In this work, analysis and simulation of all experimentally observed switching modes in hafnium oxide based resistive random access memories are carried out using a simplified electrical conduction model. To achieve switching mode variation, two metal-insulator-metal cells with identical stack combination, but varying oxygen stoichiometry of the hafnia layer, namely, stoichiometric vs highly deficient, are considered. To access the individual switching modes, the devices were subjected to a variety of cycling conditions comprising different voltage and current ranges. For modeling the device behavior, a single or two antiserially connected memdiodes (diode with memory) were utilized. In this way, successful compact simulation of unipolar, bipolar, threshold, and complementary resistive switching modes is accomplished confirming the coexistence of two switching mechanisms of opposite polarity as the basis for all observable switching phenomena in this material. We show that only calibration of the outer current–voltage loops with the memdiode model is necessary for predicting the device behavior in the defined region revealing additional information on the switching process. The correspondence of each memdiode device with the conduction characteristics of the individual top and bottom metal-oxide contacts allows one to assess the role played by each interface in the switching process separately. This identification paves the path for a future improvement of the device performance and functionality by means of appropriate interface engineering.

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The connection between the spatial location of catastrophic breakdown spots occurring in metal-insulator-metal capacitors with a high-permittivity dielectric film (HfO2) and their respective sizes is investigated. Large area structures (10 4-10 5 µm 2) are used for this correlation assessment since, for statistical considerations, a large number of spots in the same device is imperatively required. The application of ramped or constant voltage stress across the capacitor generates defects inside the dielectric that result in the formation of multiple failure sites. High power dissipation takes place locally leaving a permanent mark on the top electrode of the device. The set of marks constitutes a point pattern with attributes that can be analyzed from a statistical viewpoint. The correlation between the spot locations and their sizes is assessed through the mark correlation function and the method of reverse conditional moments. The study reveals that for severely damaged devices there exists a link between the spot location and size that leads to a short range departure from a complete spatial randomness (CSR) process. It is shown that the affected region around each failure site is actually larger than the visible area of the spot. A structural modification of the dielectric layer in the vicinity of the spot caused by the huge thermal effects occurring just before the microexplosion might be the reason behind this extension of the damage.

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