Applied Physics Letters · 2023 · 27 citations · 34 references
EngineeringMaterials EngineeringMaterials ScienceElectronic MaterialsMicroelectronicsThin FilmsCurrent-voltage CharacteristicsDevice CharacterizationDevice ModelingDevice ScalingMemory DevicesMemristive MaterialsConductionCurrent-voltage CharacterizationCurrent-voltage RelationsCurrent-voltage RelationshipOhmic ConductionResistive Random-access MemoryScaling EffectsSpace-charge-limited Current
HfO2-based resistive random-access memory devices are promising candidates for new memory and computing applications. Hereby, scaling of the devices is a key issue, where overall fundamental switching and conduction mechanisms can be easily influenced by changes in the oxide layer thickness. This work addresses the oxide thickness-dependent resistive switching characteristics in Cu/HfO2/Pt memory devices through bipolar DC switching characterization. Forming, reset, and set characteristics are investigated depending on the oxide layer thickness, revealing a significant difference for thicker compared to thinner films. Thicker samples tend to show a more abrupt reset behavior and a larger set voltage variance, while for thinner samples, a more gradual reset behavior and a low set variance is found. These phenomena can be explained by a model based on thermally assisted electrochemical metallization. Furthermore, to understand the conduction mechanism of the devices, current–voltage curves of the set process were investigated. The devices are found to have an Ohmic conduction mechanism in the lower voltage region generally, while thinner samples tend to show an additional space-charge-limited current conduction mechanism in a higher voltage region.
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Resistive switching in transition metal oxides
Akihito Sawa · Materials Today · 2008 · 2.9K citations · Full text
Ferroelectricity in hafnium oxide thin films
T. S. Böscke, Johannes Müller, D. Bräuhaus et al. · Applied Physics Letters · 2011 · 2.7K citations
Natural Sciences, Materials Engineering, Materials Science +17
Neuromorphic computing using non-volatile memory
Geoffrey W. Burr, R. M. Shelby, Abu Sebastian et al. · Advances in Physics X · 2016 · 1.1K citations · Full text