Matching Items (5)
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- All Subjects: pmc
- Creators: Barnaby, Hugh
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
In today's world there is a great need for sensing methods as tools to provide critical information to solve today's problems in security applications. Real time detection of trace chemicals, such as explosives, in a complex environment containing various interferents using a portable device that can be reliably deployed in a field has been a difficult challenge. A hybrid nanosensor based on the electrochemical reduction of trinitrotoluene (TNT) and the interaction of the reduction products with conducting polymer nanojunctions in an ionic liquid was fabricated. The sensor simultaneously measures the electrochemical current from the reduction of TNT and the conductance change of the polymer nanojunction caused from the reduction product. The hybrid detection mechanism, together with the unique selective preconcentration capability of the ionic liquid, provides a selective, fast, and sensitive detection of TNT. The sensor, in its current form, is capable of detecting parts per trillion level TNT in the presence of various interferents within a few minutes. A novel hybrid electrochemical-colorimetric (EC-C) sensing platform was also designed and fabricated to meet these challenges. The hybrid sensor is based on electrochemical reactions of trace explosives, colorimetric detection of the reaction products, and unique properties of the explosives in an ionic liquid (IL). This approach affords not only increased sensitivity but also selectivity as evident from the demonstrated null rate of false positives and low detection limits. Using an inexpensive webcam a detection limit of part per billion in volume (ppbV) has been achieved and demonstrated selective detection of explosives in the presence of common interferences (perfumes, mouth wash, cleaners, petroleum products, etc.). The works presented in this dissertation, were published in the Journal of the American Chemical Society (JACS, 2009) and Nano Letters (2010), won first place in the National Defense Research contest in (2009) and has been granted a patent (WO 2010/030874 A1). In addition, other work related to conductive polymer junctions and their sensing capabilities has been published in Applied Physics Letters (2005) and IEEE sensors journal (2008).
ContributorsDiaz Aguilar, Alvaro (Author) / Tao, Nongjian (Thesis advisor) / Tsui, Raymond (Committee member) / Barnaby, Hugh (Committee member) / Yu, Hongbin (Committee member) / Arizona State University (Publisher)
Created2012
Description
This paper summarizes the [1] ideas behind, [2] needs, [3] development, and [4] testing of 3D-printed sensor-stents known as Stentzors. This sensor was successfully developed entirely from scratch, tested, and was found to have an output of 3.2*10-6 volts per RMS pressure in pascals. This paper also recommends further work to render the Stentzor deployable in live subjects, including [1] further design optimization, [2] electrical isolation, [3] wireless data transmission, and [4] testing for aneurysm prevention.
ContributorsMeidinger, Aaron Michael (Author) / LaBelle, Jeffrey (Thesis director) / Frakes, David (Committee member) / Barrett, The Honors College (Contributor) / Mechanical and Aerospace Engineering Program (Contributor)
Created2014-05
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