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In this thesis, we deal with the application of transmission terahertz spectroscopy as an analysis tool for the study of molecular solids, in particular organic crystals of pharmaceutical interest. Most of the work has been performed using two computational packages aimed at the interpretation of the spectra, one based on molecular forcefields (DMACRYS), the other on solid state density functional theory (CASTEP). We compare low temperature determinations of several molecular organic crystals to calculated spectra, and attempt to assign calculated modes of vibrations to absorption peaks, based on the similarity in frequency between the measured and calculated peaks. One of the main aims of this work is to establish the limits of our forcefield approach, which is based on the approximation that the intramolecular degrees of freedom can be neglected. We analyse the normal modes of vibration calculated with CASTEP, evaluating the amount of rigid molecule rotational and translational contribution to each eigenvector as a function of frequency, in order to validate our forcefield approach. We also compare the two sets of eigenvectors from the DMACRYS and CASTEP calculations to assess the similarity between the two approaches. We perform the same eigenvectors analysis on several hydrate systems in order to understand the role of water in the lattice dynamics of crystalline hydrates. We attempt a classification of the eigenvectors based on the strength of the forces involved in the molecular vibrations and based on the amount of the water contribution to each normal mode. A set of isostructural crystals is analysed in order to understand the effect that small variations (in the molecular formula and in the unit cell arrangement) have on the measured and calculated absorption spectra of a crystal. Finally, we discuss the use and development of computational methods that allow us to have a more realistic description of the molecular electrostatic in DMACRYS.

The presence of the ordered $\gamma^{\prime}$ phase ($\text{Ni}_{3}\text{Al}$) in Ni-base superalloys is fundamental to the performance of engineering components such as turbine disks and blades which operate at high temperatures and loads. Hence for these alloys it is important to optimize their microstructure and phase composition. This is typically done by varying their chemistry and heat treatment to achieve an appropriate balance between $\gamma^{\prime}$ content and other constituents such as carbides, borides, oxides and topologically close packed phases. In this work we have set out to investigate the onset of $\gamma^{\prime}$ ordering in Ni-Al single crystals and in Ni-Al bicrystals containing coincidence site lattice grain boundaries (GBs) and we do this at high temperatures, which are representative of typical heat treatment schedules including quenching and annealing. For this we use the atomistic simulation methods of molecular dynamics (MD) and density functional theory (DFT). In the first part of this work we develop robust Bayesian classifiers to identify the $\gamma^{\prime}$ phase in large scale simulation boxes at high temperatures around 1500 K. We observe significant \gamma^{\prime} ordering in the simulations in the form of clusters of $\gamma^{\prime}$-like ordered atoms embedded in a $\gamma$ host solid solution and this happens within 100 ns. Single crystals are found to exhibit the expected homogeneous ordering with slight indications of chemical composition change and a positive correlation between the Al concentration and the concentration of $\gamma^{\prime}$ phase. In general, the ordering is found to take place faster in systems with GBs and preferentially adjacent to the GBs. The sole exception to this is the $\Sigma3 \left(111\right)$ tilt GB, which is a coherent twin. An analysis of the ensemble and time lag average displacements of the GBs reveals mostly `anomalous diffusion' behaviour. Increasing the Al content from pure Ni to Ni 20 at.% Al was found to either consistently increase or decrease the mobility of the GB as seen from the changing slope of the time lag displacement average. The movement of the GB can then be characterized as either `super' or `sub-diffusive' and is interpreted in terms of diffusion induced grain boundary migration, which is posited as a possible precursor to the appearance of serrated edge grain boundaries. In the second part of this work we develop a method for the training of empirical interatomic potentials to capture more elements in the alloy system. We focus on the embedded atom method (EAM) and use the Ni-Al system as a test case. Recently, empirical potentials have been developed based on results from DFT which utilize energies and forces, but neglect the electron densities, which are also available. Noting the importance of electron densities, we propose a route to include them into the training of EAM-type potentials via Bayesian linear regression. Electron density models obtained for structures with a range of bonding types are shown to accurately reproduce the electron densities from DFT. Also, the resulting empirical potentials accurately reproduce DFT energies and forces of all the phases considered within the Ni-Al system. Properties not included in the training process, such as stacking fault energies, are sometimes not reproduced with the desired accuracy and the reasons for this are discussed. General regression issues, known to the machine learning community, are identified as the main difficulty facing further development of empirical potentials using this approach.

Defects in the functional oxides play an important role in electronic devices like metal oxide semiconductor field effect transistors (MOSFETs) and resistive random-access memories (ReRAMs). The continuous scaling of CMOS has brought the Si MOSFET to its physical technology limit and the replacement of Si channel with Ge channel is required. However, the performance of Ge MOSFETs suffers from Ge/oxide interface quality and reliability problems, which originates from the charge traps and defect states in the oxide or at the Ge/oxide interface. The sub-oxide layers composed of GeII states at the Ge/GeO2 interface seems unavoidable with normal passivation methods like hydrogen treatment, which has poor electrical properties and is related to the reliability problem. On the other hand, ReRAM works by formation and rupture of O vacancy conducting filaments, while how this process happens in atomic scale remains unclear. In this thesis, density functional theory is applied to investigate the defect behaviours in oxides to address existing issues in these electronic devices. In chapter 3, the amorphous atomic structure of doped GeO2 and Ge/GeO2 interface networks are investigated to explain the improved MOSFET reliability observed in experiments. The reliability improvement has been attributed to the passivation of valence alternation pair (VAP) type O deficiency defects by doped rare earth metals. In chapter 4, the oxidation mechanism of GeO2 is investigated by transition state simulation of the intrinsic defect diffusion in the network. It is proposed that GeO2 is oxidized from the Ge substrate through lattice O interstitial diffusion, which is different from SiO2 which is oxidized by O2 molecule diffusion. This new mechanism fully explains the strange isotope tracer experimental results in the literature. In chapter 5, the Fermi level pinning effect is explored for metal semiconductor electrical contacts in Ge MOSFETs. It is found that germanides show much weaker Fermi level pinning than normal metal on top of Ge, which is well explained by the interfacial dangling bond states. These results are important to tune Schottky barrier heights (SBHs) for n-type contacts on Ge for use on Ge high mobility substrates in future CMOS devices. In chapter 6, we investigate the surface and subsurface O vacancy defects in three kinds of stable TiO2 surfaces. The low formation energy under O poor conditions and the +2 charge state being the most stable O vacancy are beneficial to the formation and rupture of conducting filament in ReRAM, which makes TiO2 a good candidate for ReRAM materials. In chapter 7, we investigate hydrogen behaviour in amorphous ZnO. It is found that hydrogen exists as hydrogen pairs trapped at oxygen vacancies and forms Zn-H bonds. This is different from that in c-ZnO, where H acts as shallow donors. The O vacancy/2H complex defect has got defect states in the lower gap region, which is proposed to be the origin of the negative bias light induced stress instability.