional materials

Reference 5

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Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Unresolved cited work

Reference 6

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This paper cites Electronic synapses made of layered two-dimensional materials.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Electronic synapses made of layered two-dimensional materials

Reference 7

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Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Unresolved cited work

Reference 8

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Observation c551a6d7-2195-4acf-89c4-8495b97cafaa · outbound

This paper cites Graphene and Related Materials for Resistive Random Access Memories.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Graphene and Related Materials for Resistive Random Access Memories

Reference 9

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Observation 03e87213-a09c-4233-8f6e-b622d3ffa983 · outbound

This paper cites Coexistence of grain‐ boundaries‐assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Coexistence of grain‐ boundaries‐assisted bipolar and threshold resistive switching in multilayer hexagonal boron nitride

Reference 10

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This paper cites H., McClellan, C., Shi, Y., Zheng, X., Chen, V., Lanza, M.,.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric H., McClellan, C., Shi, Y., Zheng, X., Chen, V., Lanza, M.,

Reference 11

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Observation 3176c949-86ed-43b3-9f9a-dea26c64ee7c · outbound

This paper cites Yield, variability, reliability, and stability of two -dimensional materials based solid -state electronic devices.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Yield, variability, reliability, and stability of two -dimensional materials based solid -state electronic devices

Reference 12

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Observation 48a9b5dd-c58b-4738-9428-8731d214c05c · outbound

This paper cites Variability and Yield in h‐BN‐Based Memristive Circuits: The Role of Each Type of Defect.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Variability and Yield in h‐BN‐Based Memristive Circuits: The Role of Each Type of Defect

Reference 13

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This paper cites Standards for the Characterization of Endurance in Resistive Switching Devices.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Standards for the Characterization of Endurance in Resistive Switching Devices

Reference 14

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Observation 8e756558-a3d4-46d7-94ab-d6950d9a1b3b · outbound

This paper cites Time series statistical analysis: a powerful tool to evaluate the variability of resistive switching memories.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Time series statistical analysis: a powerful tool to evaluate the variability of resistive switching memories

Reference 15

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This paper cites A SPICE Compact Model of Metal Oxide Resistive Switching Memory With Variations,.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric A SPICE Compact Model of Metal Oxide Resistive Switching Memory With Variations,

Reference 16

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This paper cites Compact Modeling of RRAM Devices and Its Applications in 1T1R and 1S1R Array Design.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Compact Modeling of RRAM Devices and Its Applications in 1T1R and 1S1R Array Design

Reference 17

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Observation 425b40d7-55a2-4ca0-8d15-fd22e94199f8 · outbound

This paper cites Robust compact model for bipolar oxide -based resistive switching memories.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Robust compact model for bipolar oxide -based resistive switching memories

Reference 18

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Observation 3f3aa481-4da4-4022-b76e-6c9f2cf32330 · outbound

This paper cites Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Resistive Switching: From Fundamentals of Nanoionic Redox Processes to Memristive Device Applications

Reference 19

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This paper cites A Compact Model for Metal –Oxide Resistive Random Access Memory with Experiment Verification.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric A Compact Model for Metal –Oxide Resistive Random Access Memory with Experiment Verification

Reference 20

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This paper cites Compact Model of HfOX -Based Electronic Synaptic Devices for Neuromorphic Computing.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Compact Model of HfOX -Based Electronic Synaptic Devices for Neuromorphic Computing

Reference 21

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Observation 97b993e5-ea36-42a2-93da-2f2cf46a193d · outbound

This paper cites On the Thermal Models for Resistive Random Access Memory Circuit Simulation.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric On the Thermal Models for Resistive Random Access Memory Circuit Simulation

Reference 22

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This paper cites Time series modeling of the cycle-to-cycle variability in h-BN based memristors,.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Time series modeling of the cycle-to-cycle variability in h-BN based memristors,

Reference 23

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This paper cites Temperature of conductive nanofilaments in hexagonal boron nitride based memristors showing threshold resistive switching.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Temperature of conductive nanofilaments in hexagonal boron nitride based memristors showing threshold resistive switching

Reference 24

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This paper cites Experimental study of the series resistance effect and its impact on the compact modeling of the conduction characteristics of HfO 2-based resistive switching memories.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Experimental study of the series resistance effect and its impact on the compact modeling of the conduction characteristics of HfO 2-based resistive switching memories

Reference 25

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Observation 77b2ebd8-dbeb-42a3-a61c-3685d2b10d35 · outbound

This paper cites Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective

Reference 26

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This paper cites Memristor variability and stochastic physical properties modeling from a multivariate time series approach.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Memristor variability and stochastic physical properties modeling from a multivariate time series approach

Reference 27

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This paper cites A Complex Model Via Phase -Type Distributions to Study Random Telegraph Noise in Resistive Memories.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric A Complex Model Via Phase -Type Distributions to Study Random Telegraph Noise in Resistive Memories

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:21.052078Z

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Observation 47074770-e2e9-469e-a797-439538b34e60 · outbound

This paper cites Non - Uniform Spline Quasi -Interpolation to Extract the Series Resistance in Resistive Switching Memristors for Compact Modeling Purposes.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Non - Uniform Spline Quasi -Interpolation to Extract the Series Resistance in Resistive Switching Memristors for Compact Modeling Purposes

Reference 29

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This paper cites Experimental Evaluation of the Dynamic Route Map in the Reset Transition of Memristive ReRAMs.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Experimental Evaluation of the Dynamic Route Map in the Reset Transition of Memristive ReRAMs

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:21.029687Z

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Observation 96bc2354-34c8-454e-9d2e-42d6d7bb5fc3 · outbound

This paper cites Comprehensive study on unipolar RRAM charge conduction and stochastic features, a simulation approach.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Comprehensive study on unipolar RRAM charge conduction and stochastic features, a simulation approach

Reference 31

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This paper cites Defect‐Free Metal Deposition on 2D Materials via Inkjet Printing Technology.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Defect‐Free Metal Deposition on 2D Materials via Inkjet Printing Technology

Reference 32

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This paper cites A 40nm 2Mb ReRAM macro with 85% reduction in forming time and 99% reduction in page-write time using auto -forming and auto -write schemes.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric A 40nm 2Mb ReRAM macro with 85% reduction in forming time and 99% reduction in page-write time using auto -forming and auto -write schemes

Reference 33

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This paper cites Memory devices and applications for in-memory computing.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Memory devices and applications for in-memory computing

Reference 34

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Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:53:20.669302Z

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This paper cites Hardware -intrinsic security primitives enabled by analogue state and nonlinear conductance variations in integrated memristors.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Hardware -intrinsic security primitives enabled by analogue state and nonlinear conductance variations in integrated memristors

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.656886Z

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This paper cites Memristors with initial low resistive state for efficient neuromorphic systems.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Memristors with initial low resistive state for efficient neuromorphic systems

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.644953Z

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Observation 31c3a87d-6bf3-4da5-8d22-da9a71e03a9f · outbound

This paper cites Analysis and modeling of resistive switching statistics.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Analysis and modeling of resistive switching statistics

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.631559Z

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Observation ff01c36e-19bb-4291-94e1-0278b342c41b · outbound

This paper cites Resistive Switching in HfO 2 based valence change memories, a comprehensive 3D kinetic Monte Carlo approach.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Resistive Switching in HfO 2 based valence change memories, a comprehensive 3D kinetic Monte Carlo approach

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.586630Z

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Observation faadf6e1-87a0-4da3-967f-ed370541d7cb · outbound

This paper cites Exploring Resistive Switching based Memristors in the Charge -Flux Domain, a modeling Approach.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Exploring Resistive Switching based Memristors in the Charge -Flux Domain, a modeling Approach

Reference 40

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Observation 291a97c3-154d-44a6-8327-bd1af057965c · outbound

This paper cites Introduction to Time Series and Forecasting.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Introduction to Time Series and Forecasting

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.423984Z

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Observation a3ee4115-88af-4581-bfb8-5f68de8c40bc · outbound

This paper cites Time series analysis and forecasting by example.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Time series analysis and forecasting by example

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.337234Z

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Observation a5616279-c7aa-4cc8-876f-b596debcc65c · outbound

This paper cites Resistive switching devices producing giant random telegraph noise.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Resistive switching devices producing giant random telegraph noise

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.325211Z

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Observation 69409ae0-3289-4afd-9721-aae9b96c3d99 · outbound

This paper cites Excess entropy and thermal behavior of Cu- and Ti-doped bioactive glasses.

Modeling the variability of memristive devices with hexagonal boron nitride as dielectric Excess entropy and thermal behavior of Cu- and Ti-doped bioactive glasses

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:53:20.310021Z

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