PhD Dissertations - DO NOT EDIThttp://hdl.handle.net/10106/252092024-03-28T19:33:56Z2024-03-28T19:33:56ZINVESTIGATION OF THE PLASMA ELECTROLYTIC OXIDATION MECHANISM OF TITANIUMhttp://hdl.handle.net/10106/316722023-11-09T23:01:10ZINVESTIGATION OF THE PLASMA ELECTROLYTIC OXIDATION MECHANISM OF TITANIUM
Plasma electrolytic oxidation (PEO) is an environmentally friendly technology capable of forming coatings with excellent adhesion strength at high deposition rates. The PEO process is particularly attractive for forming desirable oxide-based coatings in transition metals (Al, Ti, Mg) to improve their surface sensitive properties. At present, the PEO mechanism is not fully understood since the process includes complex processes that are difficult to study. However, understanding the PEO mechanism is essential to produce coatings with desirable characteristics for a variety of new applications. One critical PEO process parameter is the applied total current to the workpiece. The total applied current in this process is composed of electronic current caused by sparking and ionic current caused by diffusion of electrolyte ions into the oxide. In the present work, a wide spectrum of current densities was applied on commercially pure titanium in alkaline electrolytes to investigate its effect on the voltage response and produced coating characteristics. The growth mechanism and oxide characteristics were investigated by studying the correlation between the ionic/electronic current contribution rate at different current densities during the PEO stages. The voltage-time response was found to be essential because it enables the quantification of the information about different PEO phases and correlate that information with the growth mechanism. It was found that at low current densities (30 and 40 mA/cm2), the contribution of electronic current is dominating and a large number of discharge channels develop in the oxide. However, in this case there would not be enough ions (low ionic current) to diffuse through the discharge channels for reaction. High density of plasma discharges at this condition, forms large number of discharge channels and increases the porosity and surface roughness of the coating. Also, these discharges provide enough energy to raise the temperature facilitating formation of both stable rutile and metastable anatase phases. By increasing the current density, the incorporation rate of ionic current increases which results in the formation of dense anatase coatings. It was found that in order to achieve high growth rates, an equal or balanced contribution from ionic (diffusion of ions for reaction) and electronic (generation of channels) charges is required. Transmission Electron Microscopy studies showed that all coatings are composed of two layers: an amorphous layer on the top produced by quenching from the electrolyte and a composite layer close to the substrate. The bottom composite layer has a complex microstructure consisting of nanocrystalline phases due to fast nucleation rate, amorphous structure and nano pores. The thickness ratio between the bottom complex layer and the top amorphous layer increases by increasing the applied current density. Thus, the present research revealed clearly that both the electronic and ionic current play a critical role in the PEO process and a balanced contribution is needed to realize the benefits in the oxide growth process. Furthermore, it is shown that electrolyte properties including composition and conductivity have significant effects on breakdown voltage and contribution of the ionic charge and as a result coating characteristics.
PHYSICAL MODELING OF FILAMENT GROWTH AND RESISTIVE SWITCHING IN METAL OXIDE-BASED RRAMhttp://hdl.handle.net/10106/314212023-12-05T20:28:10Z2022-12-15T00:00:00ZPHYSICAL MODELING OF FILAMENT GROWTH AND RESISTIVE SWITCHING IN METAL OXIDE-BASED RRAM
Metal oxide-based resistive random-access memories (RRAM) exhibit several excellent performances, such as nanosecond switching speed, large write-erase endurance, and long retention time, and can potentially replace the traditional circuit elements for use as the fundamental units in next-generation hardware deep-learning or neuromorphic systems. The functionality of a metal oxide-based RRAM is attributed to an oxygen vacancy (V_O^(..))-rich conductive filament (CF), which initially forms, and later dissolves or regrows inside the oxide layer during the resistive switching process. However, the complicated interplays among the coexisting chemical, electrical, mechanical, and thermal effects during the formation, growth, and rupture of the CFs make the dynamic of the resistive switching behavior extremely complicated and unpredictable, and its underlying mechanisms are not fully understood. Here, we developed a phase-field model based on defect chemistry, charge transport dynamics, and micro elasticity theory to investigate the electroforming process and subsequent resistive switching behavior, using HfO2-x as a prototypical model system. It is revealed that the CF formation is assisted by the supply of oxygen vacancies V_O^(..) at the anode/oxide interface and the V_O^(..) transport in the bulk during the electroforming process. The CFs with more uniform morphology can be obtained by employing active electrodes with low vacancy formation barrier Eb and metal oxide with large electrical conductivity and lower thermal conductivity.
We also explored the role of the elastic effect on resistive switching behavior. It is found that the local oxygen vacancy distribution induces a local Vegard strain and a strain gradient, which acts as an additional driving force that inhibits the oxygen vacancy migration during switching and reduces the current on/off ratios. In addition, high-throughput phase-field simulations and a machine learning approach are performed to derive interpretable analytical correlations between the material properties (electrical and thermal conductivities, Vegard strain coefficients of the metal oxides) and the device performances (current on/off ratio and switching time). It is revealed that optimal resistive performance can be achieved in materials with a small Lorenz number and Vegard strain coefficient.
Furthermore, we also found that the switching performances can be enhanced by microstructure design. Due to the electric field concentration effect, embedding metal NIs leads to a more deterministic formation of the CF from their vicinity, in contrast to the random growth of CFs without embedded NIs. This deterministic vacancy nucleation further reduces the forming, reset, and set voltages, and enhances the uniformity of these operation voltages and current ON/OFF ratios. We further demonstrate that increasing the height of NIs, modifying the metal NIs to a triangle shape, and choosing active NI metals with high oxygen affinity can further optimize the switching performance. Our work provides a deep understanding of the underlying mechanism of CF growth and rupture, as well as the designing strategy for materials selection and microstructure design for further improved RRAM performances.
2022-12-15T00:00:00ZSimulation of Li Dendrite Inhibition in Lithium Battery by Phase-Field Methodhttp://hdl.handle.net/10106/313912023-06-29T08:27:38Z2022-05-16T00:00:00ZSimulation of Li Dendrite Inhibition in Lithium Battery by Phase-Field Method
Lithium (Li) dendrite growth poses serious challenges for the development of Li metal batteries which also stops the footsteps of human utilizing the environment-friendly new power source. Replacing liquid electrolyte with solid electrolyte can not only inhibit the dendrite growth by mechanical suppression, but also introduce more possibilities to the electrochemistry of battery. However, the underlying mechanism is still not fully understood, and most theoretical works focus on pure liquid electrolyte, ignoring the mechanical strain effects. Here we developed a phase-field model which simulates the Li dendrite growth to study the competition between diffusion and deposition rates, the pure elastic and Elasto-plastic effects, and the inhibition from nanofillers embedded in the solid electrolytes. It is revealed that high diffusion rate can transport more Li ions to the electrode surface, which create a low concentration gradient at the interface, leading to a smooth electrode surface.
Li dendrite can also be effectively inhibited by the electrolytes of high elastic modulus and initial yield strength, which induce and withstand the large mechanical suppression, respectively. High-throughput phase-field simulations are performed to establish a database of relationships between the aforementioned mechanical properties and the Li dendrite morphology, based on which a compressed-sensing machine learning model is trained to derive interpretable analytical correlations between the key material parameters and the dendrite morphology, as described by the dendrite length and area ratio. It is revealed that the Li dendrite can be effectively inhibited by the electrolytes of high elastic modulus and initial yield strength. Meanwhile, the role of the yield strength of Li metal is also critical when the yield strength of the electrolyte becomes low.
We also discovered that the introduction of the 1D nanofiber arrays could confine the Li ion transport along horizontal direction, reduce the concentration gradient across the electrode/electrolyte interface, and inhibit the Li dendrite growth. Our work provides deep understanding of the dendrite growth mechanism, the mechanical suppression and the inhibition by the 1D nanofiber array, as well as the designing strategy for the solid composite electrolyte for improved Li anode stability and Li ion conductivity.
Furthermore, we also explored the formation process of dead Li and study the formation mechanism. It is found that the initial Li amount affects the dead Li most while the high discharge voltage will also lead to the formation of dead Li.
2022-05-16T00:00:00ZStudy of Electron Energy Filtering for Cold Electron Transport at Room Temperaturehttp://hdl.handle.net/10106/313742023-06-29T08:27:06Z2022-08-17T00:00:00ZStudy of Electron Energy Filtering for Cold Electron Transport at Room Temperature
The Fermi-Dirac thermal excitation of electrons at room temperature has been a significant limitation to many technologically important phenomena such as single electron transport. The electron thermal excitation also degrades the performance of modern electronic devices as well as spintronic devices. The scaling of metal-oxide-semiconductor field-effect transistors (MOSFETs) is hindered due to the thermal excitation of electrons at room temperature. Suppression of the thermally excited electrons at room temperature would therefore enable further scaling of the transistors, and in turn, improve the performance of electronic devices.
This study demonstrates the suppression of electron thermal excitation at room temperature without using cryogenic cooling. This is done using a quantum well discrete energy level as an electron energy filter. The energy filter is placed between a source electrode and silicon, where the thermally excited electrons in the source are filtered out by a quantum well state and the energy-filtered cold electrons are injected to silicon. The energy filtering stack consists of a thin quantum well layer (~3nm/4nm/5nm SnO2) bounded by tunneling barrier 1 (~0.5nm Al2O3 or 1nm Si3N4) and tunneling barrier 2 (~1.5nm Native SiO2). This energy filtering structure has enabled cold-electron injection to silicon, with an effective electron temperature of ~0.08 Kelvin at room temperature. The current-voltage measurements show abrupt current jumps at specific voltages, which correspond to the alignment of a quantum well discrete energy level with the silicon conduction band edge. The differential conductance plot for the observed abrupt current jumps shows an extremely narrow peak, with a full width at half maximum (FWHM) of ~0.025 mV, corresponding to an effective electron temperature of ~0.08 Kelvin at room temperature. The cold-electron injection to silicon opens possibilities for extremely energy-efficient transistors with subthreshold slope values significantly below the room-temperature subthreshold slope limit of 60mV/decade, e.g., 2mV/decade (corresponding to an effective electron temperature of ~10 Kelvin).
2022-08-17T00:00:00Z