A Study of the Scaling and Advanced Functionality Potential of Phase Change Memory Devices
Thesis or dissertation
University of Exeter
As traditional volatile and non-volatile data storage and memory technologies such as SRAM, DRAM, Flash and HDD face fundamental scaling challenges, scientists and engineers are forced to search for and develop alternative technologies for future electronic and computing systems that are relatively free from scaling issues, have lower power consumptions, higher storage densities, faster speeds, and can be easily integrated on-chip with microprocessor cores. This thesis focuses on the scaling and advanced functionality potential of one such memory technology i.e. Phase Change Memory (PCM), which is a leading contender to complement or even replace the above mentioned traditional technologies. In the first part of the thesis, a physically-realistic Multiphysics Cellular Automata PCM device modelling approach was used to study the scaling potential of conventional and commercially-viable PCM devices. It was demonstrated that mushroom-type and patterned probe PCM devices can indeed be scaled down to ultrasmall (single-nanometer) dimensions, and in doing so, ultralow programming currents (sub-20 μA) and ultrahigh storage densities (~10 Tb/in2) can be achieved via such a scaling process. Our sophisticated modelling approach also provided a detailed insight into some key PCM device characteristics, such as amorphization (Reset) and crystallization (Set) kinetics, thermal confinement, and the important resistance window i.e. difference in resistances between the Reset and Set states. In the second part of the thesis, the aforementioned modelling approach was used to assess the feasibility of some advanced functionalities of PCM devices, such as neuromorphic computing and phase change metadevices. It was demonstrated that by utilizing the accumulation mode of operation inherent to phase change materials, we can combine a physical PCM device with an external comparator-type circuit to deliver a ‘self-resetting spiking phase change neuron’, which when combined with phase change synapses can potentially open a new route for the realization of all-phase change neuromorphic computers. It was further shown that it is indeed feasible to design and ‘electrically’ switch practicable phase change metadevices (for absorber and modulator applications, and suited to operation in the technologically important near-infrared range of the spectrum). Finally, it was demonstrated that the Gillespie Cellular Automata (GCA) phase change model is capable of exhibiting ‘non-Arrhenius kinetics of crystallization’, which were found to be in good agreement with reported experimental studies.
Wright, C. David
PhD in Engineering