A Cellular Automata Approach for the Simulation and Development of Advanced Phase Change Memory Devices

摘要

Phase change devices in both optical and electrical formats have been subject of intenseresearch since their discovery by Ovshinsky in the early 1960â\u80\u99s. They have revolutionizedthe technology of optical data storage and have very recently been adopted fornon-volatile semiconductor memories. Their great success relies on their remarkableproperties enabling high-speed, low power consumption and stable retention. Nevertheless,their full potential is still yet to be realized.Operations in electrical phase change devices rely on the large resistivity contrast betweenthe crystalline (low resistance) and amorphous (high resistance) structures. Theunderlying mechanisms of phase transformations and the relation between structuraland electrical properties in phase change materials are quite complex and need to beunderstood more deeply. For this purpose, we compare different approaches to mathematicalmodelling that have been suggested to realistically simulate the crystallizationand amorphization of phase change materials. In this thesis the recently introducedGillespie Cellular Automata (GCA) approach is used to obtain direct simulation of thestructural phases and the electrical states of phase change materials and devices. TheGCA approach is a powerful technique to understand the nanostructure evolution duringthe crystallization (SET) and amorphization (RESET) processes in phase change devicesover very wide length scales. Using this approach, a detailed study of the electrical propertiesand nanostructure dynamics during SET and RESET processes in a PCRAM cellis presented.Besides the possibility of binary storage in phase change memory devices, there is awider and far-reaching potential for using them as the basis for new forms of arithmeticand cognitive computing. The origin of such potential lies in a previously under-explored property, namely accumulation which has the potential to implement basic arithmeticcomputations. We exploit and explore this accumulative property in films and devices.Furthermore, we also show that the same accumulation property can be used to mimic asimple integrate and fire neuron. Thus by combining both a phase change cell operatingin the accumulative regime for the neural body and a phase change cell in the multilevelregime for the synaptic weighting an artificial neuromorphic system can be obtained.This may open a new route for the realization of phase change based cognitive computers.This thesis also examines the relaxation oscillations observed under suitable biasconditions in phase change devices. The results presented are performed through acircuit analysis in addition with a generation and recombination mechanism driven bythe electric field and carrier densities. To correctly model the oscillations we show thatit is necessary to include a parasitic inductance.Related to the electrical states of phase change materials and devices is the thresholdswitching of the amorphous phase at high electric fields and recent work has suggestedthat such threshold switching is the result of field-induced nucleation. An electric fieldinduced nucleation mechanism is incorporated into the GCA approach by adding electricfield dependence to the free energy of the system. Using results for a continuous phasechange thin films and PCRAM devices we show that a purely electronic explanation ofthreshold switching, rather than field-induced nucleation, provides threshold fields closerto experimentally measured values.