We prepared bilayer HfO 2 /TiO 2 resistive random accessory memory (RRAM) using magnetron sputtering on an ITO/PEN flexible substrate. The switching voltages (V SET and V RESET ) were smaller for the Pt/HfO 2 /TiO 2 /ITO device than for a Pt/HfO 2 /ITO memory device. The insertion of a TiO 2 layer in the switching layer was inferred to act as an oxygen reservoir to reduce the switching voltages. In addition, greatly improved uniformity was achieved, which showed the coefficient of the variations of V SET and V RESET to be 9.90% and 6.35% for the bilayer structure RRAM. We deduced that occurrence of conductive filament connection/rupture at the interface of the HfO 2 and TiO 2 , in combination with the HfO 2 acting as a virtual cathode, led to the improved uniformity. A multilevel storage capability can be obtained by varying the stop voltage in the RESET process for bilayer HfO 2 /TiO 2 RRAM. By analyzing the current conduction mechanism, we demonstrated that the multilevel high resistance state (HRS) was attributable to the increased barrier height when the stop voltage was increased.
The task of event extraction contains subtasks including detections for entity mentions, event triggers and argument roles. Traditional methods solve them as a pipeline, which does not make use of task correlation for their mutual benefits. There have been recent efforts towards building a joint model for all tasks. However, due to technical challenges, there has not been work predicting the joint output structure as a single task. We build a first model to this end using a neural transition-based framework, incrementally predicting complex joint structures in a state-transition process. Results on standard benchmarks show the benefits of the joint model, which gives the best result in the literature.
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