Matching Items (6)
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
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
Description
Programmable Metallization Cell (PMC) is a technology platform which utilizes mass transport in solid or liquid electrolyte coupled with electrochemical (redox) reactions to form or remove nanoscale metallic electrodeposits on or in the electrolyte. The ability to redistribute metal mass and form metallic nanostructure in or on a structure in situ, via the application of a bias on laterally placed electrodes, creates a large number of promising applications. A novel PMC-based lateral microwave switch was fabricated and characterized for use in microwave systems. It has demonstrated low insertion loss, high isolation, low voltage operation, low power and low energy consumption, and excellent linearity. Due to its non-volatile nature the switch operates with fewer biases and its simple planar geometry makes possible innovative device structures which can be potentially integrated into microwave power distribution circuits. PMC technology is also used to develop lateral dendritic metal electrodes. A lateral metallic dendritic network can be grown in a solid electrolyte (GeSe) or electrodeposited on SiO2 or Si using a water-mediated method. These dendritic electrodes grown in a solid electrolyte (GeSe) can be used to lower resistances for applications like self-healing interconnects despite its relatively low light transparency; while the dendritic electrodes grown using water-mediated method can be potentially integrated into solar cell applications, like replacing conventional Ag screen-printed top electrodes as they not only reduce resistances but also are highly transparent. This research effort also laid a solid foundation for developing dendritic plasmonic structures. A PMC-based lateral dendritic plasmonic structure is a device that has metallic dendritic networks grown electrochemically on SiO2 with a thin layer of surface metal nanoparticles in liquid electrolyte. These structures increase the distribution of particle sizes by connecting pre-deposited Ag nanoparticles into fractal structures and result in three significant effects, resonance red-shift, resonance broadening and resonance enhancement, on surface plasmon resonance for light trapping simultaneously, which can potentially enhance thin film solar cells' performance at longer wavelengths.
ContributorsRen, Minghan (Author) / Kozicki, Michael (Thesis advisor) / Schroder, Dieter (Committee member) / Roedel, Ronald (Committee member) / Barnaby, Hugh (Committee member) / Arizona State University (Publisher)
Created2011
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
Description
Interposers have been used in the system packaging industry for years. They have advanced from basic devices used for connection to providing new opportunities for System-in-Package and System-on-Chip architectures. Currently interposers cannot be reconfigured. Systems may implement extra input-output connections for hard reconfiguration. However, programmable metallization cells (PMC) offer the opportunity to change this. PMCs offer reliable and fast switching that has the potential to be used as resistive memory cells as well. PMCs operate by growing a metal filament from the device cathode to its anode through a solid electrolyte by applying a voltage. By reversing the voltage bias, the filament will retract. The PMC’s electrolyte can also be made from a range of materials being chalcogen or oxide based, allowing for integration in a variety of systems. By utilizing PMCs in an interposer to create a “smart interposer,” it would be possible to create easily reconfigurable systems. This project investigated how PMCs function in a lab setting. By using a probe station, the current-voltage characteristics were generated for a variety of limiting current values. The PMC on and off state resistances were extrapolated for further understanding of its switch function. In addition, works-like prototypes were developed to show the function a smart interposer. In these prototypes, transistors or relays were used as the switching mechanism in place of the PMCs. The final works-like prototype demonstrated how a smart interposer might function by using a switching mechanism to swap between half adder and full adder outputs for the same inputs.
ContributorsSpiker, Bradley Dahlton (Author) / Kozicki, Michael (Thesis director) / Gonzalez Velo, Yago (Committee member) / Electrical Engineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-05