Nanospectroscopy highlights
- Nanospectroscopy highlights
- Subfilamentary Networks in Memristive Devices
- Graphene and h-BN by a Single Molecular Precursor
- Fabrication of 2D heterojunction in graphene
- Island Ripening in a catalytic reaction
- Nanobubbles at GPa pressure under graphene
- Edge specific graphene nanoribbons
- Imaging the way molecules desorb from catalysts
- Towards the perfect graphene membrane
- Rippling of graphene on Ir(100)
- Thinnest loadstone ever
- Thermal stability of Graphene on Re(001)
- Stress Engineering at the Nanometer Scale
- Image blur in XPEEM
- AFM domain imaging using LEEM
- ARPES on corrugated graphene
- Corrugation in Exfoliated Graphene
- Domain-Wall Depinning by Spin Currents
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Subfilamentary Networks in Memristive Devices
Redox-based memristive devices are one of the most attractive emerging memory technologies in terms of scaling, power consumption and speed. In these devices, external electrical stimuli cause changes of the resistance of an oxide layer sandwiched between two metal electrodes. In the simplest application, the device can be set into a low resistance state (LRS) and reset into a high resistance state (HRS), which may encode a logical one and zero, respectively. The major obstacle delaying large-scale application, however, is the large cycle-to-cycle (C2C) and device-to-device (D2D) variability of both LRS and HRS resistance values. This behaviour describes the stochastic nature of the switching process within one cell, resulting in different resistances obtained for each switching cycle and different resistances obtained for different cells on the same chip. The switching process in transition metal oxides is believed to be driven by the nanoscale motion |
of oxygen vacancies, which form a so-called conductive filament bridging the metal electrodes. In the present study we employ spectromicroscopic photoemission and operando XAS on graphene/SrTiO3/Nb:SrTiO3 memristive devices to unveil the microscopic origin of variability. Our measurements could detect a change in the shape of the conductive filament as well as variations in the oxygen vacancy distribution within the filament. Retrieve articleSubfilamentary Networks Cause Cycle-to-Cycle Variability in Memristive Devices;C. Bäumer, R. Valenta, C. Schmitz, A. Locatelli, T.O. Menteş, S.P. Rogers, A. Sala, N. Raab, Sl. Nemsak, M. Shim, C.M. Schneider, S. Menzel, R. Waser, and R. Dittmann; ACS Nano 11(7), 6921–6929 (2017); doi: 10.1021/acsnano.7b02113. |