Finding Oxygen Reservoir by Using Extremely Small Test Cell Structure for Resistive Random Access Memory with Replaceable Bottom Electrode

Although the presence of an oxygen reservoir (OR) is assumed in many models that explain resistive switching of resistive random access memory (ReRAM) with electrode/metal oxide (MO)/electrode structures, the location of OR is not clear. We have previously reported a method, which involved the use of an AFM cantilever, for preparing an extremely small ReRAM cell that has a removable bottom electrode (BE). In this study, we used this cell structure to specify the location of OR. Because an anode is often assumed to work as OR, we investigated the effect of changing anodes without changing the MO layer and the cathode on the occurrence of reset. It was found that the reset occurred independently of the catalytic ability and Gibbs free energy (ΔG) of the anode. Our proposed structure enabled to determine that the reset was caused by repairing oxygen vacancies of which a filament consists due to the migration of oxygen ions from the surrounding area when high ΔG anode metal is used, whereas by oxidizing the anode due to the migration of oxygen ions from the MO layer when low ΔG anode metal is used, suggesting the location of OR depends on ΔG of the anode.


Simulation Simulation conditions.
Simulation was performed using commercial software COMSOL Multiphysics. We used cylindrical Pt/NiO/Pt cells with the area of 10 m (large cell) and 100 nm (small cell) in diameter, as shown in Fig. S1, where the dashed line was symmetry axis. A filament (FL) consisting of oxygen vacancies, V O 's, with the radius of 10 nm is located at the center. The memory cell was surrounded by 10 m thick air and temperature is fixed at 293 K at the edge of the air region. Vo concentration, n V , at the filament and out of the filament are shown in Table   S1. We attempted to reset the large and small cells by applying a pulse voltage with the rising time and the pulse height of 1.8 s and 1.
All numeric values for parameters used in the simulation were summarized in Table S1. Table S1. Numeric values for parameters used in this study.

Parameters from measurements and assumptions.
To solve the heat equation (Equation (5)), electric conductivity, , thermal conductivity, k, thermal capacitance C p , and mass density ρ of the NiO memory layer including V O filament and Pt electrodes have to be decided. Furthermore, n V also should be decided to solve equations for fluxes of Fick and Soret diffusion of V O (Equations (7) and (8)).

Parameters of memory layer (NiO and V O filament). V O concentration n V .
A filament in the NiO layer of a Pt/NiO/Pt structure is generally considered to be formed by V O 's.
This means that a filament is area where V O concentration, n V , is higher than surrounding area and the n V . We assumed that n V can change from the value of NiO before forming (minimum n V ) continuously  (1) using  (= 1/r) at 298 K, 14.7 μW −1 m −1 , and E a of 0.381 eV estimated above.

Thermal conductivity
Thermal conductivity, k, was assumed to be linearly dependent on n V as shown in Fig. S5. k increases from 71 Wm −1 K −1 6) , which is k of NiO, for the minimum n V linearly to 90.5 Wm −1 K −1 1) , which is k of Ni, for the maximum n V .

Isobaric specific heat capacity
Temperature dependence of isobaric specific heat capacity was estimated by interpolation and extrapolation of experimentally obtained C p values of NiO 3) shown by circles in Fig. S6. The data was fit well to Equation (6). Temperature dependence of isobaric specific heat capacity was estimated by interpolation and extrapolation using Equation (6).  The Arrhenius plot of the temperature dependence of r that was estimated by the relation of r = R ini ×S /d using R ini (T) in Fig. S4(a), the cell area, S, of 150 m in diameter, and the NiO thickness, d, of 60 nm.