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- All Subjects: programmable metallization cell
- All Subjects: pmc
- Creators: Kozicki, Michael N
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
Programmable metallization cell (PMC) technology employs the mechanisms of metal ion transport in solid electrolytes (SE) and electrochemical redox reactions in order to form metallic electrodeposits. When a positive bias is applied to an anode opposite to a cathode, atoms at the anode are oxidized to ions and dissolve into the SE. Under the influence of the electric field, the ions move to the cathode and become reduced to form the electrodeposits. These electrodeposits are filamentary in nature and persistent, and since they are metallic can alter the physical characteristics of the material on which they are formed. PMCs can be used as next generation memories, radio frequency (RF) switches and physical unclonable functions (PUFs).
The morphology of the filaments is impacted by the biasing conditions. Under a relatively high applied electric field, they form as dendritic elements with a low fractal dimension (FD), whereas a low electric field leads to high FD features. Ion depletion effects in the SE due to low ion diffusivity/mobility also influences the morphology by limiting the ion supply into the growing electrodeposit.
Ion transport in SE is due to hopping transitions driven by drift and diffusion force. A physical model of ion hopping with Brownian motion has been proposed, in which the ion transitions are random when time window is larger than characteristic time. The random growth process of filaments in PMC adds entropy to the electrodeposition, which leads to random features in the dendritic patterns. Such patterns has extremely high information capacity due to the fractal nature of the electrodeposits.
In this project, lateral-growth PMCs were fabricated, whose LRS resistance is less than 10Ω, which can be used as RF switches. Also, an array of radial-growth PMCs was fabricated, on which multiple dendrites, all with different shapes, could be grown simultaneously. Those patterns can be used as secure keys in PUFs and authentication can be performed by optical scanning.
A kinetic Monte Carlo (KMC) model is developed to simulate the ion transportation in SE under electric field. The simulation results matched experimental data well that validated the ion hopping model.
The morphology of the filaments is impacted by the biasing conditions. Under a relatively high applied electric field, they form as dendritic elements with a low fractal dimension (FD), whereas a low electric field leads to high FD features. Ion depletion effects in the SE due to low ion diffusivity/mobility also influences the morphology by limiting the ion supply into the growing electrodeposit.
Ion transport in SE is due to hopping transitions driven by drift and diffusion force. A physical model of ion hopping with Brownian motion has been proposed, in which the ion transitions are random when time window is larger than characteristic time. The random growth process of filaments in PMC adds entropy to the electrodeposition, which leads to random features in the dendritic patterns. Such patterns has extremely high information capacity due to the fractal nature of the electrodeposits.
In this project, lateral-growth PMCs were fabricated, whose LRS resistance is less than 10Ω, which can be used as RF switches. Also, an array of radial-growth PMCs was fabricated, on which multiple dendrites, all with different shapes, could be grown simultaneously. Those patterns can be used as secure keys in PUFs and authentication can be performed by optical scanning.
A kinetic Monte Carlo (KMC) model is developed to simulate the ion transportation in SE under electric field. The simulation results matched experimental data well that validated the ion hopping model.
ContributorsYu, Weijie (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh (Thesis advisor) / Diaz, Rodolfo (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2015
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
The Programmable Metallization Cell (PMC) is a novel solid-state resistive switching technology. It has a simple metal-insulator-metal “MIM” structure with one metal being electrochemically active (Cu) and the other one being inert (Pt or W), an insulating film (silica) acts as solid electrolyte for ion transport is sandwiched between these two electrodes. PMC’s resistance can be altered by an external electrical stimulus. The change of resistance is attributed to the formation or dissolution of Cu metal filament(s) within the silica layer which is associated with electrochemical redox reactions and ion transportation. In this dissertation, a comprehensive study of microfabrication method and its impacts on performance of PMC device is demonstrated, gamma-ray total ionizing dose (TID) impacts on device reliability is investigated, and the materials properties of doped/undoped silica switching layers are illuminated by impedance spectroscopy (IS). Due to the inherent CMOS compatibility, Cu-silica PMCs have great potential to be adopted in many emerging technologies, such as non-volatile storage cells and selector cells in ultra-dense 3D crosspoint memories, as well as electronic synapses in brain-inspired neuromorphic computing. Cu-silica PMC device performance for these applications is also assessed in this dissertation.
ContributorsChen, Wenhao (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh J (Thesis advisor) / Yu, Shimeng (Committee member) / Thornton, Trevor (Committee member) / Arizona State University (Publisher)
Created2017
Description
Programmable Metallization Cell (PMC) devices are, in essence, redox-based
solid-state resistive switching devices that rely on ion transport through a solid electrolyte (SE) layer from anode to cathode. Analysis and modeling of the effect of different fabrication and processing parameter/conditions on PMC devices are crucial for future electronics. Furthermore, this work is even more significant for devices utilizing back-end- of-line (BEOL) compatible materials such as Cu, W, their oxides and SiOx as these devices offer cost effectiveness thanks to their inherent foundry-ready nature. In this dissertation, effect of annealing conditions and cathode material on the performance of Cu-SiOx vertical devices is investigated which shows that W-based devices have much lower forming voltage and initial resistance values. Also, higher annealing temperatures first lead to an increase in forming voltage from 400 °C to 500 °C, then a drastic decrease at 550 °C due to Cu island formation at the Cu/SiOx interface. Next, the characterization and modeling of the bilayer Cu2O/Cu-WO3 obtained by annealing the deposited Cu/WO3 stacks in air at BEOL-compatible temperatures is presented that display unique characteristics for lateral PMC devices. First, thin film oxidation kinetics of Cu is studied which show a parabolic relationship with annealing time and an activation energy of 0.70 eV. Grown Cu2O shows a cauliflower-like morphology where feature size on the surface increase with annealing time and temperature. Then, diffusion kinetics of Cu in WO3 is examined where the activation energy of diffusion of Cu into WO3 is calculated to be 0.74 eV. Cu was found to form clusters in the WO3 host which was revealed by imaging. Moreover, using the oxidation and diffusion analyses, a Matlab model is established for modeling the bilayer for process and annealing-condition optimization. The model is built to produce the resulting Cu2O thickness and Cu concentration in Cu-WO3. Additionally, material characterization, preliminary electrical results along with modeling of lateral PMC devices utilizing the bilayer is also demonstrated. By tuning the process parameters such as deposited Cu thickness and annealing conditions, a low-resistive Cu2O layer was achieved which dramatically enhanced the electrodeposition growth rate for lateral PMC devices.
solid-state resistive switching devices that rely on ion transport through a solid electrolyte (SE) layer from anode to cathode. Analysis and modeling of the effect of different fabrication and processing parameter/conditions on PMC devices are crucial for future electronics. Furthermore, this work is even more significant for devices utilizing back-end- of-line (BEOL) compatible materials such as Cu, W, their oxides and SiOx as these devices offer cost effectiveness thanks to their inherent foundry-ready nature. In this dissertation, effect of annealing conditions and cathode material on the performance of Cu-SiOx vertical devices is investigated which shows that W-based devices have much lower forming voltage and initial resistance values. Also, higher annealing temperatures first lead to an increase in forming voltage from 400 °C to 500 °C, then a drastic decrease at 550 °C due to Cu island formation at the Cu/SiOx interface. Next, the characterization and modeling of the bilayer Cu2O/Cu-WO3 obtained by annealing the deposited Cu/WO3 stacks in air at BEOL-compatible temperatures is presented that display unique characteristics for lateral PMC devices. First, thin film oxidation kinetics of Cu is studied which show a parabolic relationship with annealing time and an activation energy of 0.70 eV. Grown Cu2O shows a cauliflower-like morphology where feature size on the surface increase with annealing time and temperature. Then, diffusion kinetics of Cu in WO3 is examined where the activation energy of diffusion of Cu into WO3 is calculated to be 0.74 eV. Cu was found to form clusters in the WO3 host which was revealed by imaging. Moreover, using the oxidation and diffusion analyses, a Matlab model is established for modeling the bilayer for process and annealing-condition optimization. The model is built to produce the resulting Cu2O thickness and Cu concentration in Cu-WO3. Additionally, material characterization, preliminary electrical results along with modeling of lateral PMC devices utilizing the bilayer is also demonstrated. By tuning the process parameters such as deposited Cu thickness and annealing conditions, a low-resistive Cu2O layer was achieved which dramatically enhanced the electrodeposition growth rate for lateral PMC devices.
ContributorsBalaban, Mehmet Bugra (Author) / Kozicki, Michael N (Thesis advisor) / Barnaby, Hugh J (Committee member) / Goryll, Michael (Committee member, Committee member) / Arizona State University (Publisher)
Created2020