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Title: Probing the resistance switching mechanism in silicon suboxide memory devices
Author: Buckwell, Mark
ISNI:       0000 0004 7231 7576
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2018
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Redox-based resistive random access memory has the scope to greatly improve upon current electronic data storage, though the mechanism by which devices operate is not understood completely. In particular, the connection between oxygen migration, the formation of conductive filaments and device longevity is still disputed. Here, I used atomic force microscopy, scanning electron microscopy and x-ray photoelectron spectroscopy to characterise the growth of filaments and the movement of oxygen in silicon-rich silicon oxide memory devices. As such, I was able to establish some of the chemical and structural differences between states of different resistance, which would correspond to binary data storage states. The oxide active layer is reduced simultaneously to the appearance of surface distortion and volumes of high conductivity in an otherwise-insulating material. These results support the established model of a resistance switching mechanism that relies on the migration of oxygen ions under an electrical bias, forming conductive pathways in the switching material. Notably, I demonstrate a reduction in the active layer stoichiometry as a result of electrical stress and show for the first time the presence of multiple filamentary growths in three dimensions in an intrinsic switching material. In addition, I have proven the efficacy of an extension to the method of profiling conductivity variations in insulators in three dimensions using conductive atomic force microscopy. However, in this case my findings conflict with the status quo of this methodology. In particular, I demonstrate that the measurement process significantly affects the scanning probe, leading to the likelihood of data inaccuracy. This highlights the needed for further development of the technique and careful analysis of the data obtained.
Supervisor: Kenyon, A. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available