High Spatial Resolution Microanalysis of Semiconductor Interfaces

The work presented in this thesis is concerned with high spatial resolution characterisation of compound semiconductor multilayer structures. The principal techniques used are high-angle annular dark field imaging (ADFI) and energy dispersive x-ray (EDX) microanalysis. These are both available on a scanning transmission electron microscope (STEM). The motivation for this project is that, to enable a greater understanding of material growth processes and of the electronic and optical properties of semiconductor multilayers, it is desirable to obtain a knowledge of the atomic perfection of, and elemental compositions across, layer interfaces in the materials. This thesis is primarily concerned with the analysis of AlGaAs/GaAs multilayer specimens grown by molecular beam epitaxy (MBE) and InGaAs/InP specimens grown by MBE and by atmospheric pressure metal-organic chemical vapour deposition (MOCVD). A brief description of the material growth processes and a general introduction to the structural and compositional characterisation of semiconductor multilayers is given in chapter 1. The theoretical bases that underlie the two analytical techniques used in this project are discussed in chapter 2. The chapter describes the way in which elastically scattered electrons can be used to provide compositional information on multilayers using the technique of high-angle ADFI. In preparation for the measurement of elemental compositions using EDX microanalysis, cross sections for the production of characteristic x-ray photons for the elements of interest in this project are calculated. Experimental procedures and data analysis techniques used in this thesis are established in chapters 3, 4 and 5. A detailed description of the STEM and its associated detectors is given in chapter 3. The discussion includes the calculation of the current density distribution in the electron probe used for each of the two analytical techniques. Chapter 3 concludes with a description of the technique used to prepare high quality cross-sectional specimens for microanalysis in a STEM. Considerations specific to the analysis of semiconductor multilayers using high-angle ADFI are addressed in chapter 4. Optimised experimental conditions for the technique are established, as is the image analysis technique that is used to yield as much information as possible from the acquired data. Chapter 4 also includes a description of a second composition sensitive imaging technique, namely structure factor contrast imaging which is principally used here for orienting the cross-sectional specimen in the microscope. Considerations relevant to EDX microanalysis of semiconductor multilayers are discussed in chapter 5. This includes a detailed description of a Monte Carlo simulation routine used to help in the interpretation of measured concentration distributions from interface regions. The application of EDX microanalysis and high-angle ADFI to the characterisation of the materials of interest is described in chapters 6, 7 and 8. In the study of high quality MBE grown AIGaAs/GaAs specimens described in chapter 6, emphasis is given to the development of a results analysis procedure that utilises the full potential of each analytical technique. The investigation of the InGaAs/InP specimens grown by atmospheric pressure MOCVD is described in chapter 7. In this chapter, the procedures developed in chapters 2 to 6 are used to provide as much information as possible on the variation in elemental composition across interfaces and at layer centres in the system. This information is used by material growers to modify and improve atmospheric pressure MOCVD growth techniques. Similar studies are carried out in chapter 8 in the investigation of MBE grown InGaAs/InP specimens. Finally, in chapter 9, general conclusions are drawn on the work described in this thesis and suggestions are made for future studies of semiconductor multilayers in a STEM

Multi-epoch machine learning for galaxy formation

In this thesis I utilise a range of machine learning techniques in conjunction with hydrodynamical cosmological simulations. In Chapter 2 I present a novel machine learning method for predicting the baryonic properties of dark matter only subhalos taken from N-body simulations. The model is built using a tree-based algorithm and incorporates subhalo properties over a wide range of redshifts as its input features. I train the model using a hydrodynamical simulation which enables it to predict black hole mass, gas mass, magnitudes, star formation rate, stellar mass, and metallicity. This new model surpasses the performance of previous models. Furthermore, I explore the predictive power of each input property by looking at feature importance scores from the tree-based model. By applying the method to the LEGACY N-body simulation I generate a large volume mock catalog of the quasar population at z=3. By comparing this mock catalog with observations, I demonstrate that the IllustrisTNG subgrid model for black holes is not accurately capturing the growth of the most massive objects. In Chapter 3 I apply my method to investigate the evolution of galaxy properties in different simulations, and in various environments within a single simulation. By comparing the Illustris, EAGLE, and TNG simulations I show that subgrid model physics plays a more significant role than the choice of hydrodynamics method. Using the CAMELS simulation suite I consider the impact of cosmological and astrophysical parameters on the buildup of stellar mass within the TNG and SIMBA models. In the final chapter I apply a combination of neural networks and symbolic regression methods to construct a semi-analytic model which reproduces the galaxy population from a cosmological simulation. The neural network based approach is capable of producing a more accurate population than a previous method of binning based on halo mass. The equations resulting from symbolic regression are found to be a good approximation of the neural network

sympl (v. 0.4.0) and climt (v. 0.15.3) – towards a flexible framework for building model hierarchies in Python

sympl (System for Modelling Planets) and climt (Climate Modelling and Diagnostics Toolkit) are an attempt to rethink climate modelling frameworks from the ground up. The aim is to use expressive data structures available in the scientific Python ecosystem along with best practices in software design to allow scientists to easily and reliably combine model components to represent the climate system at a desired level of complexity and to enable users to fully understand what the model is doing.sympl is a framework which formulates the model in terms of a state that gets evolved forward in time or modified within a specific time by well-defined components. sympl's design facilitates building models that are self-documenting, are highly interoperable, and provide fine-grained control over model components and behaviour. sympl components contain all relevant information about the input they expect and output that they provide. Components are designed to be easily interchanged, even when they rely on different units or array configurations. sympl provides basic functions and objects which could be used in any type of Earth system model.climt is an Earth system modelling toolkit that contains scientific components built using sympl base objects. These include both pure Python components and wrapped Fortran libraries. climt provides functionality requiring model-specific assumptions, such as state initialization and grid configuration. climt's programming interface designed to be easy to use and thus appealing to a wide audience.Model building, configuration and execution are performed through a Python script (or Jupyter Notebook), enabling researchers to build an end-to-end Python-based pipeline along with popular Python data analysis and visualization tools.</p

Effects of Space Charge, Dopants, and Strain Fields on Surfaces and Grain Boundaries in YBCO Compounds

Statistical thermodynamical and kinetically-limited models are applied to study the origin and evolution of space charges and band-bending effects at low angle [001] tilt grain boundaries in YBa$_2$Cu$_3$O$_7$ and the effects of Ca doping upon them. Atomistic simulations, using shell models of interatomic forces, are used to calculate the energetics of various relevant point defects. The intrinsic space charge profiles at ideal surfaces are calculated for two limits of oxygen contents, i.e. YBa$_2$Cu$_3$O$_6$ and YBa$_2$Cu$_3$O$_7$. At one limit, O$_6$, the system is an insulator, while at O$_7$, a metal. This is analogous to the intrinsic and doping cases of semiconductors. The site selections for doping calcium and creating holes are also investigated by calculating the heat of solution. In a continuum treatment, the volume of formation of doping calcium at Y-sites is computed. It is then applied to study the segregation of calcium ions to grain boundaries in the Y-123 compound. The influences of the segregation of calcium ions on space charge profiles are finally studied to provide one guide for understanding the improvement of transport properties by doping calcium at grain boundaries in Y-123 compound.Comment: 13 pages, 5 figure

Tai Chi and vestibular rehabilitation improve vestibulopathic gait via different neuromuscular mechanisms: Preliminary report

BACKGROUND: Vestibular rehabilitation (VR) is a well-accepted exercise program intended to remedy balance impairment caused by damage to the peripheral vestibular system. Alternative therapies, such as Tai Chi (TC), have recently gained popularity as a treatment for balance impairment. Although VR and TC can benefit people with vestibulopathy, the degree to which gait improvements may be related to neuromuscular adaptations of the lower extremities for the two different therapies are unknown. METHODS: We examined the relationship between lower extremity neuromuscular function and trunk control in 36 older adults with vestibulopathy, randomized to 10 weeks of either VR or TC exercise. Time-distance measures (gait speed, step length, stance duration and step width), lower extremity sagittal plane mechanical energy expenditures (MEE), and trunk sagittal and frontal plane kinematics (peak and range of linear and angular velocity), were measured. RESULTS: Although gait time-distance measures were improved in both groups following treatment, no significant between-groups differences were observed for the MEE and trunk kinematic measures. Significant within groups changes, however, were observed. The TC group significantly increased ankle MEE contribution and decreased hip MEE contribution to total leg MEE, while no significant changes were found within the VR group. The TC group exhibited a positive relationship between change in leg MEE and change in trunk velocity peak and range, while the VR group exhibited a negative relationship. CONCLUSION: Gait function improved in both groups consistent with expectations of the interventions. Differences in each group's response to therapy appear to suggest that improved gait function may be due to different neuromuscular adaptations resulting from the different interventions. The TC group's improvements were associated with reorganized lower extremity neuromuscular patterns, which appear to promote a faster gait and reduced excessive hip compensation. The VR group's improvements, however, were not the result of lower extremity neuromuscular pattern changes. Lower-extremity MEE increases corresponded to attenuated forward trunk linear and angular movement in the VR group, suggesting better control of upper body motion to minimize loss of balance. These data support a growing body of evidence that Tai Chi may be a valuable complementary treatment for vestibular disorders

New constraints on the primordial black hole number density from Galactic gamma-ray astronomy

Primordial black holes are unique probes of cosmology, general relativity, quantum gravity and non standard particle physics. They can be considered as the ultimate particle accelerator in their last (explosive) moments since they are supposed to reach, very briefly, the Planck temperature. Upper limits on the primordial black hole number density of mass $M_{\star} = 5 10^{14}$ g, the Hawking mass (born in the big-bang terminating their life presently), is determined comparing their predicted cumulative $\gamma$-ray emission, galaxy-wise, to the one observed by the EGRET satellite, once corrected for non thermal $\gamma$-ray background emission induced by cosmic ray protons and electrons interacting with light and matter in the Milky Way. A model with free gas emissivities is used to map the Galaxy in the 100 MeV photon range, where the peak of the primordial black hole emission is expected. The best gas emissivities and additional model parameters are obtained by fitting the EGRET data and are used to derive the maximum emission of the primordial black hole of the Hawking mass, assuming that they are distributed like the dark matter in the Galactic halo. The bounds we obtain, depending on the dark matter distribution, extrapolated to the whole Universe ($\Omega_{PBH}(M_{\star}) = 2.4 10^{-10}$ to $2.6 10^{-9}$ are more stringent than the previous ones derived from extragalactic $\gamma$-ray background and antiprotons fluxes, though less model dependent and based on more robust data. These new limits have interesting consequences on the theory of the formation of small structures in the Universe, since they are the only constraint on very small scale density fluctuations left by inflation.Comment: 8 pages, 6 figures ; accepted in Astronomy and Astrophysic

MRI of the temporo-mandibular joint: which sequence is best suited to assess the cortical bone of the mandibular condyle? A cadaveric study using micro-CT as the standard of reference

OBJECTIVE: To determine the best suited sagittal MRI sequence out of a standard temporo-mandibular joint (TMJ) imaging protocol for the assessment of the cortical bone of the mandibular condyles of cadaveric specimens using micro-CT as the standard of reference. METHODS: Sixteen TMJs in 8 human cadaveric heads (mean age, 81 years) were examined by MRI. Upon all sagittal sequences, two observers measured the cortical bone thickness (CBT) of the anterior, superior and posterior portions of the mandibular condyles (i.e. objective analysis), and assessed for the presence of cortical bone thinning, erosions or surface irregularities as well as subcortical bone cysts and anterior osteophytes (i.e. subjective analysis). Micro-CT of the condyles was performed to serve as the standard of reference for statistical analysis. RESULTS: Inter-observer agreements for objective (r = 0.83-0.99, P < 0.01) and subjective (κ = 0.67-0.88) analyses were very good. Mean CBT measurements were most accurate, and cortical bone thinning, erosions, surface irregularities and subcortical bone cysts were best depicted on the 3D fast spoiled gradient echo recalled sequence (3D FSPGR). CONCLUSION: The most reliable MRI sequence to assess the cortical bone of the mandibular condyles on sagittal imaging planes is the 3D FSPGR sequence. KEY POINTS: MRI may be used to assess the cortical bone of the TMJ. • Depiction of cortical bone is best on 3D FSPGR sequences. • MRI can assess treatment response in patients with TMJ abnormalities

A weak characterization of slow variables in stochastic dynamical systems

We present a novel characterization of slow variables for continuous Markov processes that provably preserve the slow timescales. These slow variables are known as reaction coordinates in molecular dynamical applications, where they play a key role in system analysis and coarse graining. The defining characteristics of these slow variables is that they parametrize a so-called transition manifold, a low-dimensional manifold in a certain density function space that emerges with progressive equilibration of the system's fast variables. The existence of said manifold was previously predicted for certain classes of metastable and slow-fast systems. However, in the original work, the existence of the manifold hinges on the pointwise convergence of the system's transition density functions towards it. We show in this work that a convergence in average with respect to the system's stationary measure is sufficient to yield reaction coordinates with the same key qualities. This allows one to accurately predict the timescale preservation in systems where the old theory is not applicable or would give overly pessimistic results. Moreover, the new characterization is still constructive, in that it allows for the algorithmic identification of a good slow variable. The improved characterization, the error prediction and the variable construction are demonstrated by a small metastable system