Research paperExperimental CharacterizationComputational Kinetic ModelStudies of two-dimensional material resistive random-access memory by kinetic Monte Carlo simulationsYing-Chuan Chen, Yu-Ting Chao, Edward Chen, Chao-Hsin Wu et al.2023·10.1103/PhysRevMaterials.7.094001·arXiv:2304.11345AbstractResistive memory based on two-dimensional tungsten disulfide (WS₂), molybdenum disulfide (MoS₂), and hexagonal boron nitride (h-BN) materials is studied via experiments and simulations. The influence of active-layer thickness is discussed, and the thickness with the best on/off ratio is identified for 2D resistive random-access memory. The work compares CVD-grown and mechanically exfoliated samples and uses a kinetic Monte Carlo model to extract material parameters, including diffusion-related activation energies and retention characteristics.Read more
Exfoliated WS₂ RRAM device with asymmetric Au/Ti electrodes on heavily doped p-type Si substrate; active WS₂ thickness 33 nm (44 layers).1 preparation4 characterizations4 properties2 figuresExperimentalWS₂Studied MaterialExpand
MoS₂ RRAM device used for comparison with Au/Ti electrodes; active layer thickness 20 nm.1 characterization3 properties1 figureExperimentalMoS₂Studied MaterialExpand
h-BN RRAM device used for comparison with Au/Ti electrodes; active layer thickness 39.4 nm.1 characterization3 properties1 figureExperimentalBNStudied MaterialExpand
KMC model system for WS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedWS₂Studied MaterialExpand
KMC model system for MoS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedMoS₂Studied MaterialExpand
KMC model system for h-BN RRAM parameter extraction and I-V simulation.2 propertiesSimulatedBNStudied MaterialExpand
Research paperExperimental CharacterizationComputational Kinetic ModelStudies of two-dimensional material resistive random-access memory by kinetic Monte Carlo simulationsYing-Chuan Chen, Yu-Ting Chao, Edward Chen, Chao-Hsin Wu et al.2023·10.1103/PhysRevMaterials.7.094001·arXiv:2304.11345AbstractResistive memory based on two-dimensional tungsten disulfide (WS₂), molybdenum disulfide (MoS₂), and hexagonal boron nitride (h-BN) materials is studied via experiments and simulations. The influence of active-layer thickness is discussed, and the thickness with the best on/off ratio is identified for 2D resistive random-access memory. The work compares CVD-grown and mechanically exfoliated samples and uses a kinetic Monte Carlo model to extract material parameters, including diffusion-related activation energies and retention characteristics.Read more
Exfoliated WS₂ RRAM device with asymmetric Au/Ti electrodes on heavily doped p-type Si substrate; active WS₂ thickness 33 nm (44 layers).1 preparation4 characterizations4 properties2 figuresExperimentalWS₂Studied MaterialExpand
MoS₂ RRAM device used for comparison with Au/Ti electrodes; active layer thickness 20 nm.1 characterization3 properties1 figureExperimentalMoS₂Studied MaterialExpand
h-BN RRAM device used for comparison with Au/Ti electrodes; active layer thickness 39.4 nm.1 characterization3 properties1 figureExperimentalBNStudied MaterialExpand
KMC model system for WS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedWS₂Studied MaterialExpand
KMC model system for MoS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedMoS₂Studied MaterialExpand
KMC model system for h-BN RRAM parameter extraction and I-V simulation.2 propertiesSimulatedBNStudied MaterialExpand
Research paperExperimental CharacterizationComputational Kinetic ModelStudies of two-dimensional material resistive random-access memory by kinetic Monte Carlo simulationsYing-Chuan Chen, Yu-Ting Chao, Edward Chen, Chao-Hsin Wu et al.2023·10.1103/PhysRevMaterials.7.094001·arXiv:2304.11345AbstractResistive memory based on two-dimensional tungsten disulfide (WS₂), molybdenum disulfide (MoS₂), and hexagonal boron nitride (h-BN) materials is studied via experiments and simulations. The influence of active-layer thickness is discussed, and the thickness with the best on/off ratio is identified for 2D resistive random-access memory. The work compares CVD-grown and mechanically exfoliated samples and uses a kinetic Monte Carlo model to extract material parameters, including diffusion-related activation energies and retention characteristics.Read more
Exfoliated WS₂ RRAM device with asymmetric Au/Ti electrodes on heavily doped p-type Si substrate; active WS₂ thickness 33 nm (44 layers).1 preparation4 characterizations4 properties2 figuresExperimentalWS₂Studied MaterialExpand
MoS₂ RRAM device used for comparison with Au/Ti electrodes; active layer thickness 20 nm.1 characterization3 properties1 figureExperimentalMoS₂Studied MaterialExpand
h-BN RRAM device used for comparison with Au/Ti electrodes; active layer thickness 39.4 nm.1 characterization3 properties1 figureExperimentalBNStudied MaterialExpand
KMC model system for WS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedWS₂Studied MaterialExpand
KMC model system for MoS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedMoS₂Studied MaterialExpand
KMC model system for h-BN RRAM parameter extraction and I-V simulation.2 propertiesSimulatedBNStudied MaterialExpand
Research paperExperimental CharacterizationComputational Kinetic ModelStudies of two-dimensional material resistive random-access memory by kinetic Monte Carlo simulationsYing-Chuan Chen, Yu-Ting Chao, Edward Chen, Chao-Hsin Wu et al.2023·10.1103/PhysRevMaterials.7.094001·arXiv:2304.11345AbstractResistive memory based on two-dimensional tungsten disulfide (WS₂), molybdenum disulfide (MoS₂), and hexagonal boron nitride (h-BN) materials is studied via experiments and simulations. The influence of active-layer thickness is discussed, and the thickness with the best on/off ratio is identified for 2D resistive random-access memory. The work compares CVD-grown and mechanically exfoliated samples and uses a kinetic Monte Carlo model to extract material parameters, including diffusion-related activation energies and retention characteristics.Read more
Exfoliated WS₂ RRAM device with asymmetric Au/Ti electrodes on heavily doped p-type Si substrate; active WS₂ thickness 33 nm (44 layers).1 preparation4 characterizations4 properties2 figuresExperimentalWS₂Studied MaterialExpand
MoS₂ RRAM device used for comparison with Au/Ti electrodes; active layer thickness 20 nm.1 characterization3 properties1 figureExperimentalMoS₂Studied MaterialExpand
h-BN RRAM device used for comparison with Au/Ti electrodes; active layer thickness 39.4 nm.1 characterization3 properties1 figureExperimentalBNStudied MaterialExpand
KMC model system for WS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedWS₂Studied MaterialExpand
KMC model system for MoS₂ RRAM parameter extraction and I-V simulation.2 propertiesSimulatedMoS₂Studied MaterialExpand
KMC model system for h-BN RRAM parameter extraction and I-V simulation.2 propertiesSimulatedBNStudied MaterialExpand