Simulating Radial Dendrite Growth

abstract: 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...

Full description

Bibliographic Details
Other Authors: Foss, Ryan Martin (Author)
Format: Dissertation
Language:English
Published: 2016
Subjects:
PMC
Online Access:http://hdl.handle.net/2286/R.I.40742
id ndltd-asu.edu-item-40742
record_format oai_dc
spelling ndltd-asu.edu-item-407422018-06-22T03:07:55Z Simulating Radial Dendrite Growth abstract: 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. Dissertation/Thesis Foss, Ryan Martin (Author) Kozicki, Michael N (Advisor) Barnaby, Hugh (Committee member) Allee, David R (Committee member) Arizona State University (Publisher) Electrical engineering Dendrite Growth Dendrite Morphology Mott-Gurney Ion Hopping PMC Radial Growth Simulation Model eng 65 pages Masters Thesis Electrical Engineering 2016 Masters Thesis http://hdl.handle.net/2286/R.I.40742 http://rightsstatements.org/vocab/InC/1.0/ All Rights Reserved 2016
collection NDLTD
language English
format Dissertation
sources NDLTD
topic Electrical engineering
Dendrite Growth
Dendrite Morphology
Mott-Gurney Ion Hopping
PMC
Radial Growth
Simulation Model
spellingShingle Electrical engineering
Dendrite Growth
Dendrite Morphology
Mott-Gurney Ion Hopping
PMC
Radial Growth
Simulation Model
Simulating Radial Dendrite Growth
description abstract: 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. === Dissertation/Thesis === Masters Thesis Electrical Engineering 2016
author2 Foss, Ryan Martin (Author)
author_facet Foss, Ryan Martin (Author)
title Simulating Radial Dendrite Growth
title_short Simulating Radial Dendrite Growth
title_full Simulating Radial Dendrite Growth
title_fullStr Simulating Radial Dendrite Growth
title_full_unstemmed Simulating Radial Dendrite Growth
title_sort simulating radial dendrite growth
publishDate 2016
url http://hdl.handle.net/2286/R.I.40742
_version_ 1718701293133889536