Matching Items (3)
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- Creators: Allee, David R.
- All Subjects: pmc
- All Subjects: TCAD
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
Flash memories are critical for embedded devices to operate properly but are susceptible to radiation effects, which make flash memory a key factor to improve the reliability of circuitry. This thesis describes the simulation techniques used to analyze and predict total ionizing dose (TID) effects on 90-nm technology Silicon Storage Technology (SST) SuperFlash Generation 3 devices. Silvaco Atlas is used for both device level design and simulation purposes.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.
The simulations consist of no radiation and radiation modeling. The no radiation modeling details the cell structure development and characterizes basic operations (read, erase and program) of a flash memory cell. The program time is observed to be approximately 10 μs while the erase time is approximately 0.1 ms.
The radiation modeling uses the fixed oxide charge method to analyze the TID effects on the same flash memory cell. After irradiation, a threshold voltage shift of the flash memory cell is observed. The threshold voltages of a programmed cell and an erased cell are reduced at an average rate of 0.025 V/krad.
The use of simulation techniques allows designers to better understand the TID response of a SST flash memory cell and to predict cell level TID effects without performing the costly in-situ irradiation experiments. The simulation and experimental results agree qualitatively. In particular, simulation results reveal that ‘0’ to ‘1’ errors but not ‘1’ to ‘0’ retention errors occur; likewise, ‘0’ to ‘1’ errors dominate experimental testing, which also includes circuitry effects that can cause ‘1’ to ‘0’ failures. Both simulation and experimental results reveal flash memory cell TID resilience to about 200 krad.
ContributorsChen, Yitao (Author) / Holbert, Keith E. (Thesis advisor) / Clark, Lawrence T. (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2016
Description
Nonvolatile memory (NVM) technologies have been an integral part of electronic systems for the past 30 years. The ideal non-volatile memory have minimal physical size, energy usage, and cost while having maximal speed, capacity, retention time, and radiation hardness. A promising candidate for next-generation memory is ion-conducting bridging RAM which is referred to as programmable metallization cell (PMC), conductive bridge RAM (CBRAM), or electrochemical metallization memory (ECM), which is likely to surpass flash memory in all the ideal memory characteristics. A comprehensive physics-based model is needed to completely understand PMC operation and assist in design optimization.
To advance the PMC modeling effort, this thesis presents a precise physical model parameterizing materials associated with both ion-rich and ion-poor layers of the PMC's solid electrolyte, so that captures the static electrical behavior of the PMC in both its low-resistance on-state (LRS) and high resistance off-state (HRS). The experimental data is measured from a chalcogenide glass PMC designed and manufactured at ASU. The static on- and off-state resistance of a PMC device composed of a layered (Ag-rich/Ag-poor) Ge30Se70 ChG film is characterized and modeled using three dimensional simulation code written in Silvaco Atlas finite element analysis software. Calibrating the model to experimental data enables the extraction of device parameters such as material bandgaps, workfunctions, density of states, carrier mobilities, dielectric constants, and affinities.
The sensitivity of our modeled PMC to the variation of its prominent achieved material parameters is examined on the HRS and LRS impedance behavior.
The obtained accurate set of material parameters for both Ag-rich and Ag-poor ChG systems and process variation verification on electrical characteristics enables greater fidelity in PMC device simulation, which significantly enhances our ability to understand the underlying physics of ChG-based resistive switching memory.
To advance the PMC modeling effort, this thesis presents a precise physical model parameterizing materials associated with both ion-rich and ion-poor layers of the PMC's solid electrolyte, so that captures the static electrical behavior of the PMC in both its low-resistance on-state (LRS) and high resistance off-state (HRS). The experimental data is measured from a chalcogenide glass PMC designed and manufactured at ASU. The static on- and off-state resistance of a PMC device composed of a layered (Ag-rich/Ag-poor) Ge30Se70 ChG film is characterized and modeled using three dimensional simulation code written in Silvaco Atlas finite element analysis software. Calibrating the model to experimental data enables the extraction of device parameters such as material bandgaps, workfunctions, density of states, carrier mobilities, dielectric constants, and affinities.
The sensitivity of our modeled PMC to the variation of its prominent achieved material parameters is examined on the HRS and LRS impedance behavior.
The obtained accurate set of material parameters for both Ag-rich and Ag-poor ChG systems and process variation verification on electrical characteristics enables greater fidelity in PMC device simulation, which significantly enhances our ability to understand the underlying physics of ChG-based resistive switching memory.
ContributorsRajabi, Saba (Author) / Barnaby, Hugh (Thesis advisor) / Kozicki, Michael (Committee member) / Vasileska, Dragica (Committee member) / Arizona State University (Publisher)
Created2014