acase@tulane.edu / 1 / Kui Zhang

In this work, electrical mechanism of Low Temperature Poly-Si Thin-Film Transistors (LTPS TFTs) and Nonvolatile memory TFTs was investigated. First, relationship between trap states in grain boundary and capacitance-voltage (C-V) transfer characteristic curve would be discussed. The experimental results reveal that the C-V curves were a function with the trap state distribution and the measured frequency. The threshold voltage was increased with increasing measured frequency and temperature. Besides, anomalous capacitance was generated in p-channel LTPS TFTs when the device was operated at off-state. In general, the effective capacitance of the LTPS TFTs was only dependent with the overlap area between gate and source/drain under the off-state. However, the experimental results reveal that the off-state capacitance was increased with decreasing measured frequency and/or with increasing measurement temperature. By fitting the curve of drain current versus electric field under off-state region, it was verified that the TAGIDL is consisted of the Pool-Frenkel emission and thermal field emission. In addition, the charge density calculated from the Cch-Vg measurement also the same dependence with electric field. This result demonstrates that the anomalous capacitance is mainly due to the trap-assisted-gate-induced-drain-leakage (TAGIDL). In order to suppress the anomalous capacitance, a band-to-band hot electron (BTBHE) stress was utilized to reduce the vertical electric field between the gate and the drain. The electric field simulation was also performed by ISE-TCAD software. In addition, the degradation mechanism in Nonvolatile memory TFTs under DC stress was discussed. The gate insulator of the Nonvolatile memory TFTs was stacked with oxide-nitride-oxide and the thickness was 40nm-20nm-10nm, respectively. The polarities of the gate insulator were included fresh state, programmed state and erased state. In order to compare the ONO with the STD TFTs, the STD TFTs was also discussed with the same DC stress condition. The experimental results reveal that the degradation phenomenon was not only oxide trapping (Nox) but alsointerface trap (Nit). Besides, the simulation software ISE-TCAD was used to demonstrate these results. This main degradation phenomenon was caused by carrier injecting into oxide which was due to the coulomb force. The Nox and Nit were increased while carrier injected into the gate oxide. On the other hand, there were showed identical degradation mechanism in fresh state and erase state SONOS TFTs under the positive gate bias stress, but in which were not consistent with the program state. In program state, the vertical electric field was released due to trapping electrons in nitride. Therefore, the electric property would slightly improve during the positive gate bias stress and the main degradation mechanism was become to the carrier detrapped from nitride to gate terminal. Beside, the off state C-V curve was slightly increased under the positive gate bias stress in program state. This result was contributed to the electrons trapped in the oxide near the gate insulator edge cause by the electric field corner effect. And then, the electric field corner effect was also verified by the simulation software ISE-TCAD. Finally, the TAGIDL in fresh and erase states is increased with increasing the stress time. On contrary, the situation in program state is decreased with increasing the stress time. These results are contributed to a large number electrons injection into the overlapped insulator region between the gate and S/D and enhancing the band bending in the overlapped region when SONOS TFT is operated at fresh and erase states. However, in program state, the electrons trapped in the nitride are flowed to the gate due to the positive bias.

No description available.

Bilayer magnetic nanostructures are currently of interest in a variety of applications due to the ability to combine complementary properties of each layer. One key area is data storage where extending hard disk drive (HDD) storage density may be achieved by storing each bit of data in an individual magnetic nanostructure. Whilst several magnetometry techniques are capable of measuring the properties of arrays of magnetic nanostructures, very few are sensitive enough to measure an individual magnetic nanostructure. An electrical technique termed anomalous Hall effect (AHE) magnetometry is used in this work due to its high sensitivity. In this technique the structure is fabricated on a Hall cross, and a current is applied and the transverse voltage measured whilst sweeping an external magnetic field. Bilayer magnetic nanostructures formed from separated Co/Pd and Co/Ni multilayers were measured for the first time with this technique, which showed that an asymmetry is seen in their hysteresis loops when the two layers are magnetically decoupled. It is demonstrated that this is due to a combination of a very small giant magnetoresistance (GMR) effect present in the magnetic nanostructure, and the Hall cross offset voltage which results from small imperfections in the shape of the cross. A finite element simulation is used to provide quantitative evidence for this model. These results indicate that asymmetry will be seen in Hall measurements of other materials which exhibit magnetoresistance. Bilayers of FePt and FeRh were also investigated as these materials are of interest for a future HDD system where the structure is heated, and the FeRh undergoes a ferromagnetic transition causing it to assist the switching of the FePt. These thin films are difficult to deposit whilst achieving chemical ordering in both layers. FeRh/FePt films are deposited, before greater ordering is demonstrated with an FePt/FeRh film. It is demonstrated that AHE magnetometry can provide a similar level of measurement information of bilayer nanostructures of these materials as bulk magnetometry techniques can provide of the thin film.

No description available.

The modelling of transport processes in biological systems is one of the main theoretical challenges in physics, chemistry and biology. This is motivated by their essential role in the emergence of diseases, like tumour metastases, which originate from the spontaneous migration of cancer cells. Thus, improvements in their understanding could potentially pave the way for an outstanding innovation of present-day techniques in medicine. These processes often exhibit anomalous properties, which are qualitatively described by the power-law scaling of their mean square displacement, compared to the linear one of normal diffusion. Such behaviour has been often successfully explained by the celebrated continuous-time random walk model. However, recent experimental studies revealed the existence of both more complicated mean square displacement behaviour and anomalous features in other characteristic observables, e.g. the position-velocity statistics or the two point correlation functions of either the velocity or the position. Thus, in order to understand the anomalous diffusion recorded in these experiments and assess the microscopic processes underlying the observed macroscopic dynamics, one needs to have a complete tool-kit of techniques and models that can be readily compared with the experimental datasets. In this Thesis, we contribute to the construction of such a complete framework by fully characterising anomalous processes, which are described by means of a continuoustime random walk with general waiting time distributions and/or external forces that are exerted both during the jumps (as in the original model) and the waiting times. In the first case we derive both the joint statistics of these processes and their observables, specifically by obtaining a generalised fractional Feynman-Kac formula, and their multipoint correlation functions and employ them to fit the mean square displacement data of diffusing mitochondria. This result supports the experimental relevance of our formalism, which comprises general formulas for several quantities that can provide readily predictable tests to be checked in experiments. In the second case, we characterise the new anomalous processes by means of Langevin equations driven by a novel type of non Gaussian noise, which reproduces the typical fluctuations of a free diffusive continuous-time random walk. For a constant external force, we also obtain the fractional evolution equations of their position probability density function and show that, contrarily to continuous-time random walks, they are weak Galilean invariant, i.e., their position distribution in different Galilean frames is obtained by shifting the sample variable according to the relative motion of the frames. Thus, these processes provide a suitable frame-invariant framework, that could be employed to investigate the stochastic thermodynamics of anomalous diffusive processes.

Diffusion can be classified as either normal or anomalous. A variety of experimental systems are evaluated to classify diffusion. Potential regressions and step size distributions are analysed. Nor-mal diffusion holds except where flocculation takes place, or where concentrations of cationic starches are high or with cationic starches and latex together. In these cases, subdiffusion takes place. Furthermore, limiting values are used to calculate diffusion coefficients. Diffusion of non-spherical particles is covered as well, here tested on microcrystalline cellulose.

The electrical conductivity of InN, group III-V semiconductor, is measured by four point measurement at low temperatures and high magnetic fields. From Resistance Vs temperature measurements (done in the absence of magnetic field) there is a transition from semiconducting state to superconducting state at 2.5K. This superconducting state disappears when the measurements are repeated but at a magnetic field of 0.1 Tesla. Mover the Hall voltage is not proportional to the magnetic field.

Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.

Many crucial cellular processes take place at the plasma membrane. The latter is a complex, two-dimensional medium exhibiting significant lateral structure. As a result, a number of non-classical processes, including anomalous diffusion, compartimentalisation and fractal kinetics take place at the membrane surface. The evaluation of various hypotheses and theories about the membrane is currently very difficult because no general modelling framework is available. In this thesis, we present a stochastic, spatially explicit Monte Carlo model for the plasma membrane that accounts for illmixedness, mobile lipid microdomains, fixed proteins, cytoskeletal fence structures and other interactions. We interrogate this model to obtain three classes of results, regarding (1) the effect of lipid microdomains on protein dynamics on the membrane (2) the effects of microdomains, cytoskeletal fences and fixed proteins on the nature of the (anomalous) diffusion on the membrane and (3) the effects of obstructed diffusion on reaction kinetics at the membrane. We find that the presence of lipid microdomains can lead to nonclassical phenomena such as increased collision rates and differences between long-range and short-range diffusion coefficients. Our results also suggest that experimental techniques measuring long-range diffusion may not be sufficiently discriminating and hence cannot be used to infer quantitative information about the presence and characteristics of microdomains. With regard to anomalous diffusion in particular, we find that to explain this phenomenon at the levels observed in vivo, a number of interactions are required, including (but not necessarily limited to) obstacle-induced diffusion and segregation, or exclusion from microdomains. The effects of these different interactions upon the nature of the diffusion appear to be approximately additive. Finally, we show that a widely used non-spatial method, the Stochastic Simulation Algorithm, can be modified to take into account anomalous diffusion and that this significantly increases its predictive accuracy. The model presented in this thesis is expected to be of future value in evaluating different models of cell surface processes.