HFO2-based resistance switching non-volatile random access memory : low power operation and reduced variability
- We have entered an era of "Big Data" in which the amounts of data being generated and stored is rapidly exceeding exascale. Information collected by various sensors, user data, personal information, and internet all have led to this rapid increase of stored information. In fact, not only has the amount of data increased drastically, but the nature of this data has changed as well. Computation is now required to revolve around this new data and traditional algorithms of predicting more frequently accessible data are now proving less useful. These changes have made memory capacity, performance, and reliability improvement more critical than ever. The prospect of finding a Storage Class Memory (SCM) and its potential revolutionary impact on computer architecture has driven many researchers to investigate various alternatives to current FLASH based memory. As such, in this data-centric era efforts are being made to introduce emerging memory solutions that may bring about new level in the current memory hierarchy. Resistance-change based random access memory (RRAM) based on Transition Metal Oxides (TMOs), whose operation is based on the change in resistivity due to the formation of a conductive filament in the oxide material, has attracted attention in recent years because of its potential for high density, high speed, and good retention as a novel nonvolatile memory. However, achieving low power operation and high device-to-device uniformity in the cell resistance states are the major challenges for practical applications of RRAM technology. While certain progress has been made in understanding the switching mechanism of TMO memory devices, lack of precise control of the filament formation, perceived to be a random process, introduces variability into the switching characteristics of this class of devices, hindering further progress. In this thesis we address these major issues in HfO2-based RRAM devices. In this dissertation we address the problem variability and reducing switching power by proposing a constant voltage forming (CVF) method. The method is shown to increase the resistances of the low resistance and high resistance states while reducing their variability. By forcing the forming in all devices to occur at the same predefined voltage, the CVF method is demonstrated to eliminate a major cause of the device-to-device variation associated with the randomness of the forming voltage values. Moreover, both experiments and simulations show that CVF at lower voltages suppresses the parasitic overshoot current, resulting in a more controlled and smaller filament cross-section and lower operation currents. Further, electrical and physical characterization of the HfO2 RRAM devices is demonstrated, presenting physical evidence for a filament in HfO2 RRAM using scanning transmission electron microscopy. A 'deep reset' phenomenon is observed electrically for ultra-short pulses at larger voltages otherwise not observable using longer pulse times. The interplay of breakdown and recombination forces for hafnium and oxygen ions is suggested to explain this observed phenomenon. Finally, we present a detailed model for the reset process kinetics in HfO2-based RRAM describing the transition between low and high resistance states at the atomic level. Based on the filament characteristics as observed by TEM, the kinetics of the reset operation is then simulated using our developed Kinetic Monte Carlo (KMC) method incorporating ab-initio calculated microscopic characteristics of the oxygen ions in hafnia. Temperature and field driven oxygen diffusion in the oxide surrounding the filament is shown to provide the needed supply of oxygen to re-oxidize the tip of the filament and switch the device back to the High Resistance State (HRS). Using this developed model and KMC simulator, the dependence of reset process on surrounding interstitial oxygen ion concentration, reset pulse width, and reset pulse height is studied and the variability of the resulting HRS state is simulated.
|Type of resource
|electronic; electronic resource; remote
|1 online resource.
|Stanford University, Department of Electrical Engineering.
|Nishi, Yoshio, 1940-
|Nishi, Yoshio, 1940-
|Wong, S. Simon
|Wong, S. Simon
|Statement of responsibility
|Submitted to the Department of Electrical Engineering.
|Thesis (Ph.D.)--Stanford University, 2015.
- © 2015 by Asad Kalantarian
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
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