Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective
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AuthorMaldonado Correa, David; Aldana Delgado, Samuel; González, M. B.; Jiménez Molinos, Francisco; Ibáñez Pérez, María José; Barrera Rosillo, Domingo; Campabadal, F.; Roldán Aranda, Juan Bautista
Resistive switching memoryRRAMParameter extractionKinetic Monte Carlo simulationVariabilityModelingNumerical techniques
D. Maldonado et al. Variability estimation in resistive switching devices, a numerical and kinetic Monte Carlo perspective. Microelectronic Engineering 257 (2022) 111736 [https://doi.org/10.1016/j.mee.2022.111736]
SponsorshipSpanish Ministry of Science, Innovation and Universities and the FEDER program through projects TEC2017-84321-C4-1-R, TEC2017-84321-C4-3-R; Consejería de Conocimiento, Investigación y Universidad, Junta de Andalucía (Spain) and the FEDER program, projects A.TIC.117.UGR18, IE2017-5414 and B.TIC.624.UGR20; Funding for open access charge: Universidad de Granada/CBUA
We have analyzed variability in resistive memories (Resistive Random Access Memories, RRAMs) making use of advanced numerical techniques to process experimental measurements and simulations based on the kinetic Monte Carlo technique. The devices employed in the study were fabricated using the TiN/Ti/HfO2/W stack. The switching parameters were obtained making use of new developed extraction methods. The appropriateness of the advanced parameter extraction methodologies has been checked by comparison to kinetic Monte Carlo simulations; in particular, the reset and set events have been studied and detected. The data obtained were employed to shed light on the resistive switching operation and the cycle-to-cycle variability. It has been shown that variability depends on the numerical technique employed to obtain the set and reset voltages, therefore, this issue must be taken into consideration in RS characterization and modeling studies. The proposed techniques are complementary and depending on the technology and the curves shape the features of a particular method could make it to be the most appropriate.