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- All Subjects: pmc
- Creators: Kozicki, Michael N
- Creators: Alford, Dr. Terry
Description
Advances in software and applications continue to demand advances in memory. The ideal memory would be non-volatile and have maximal capacity, speed, retention time, endurance, and radiation hardness while also having minimal physical size, energy usage, and cost. The programmable metallization cell (PMC) is an emerging memory technology that is likely to surpass flash memory in all the listed ideal memory characteristics. A comprehensive physics-based model is needed to fully understand PMC operation and aid in design optimization. With the intent of advancing the PMC modeling effort, this thesis presents two simulation models for the PMC. The first model is a finite element model based on Silvaco Atlas finite element analysis software. Limitations of the software are identified that make this model inconsistent with the operating mechanism of the PMC. The second model is a physics-based numerical model developed for the PMC. This model is successful in matching data measured from a chalcogenide glass PMC designed and manufactured at ASU. Matched operating characteristics observable in the current and resistance vs. voltage data include the OFF/ON resistances and write/erase and electrodeposition voltage thresholds. Multilevel programming is also explained and demonstrated with the numerical model. The numerical model has already proven useful by revealing some information presented about the operation and characteristics of the PMC.
ContributorsOleksy, David Ryan (Author) / Barnaby, Hugh J (Thesis advisor) / Kozicki, Michael N (Committee member) / Edwards, Arthur H (Committee member) / Arizona State University (Publisher)
Created2013
Description
The formation of dendrites in materials is usually seen as a failure-inducing defect in devices. Naturally, most research views dendrites as a problem needing a solution while focusing on process control techniques and post-mortem analysis of various stress patterns with the ultimate goal of total suppression of the structures. However, programmable metallization cell (PMC) technology embraces dendrite formation in chalcogenide glasses by utilizing the nascent conductive filaments as its core operative element. Furthermore, exciting More-than-Moore capabilities in the realms of device watermarking and hardware encryption schema are made possible by the random nature of dendritic branch growth. While dendritic structures have been observed and are well-documented in solid state materials, there is still no satisfactory theoretical model that can provide insight and a better understanding of how dendrites form. Ultimately, what is desired is the capability to predict the final structure of the conductive filament in a PMC device so that exciting new applications can be developed with PMC technology.
This thesis details the results of an effort to create a first-principles MATLAB simulation model that uses configurable physical parameters to generate images of dendritic structures. Generated images are compared against real-world samples. While growth has a significant random component, there are several reliable characteristics that form under similar parameter sets that can be monitored such as the relative length of major dendrite arms, common branching angles, and overall growth directionality.
The first simulation model that was constructed takes a Newtonian perspective of the problem and is implemented using the Euler numerical method. This model has several shortcomings stemming majorly from the simplistic treatment of the problem, but is highly performant. The model is then revised to use the Verlet numerical method, which increases the simulation accuracy, but still does not fully resolve the issues with the theoretical background. The final simulation model returns to the Euler method, but is a stochastic model based on Mott-Gurney’s ion hopping theory applied to solids. The results from this model are seen to match real samples the closest of all simulations.
This thesis details the results of an effort to create a first-principles MATLAB simulation model that uses configurable physical parameters to generate images of dendritic structures. Generated images are compared against real-world samples. While growth has a significant random component, there are several reliable characteristics that form under similar parameter sets that can be monitored such as the relative length of major dendrite arms, common branching angles, and overall growth directionality.
The first simulation model that was constructed takes a Newtonian perspective of the problem and is implemented using the Euler numerical method. This model has several shortcomings stemming majorly from the simplistic treatment of the problem, but is highly performant. The model is then revised to use the Verlet numerical method, which increases the simulation accuracy, but still does not fully resolve the issues with the theoretical background. The final simulation model returns to the Euler method, but is a stochastic model based on Mott-Gurney’s ion hopping theory applied to solids. The results from this model are seen to match real samples the closest of all simulations.
ContributorsFoss, Ryan (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Programmable Metallization Cell (PMC) technology has been shown to possess the necessary qualities for it to be considered as a leading contender for the next generation memory. These qualities include high speed and endurance, extreme scalability, ease of fabrication, ultra low power operation, and perhaps most importantly ease of integration with the CMOS back end of line (BEOL) process flow. One area where detailed study is lacking is the reliability of PMC devices. In previous reliability work, the low and high resistance states were monitored for periods of hours to days without any applied voltage and the results were extrapolated to several years (>10) but little has been done to analyze the low resistance state under stress. With or without stress, the low resistance state appears to be highly stable but a gradual increase in resistance with time, less than one order of magnitude after ten years when extrapolated, has been observed. It is important to understand the physics behind this resistance rise mechanism to comprehend the reliability issues associated with the low resistance state. This is also related to the erase process in PMC cells where the transition from the ON to OFF state occurs under a negative voltage. Hence it is important to investigate this erase process in PMC cells under different conditions and to model it. Analyzing the programming and the erase operations separately is important for any memory technology but its ability to cycle efficiently (reliably) at low voltages and for more than 1E4 cycles (without affecting the cells performance) is more critical. Future memory technologies must operate with the low power supply voltages (<1V) required for small geometry nodes. Low voltage programming of PMC memory devices has previously been demonstrated using slow voltage sweeps and small numbers of fast pulses. In this work PMC memory cells were cycled at low voltages using symmetric pulses with different load resistances and the distribution of the ON and OFF resistances was analyzed. The effect of the program current used during the program-erase cycling on the resulting resistance distributions is also investigated. Finally the variation found in the behavior of similar resistance ON states in PMC cells was analyzed more in detail and measures to reduce this variation were looked into. It was found that slow low current programming helped reducing the variation in erase times of similar resistance ON states in PMC cells. This scheme was also used as a pre-conditioning technique and the improvements in subsequent cycling behavior were compared.
ContributorsKamalanathan, Deepak (Author) / Kozicki, Dr. Michael (Thesis advisor) / Schroder, Dr. Dieter (Committee member) / Goryll, Dr. Michael (Committee member) / Alford, Dr. Terry (Committee member) / Arizona State University (Publisher)
Created2011