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Subfilamentary Networks in Memristive Devices

In-operando XAS-PEEM gives access to  the microscopic origin of resitance variability in memristior devices based on transition metal oxides. Upon switching, the spatial rearrangement of oxygen vacancies results in variations of their local concentration and shape of the conductive filament bridging the metal electrodes.
C. Baeumer et al., ACS Nano 11, 6921 (2017).

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.

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Subfilamentary 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.
Ultima modifica il Mercoledì, 14 Novembre 2018 15:51