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As the downscaling of metal-oxide-semiconductor field-effect transistors (MOSFETs) continues, the short-channel effects (SCEs) and contact resistance severely degrade device performance. It is crucial to understand the physics at various interfacial regions of MOSFETs to provide guidance for overcoming these limitations. In this thesis, the representative materials and their contacts employed in the development of MOSFETs are studied using density functional calculations, with an emphasis on understanding the electronic behaviours of metal-semiconductor junctions and heterojunction. The thesis studies the structural, electronic, and optical properties of nine polymorphs of SiO₂, employing both the traditional generalised gradient approximation (GGA) and the state-of-the-art screened exchange (sX) functional. Calculations using the sX functional accurately reproduce the experimental band gap values, whereas GGA is more effective in describing the optical properties. The advanced sX method and the more efficient GGA + U scheme are applied to several important oxides (ZnO, CdO, SrO, and MgO) to address the underestimated band gaps of oxides by the traditional GGA functional. The GGA + U scheme is further applied to calculate the Schottky barrier heights (SBHs) at various metal-oxide interfaces. The metal-induced gap states (MIGS) model is demonstrated to be a reliable simplified approach for predicting the pinning effect. A similar investigation involving high-κ CaF₂ is carried out, which confirms the accuracy of the sX method in characterising wide band gap materials. Moreover, the computed electronic properties of Si-CaF₂ and metal-CaF₂ interfaces obtained using the GGA + U scheme are consistent with the MIGS predictions. Studies are also conducted on p-type and ambipolar monolayer WSe₂ contacting with various metals. Through a rational design approach, weakly pinned, low-resistance metal-WSe₂ contacts are achieved, offering potential applications in 2D semiconductor devices.

This thesis reports studies of systems containing actinide (An) and noble gas (Ng) elements, in both the nuclear materials and coordination chemistry fields. Among nuclear fuel fission products, noble gases (especially Kr and Xe) have low solubility and may release to the fuel-clad gap, which will lead to fuel swelling and thermal conductivity degradation. For the safe and efficient use of nuclear fuel, it is important to have a comprehensive understanding of fission gas release behaviours. However, the fission gas release model in actinide nitrides, promising candidates for use as a fuel in Generation IV reactors, is rudimentary. Chapter 3 studies the effect of non-stoichiometry of UN on point defect formation energy and Ng solution energy. The most stable defect types and the preferred trap sites of Ng under different stoichiometric conditions are reported. Chapter 4 investigates the diffusion of Ng in UN, and finds that the Ng diffusion is governed by the U vacancy-assisted mechanism. The calculated diffusion coefficients are in good agreement with the experiments. Chapter 5 extends the binary UN work to ternary (U, Pu)N. Actinide vacancy formation energy and Ng incorporation energy are found to be highly dependent on the chemical environment around the defects (i.e., the number of U atoms in the first (NU(1NN)) and second (NU(2NN)) nearest-neighbour shell), which increase as NU(1NN) increases while decrease as NU(2NN) increases. In coordination chemistry, An-Ng (especially He) complexes are candidate molecules for achieving high coordination numbers. Chapter 6 investigates the geometries, electronic structures, and bond properties of early An-Ng complexes, reporting 18-coordinate Th3+-He and Th4+-He systems for the first time. The covalency of the An-He bond in the group valent AnHe17q+ (An = Ac-U) species increases from AcHe173+ to UHe176+, while Ac-Ng bond covalency in AcNg123+ increases as the Ng gets heavier.

Magnesium sulfate hydrates are considered important rock-forming minerals on the outer three Galilean moons of Jupiter (i.e., Europa, Ganymede, Callisto) and, alongside ferrous sulfate hydrates, are promising candidate minerals for the widespread sulfate deposits that occur in the equatorial region of Mars. In such extraterrestrial environments, these minerals experience extreme high-pressure conditions in the interiour of the Galilean moons and low temperature conditions on the surface of these moons and Mars. The aim of this thesis is to understand the structural stability, compressibility, and thermal expansion of these compounds in such extreme environments and aid their identification in ongoing and future space missions. Most magnesium sulfate hydrates lack accurate reference elastic tensors, which hinders their seismological identification in lander missions on the icy moons of the outer solar system, as envisioned for the near future. In this thesis, the accuracy of recent advancements in density functional theory to predict the compressibility and elastic constants of icy satellite candidate minerals (i.e., epsomite (MgSO₄·7H₂O), gypsum (CaSO₄·2H₂O), carbon dioxide (CO₂), and benzene (C₆H₆)) was assessed by benchmarking them against experimental reference data from the literature. Key findings are that density functional theory calculations do not yield elastic constants accurate enough to be used as a reference for the seismic exploration of icy moons. However, the bulk compressibility of such materials is very accurately reproduced by density functional theory, which was therefore used to predict the compressibility of the icy satellite candidate minerals starkeyite (MgSO₄·4H₂O) and cranswickite (MgSO₄·4H₂O). Knowledge of the compressibility of such minerals is critical to model mantle processes (e.g., salt diaprisim, plate tectonics, subduction) and the density structure of the outer three Galilean moons. The thermal expansion and structural stability of three sulfate minerals (i.e., rozenite (FeSO₄·4H₂O), starkeyite, and cranswickite) was characterised for the first time using neutron diffraction. Cranswickite transforms to starkeyite at 330 K, well above the maximum surface temperature of 308 K hitherto reported on Mars. Starkeyite likely undergoes a structural phase transition at around 245 K. The structure of this proposed low-temperature polymorph could not be determined but would be of great interest since the temperature drops below 245 K on equatorial Mars at night-time. Starkeyite was also studied by means of synchrotron X-ray diffraction but suffered radiation damage. No phase transition was observed in rozenite from 290 - 21 K, which contrasts with Raman data reported in the literature, where sharpening of vibrational modes upon cooling was misinterpreted as mode splitting and evidence for two phase transitions at temperatures relevant to the Martian surface. First-principles phonon frequency calculations provide evidence supporting the absence of vibrational mode splitting. A workflow to obtain reliable reference Raman spectra for space exploration was proposed and an optical centre stick for the simultaneous acquisition of neutron diffraction and Raman spectroscopy data at the HRPD instrument was commissioned. Lastly, the structure of a polymorph of hexahydrite (MgSO₄·6H₂O), most recently proposed in the literature, was shown to be unambiguously wrong.

This thesis explores the design, synthesis, optoelectronic properties, and photocatalytic testing of copper(I) complexes with a two- or three-coordinate geometry bearing N-heterocyclic carbene ligands. Our design strategies aim to avoid the failings of four-coordinate copper(I) complexes which are prone to Jahn-Teller distortion in the excited state. The first chapter provides an overview of the fundamental photophysical properties of transition metal complexes and an introduction to bimolecular energy and electron transfer processes. A mini-review of Earth-abundant photocatalysts is presented. Special attention will then be devoted to describing the design principles of copper(I) based photocatalysts (PCs). We begin by describing the photophysical and electrochemical properties of four-coordinate copper(I) complexes, followed by the design and applications of copper(I) complexes as PCs. Next, we provide a summary of the development of two- and three-coordinate copper(I) complexes, describing their photophysical properties and applications. Chapter 2 describes the synthesis, characterisation and optoelectronic properties of seven three-coordinate copper(I) N-heterocyclic carbene (NHC) complexes bearing N^N ligands, of the form of [Cu(IPr)(N^N)]PF₆ (where IPr is 1,3-Bis(2,6-diisopropylphenyl)imidazolium, and N^N is phen = 1,10-phenanthroline, bpy = 2,2'-bipyridine, dpa = 2,2'-dipyridylamine, mdpa = N-methyl-2,2'-dipyridylamine, dpym = di(pyridin-2-yl)methane, phdpym = 2,2'-(phenylmethylene)dipyridine, fludpym = 2,2'-(9H-fluorene-9,9-diyl)dipyridine). Six complexes underwent successful preliminary photocatalytic testing in two mechanistically distinct photocatalysis reactions: an Atom Transfer Radical Addition (ATRA) photoinduced electron transfer (PET) reaction between an alkyl halide and an alkene; and photoinduced energy transfer (PEnT) reaction of a vinyl azide to a vinyl nitrene, which subsequently rearranges to form a pyrrole. The complex [Cu(IPr)(phen)]PF₆ performed best in the ATRA reaction (77% NMR yield) out of six complexes tested, while complex [Cu(IPr)(phdpym)]PF₆ performed best in the PEnT reaction (59% NMR yield vs 66% obtained with [Cu(dmp)(BINAP)]BF₄). Chapter 3 reports the synthesis, characterisation and optoelectronic properties of a series of three-coordinate copper(I) NHC complexes bearing a dpa ligand, of the form [Cu(NHC)(dpa)]PF₆. Three complexes underwent preliminary photocatalytic testing, however their performance as PCs was poor. Chapter 4 reports the first example of a neutral linear two-coordinate Cu(I) complex Cu(IPrBIAN)(Cz) bearing an IPrBIAN NHC ligand, and after investigation of its optoelectronic properties, it was successfully applied as a PC in a proof-of-concept PET ATRA reaction (52% NMR yield). Cu(IPrBIAN)(Cz) also exhibited interesting dual emission properties in solution; this is seen as separate emission depending on excitation source for most solvents, and is especially strong in chloroform solution. The synthesis, characterisation, and optoelectronic properties of further derivatives of this complex bearing 3,6-substituted carbazolate ligands were also investigated. The final conclusions chapter summarises the results of each chapter and brings focus to the overarching aims and themes of the thesis. This chapter identifies key areas for future work in the field of two- and three-coordinate copper(I) complexes as photocatalysts, specifically the need to improve PC stability, investigate reaction mechanisms, and correlate structure-property relationships with photocatalytic performance. A need for standardisation of photocatalysis reaction set-ups is identified as a requirement for reproducibility of results within the field of photocatalysis.

Processes that can be described by systems of interacting particles are ubiquitous in nature, society, and industry, ranging from animal flocking, the spread of diseases, and formation of opinions to nano-filtration, brewing, and printing. In real-world applications it is often relevant to not only model a process of interest, but to also optimize it in order to achieve a desired outcome with minimal resources, such as time, money, or energy. Mathematically, the dynamics of interacting particle systems can be described using Dynamic Density Functional Theory (DDFT). The resulting models are nonlinear, nonlocal partial differential equations (PDEs) that include convolution integral terms. Such terms also enter the naturally arising no-flux boundary conditions. Due to the nonlocal, nonlinear nature of such problems they are challenging both to analyse and solve numerically. In order to optimize processes that are modelled by PDEs, one can apply tools from PDE-constrained optimization. The aim here is to drive a quantity of interest towards a target state by varying a control variable. This is constrained by a PDE describing the process of interest, in which the control enters as a model parameter. Such problems can be tackled by deriving and solving the (first-order) optimality system, which couples the PDE model with a second PDE and an algebraic equation. Solving such a system numerically is challenging, since large matrices arise in its discretization, for which efficient solution strategies have to be found. Most work in PDE-constrained optimization addresses problems in which the control is applied linearly, and which are constrained by local, often linear PDEs, since introducing nonlinearity significantly increases the complexity in both the analysis and numerical solution of the optimization problem. However, in order to optimize real-world processes described by nonlinear, nonlocal DDFT models, one has to develop an optimal control framework for such models. The aim is to drive the particles to some desired distribution by applying control either linearly, through a particle source, or bilinearly, though an advective field. The optimization process is constrained by the DDFT model that describes how the particles move under the influence of advection, diffusion, external forces, and particle-particle interactions. In order to tackle this, the (first-order) optimality system is derived, which, since it involves nonlinear (integro-)PDEs that are coupled nonlocally in space and time, is significantly harder than in the standard case. Novel numerical methods are developed, effectively combining pseudospectral methods and iterative solvers, to efficiently and accurately solve such a system. In a next step this framework is extended so that it can capture and optimize industrially relevant processes, such as brewing and nano-filtration. In order to do so, extensions to both the DDFT model and the numerical method are made. Firstly, since industrial processes often involve tubes, funnels, channels, or tanks of various shapes, the PDE model itself, as well as the optimization problem, need to be solved on complicated domains. This is achieved by developing a novel spectral element approach that is compatible with both the PDE solver and the optimal control framework. Secondly, many industrial processes, such as nano-filtration, involve more than one type of particle. Therefore, the DDFT model is extended to describe multiple particle species. Finally, depending on the application of interest, additional physical effects need to be included in the model. In this thesis, to model sedimentation processes in brewing, the model is modified to capture volume exclusion effects.

In this thesis we give an introduction to the drying and assembly of colloidal films. Then, we describe our work to develop a dynamical density functional theory (DDFT) model for the drying of colloidal films on planar surfaces. This theory is able to describe the microstructure of the colloidal films, including packing effects at interfaces and the stratification that occurs during drying. We consider mixtures of two different sizes of colloids. Firstly, we treat the three dimensional (3D) mixture as being a mixture of hard-spheres with density profiles that vary only in the direction perpendicular to the substrate, reducing the system to a 1D model. We also neglect the influence of gravity. This model is based on a DDFT with an implementation of fundamental measure theory (FMT) which can describe accurately highly confined hard-sphere fluids. Depending on the solvent evaporation rate, size ratio, and the initial concentrations of the two species, we observe varying degrees of stratification in the final dried films. Our model predicts some of the structures described in the literature previously from experiments and computer simulations. Secondly, we consider mixtures of hard disks (i.e. a 2D mixture) with a fixed 2:1 particle size ratio and with an additional attractive interaction between the particles, in order to explore the influence of phase-separation on the final film structure. In particular, this system exhibits variations in the density profiles both in the perpendicular and parallel directions to the substrate. We also replace FMT with a local density approximation (LDA) which enables us to obtain the 2D density profiles with limited computational resources. We explore the influence on the ordering of varying the initial concentrations and the evaporation rate. When the initial concentration is high and the evaporation rate is sufficiently high both phase separation and size segregation occur and our model shows how these influence the final dried film structures. We also explored a 2-step drying process, which makes phase separation occur at the region close to the substrate. Our observations of cases where we partially dry the dispersion and then stop evaporation to let the system relax, could be used to guide experimental work to obtain a specific film structures and may be useful in the coatings industry.

The ethanol oxidation reaction (EOR) has gained tremendous attention worldwide in electrocatalysis and fuel cells. Ethanol as a fuel has superiority in sustainability, renewability, low toxicity, and high theoretical energy den-sity compared with hydrogen and methanol. The electrooxidation of ethanol is hard to be achieved without the help of platinum (Pt)-group catalysts. How-ever, the scarcity of Pt has led to its high price, which significantly limits industrial production. Much effort has been devoted to palladium (Pd), an-other Pt-group metal with a larger reserve than Pt. A great many experimental works have been conducted to search for high-performance Pd-based cata-lysts. However, theoretical research is still lacking, including the mechanistic investigation and the rational design of electrocatalysts. Therefore, the first-principle calculations within the density functional theory (DFT) framework, which are powerful tools for theoretical studies, explore the heterogeneous catalytic reaction in direct ethanol fuel cell (DEFC). The ethanol electrooxi-dation reaction on Pd and Pd-based systems is studied, mainly on the activity and selectivity, respectively.

This thesis is centred around the interaction of few-molecule arrays with gold surfaces and the enhanced optical fields that occur in nanoscale junctions between gold nanoparticles (AuNPs). This behaviour is enabled by optically resonant collective electron density oscillations (and electrostatic coupling thereof) at the nanoparticle and nanojunction surfaces, which confine incident light to nanoscale volumes and boost the local electromagnetic field strength - a phenomenon known as plasmonic enhancement. This facilitates enhanced light-matter interactions with broad potential for advanced nanophotonic applications, including few-molecule sensing, reaction monitoring, quantum information systems, molecular electronic devices, nanometrology, light harvesting and catalysis. The utility of these plasmonic nanostructures is strongly influenced by the chemical structure of the molecular spacers used for nano self-assembly. In this work, I develop bespoke spacer molecules based on a set of functional design criteria for optimisation of the nanophotonic applications described above. Three different classes of molecular spacer are investigated in this thesis; their ability to self-assemble plasmonic nanostructures is characterised, and the functionality of the resulting nanostructures is assessed. The knowledge gained from each chapter is used for iterative re-design and optimisation of the molecular spacer system, as well as inspiration for future nanophotonic devices. The first class of molecular spacer is the bis-phthalocyanine (BPc) family: rare-earth sandwich complexes with a well-studied plethora of complex physicochemical properties and applications in sensing, optics and spin-resolved molecular electronics. BPcs were used here for their potential to create nanostructures with atypically large plasmonic enhancement; BPc@AuNP nanostructures were investigated from a plasmonic sensing and nanometrology perspective. No sensing behaviour was observed under the conditions tested, but an anomalously large shift in plasmon resonance wavelength was observed upon variation of the BPc metal centre. Several candidate hypotheses for this are discussed, and the results highlight the limitations of the approximations and assumptions often used to model tightly coupled plasmonic systems. The second spacer class uses supramolecular chemistry to provide control over orientation, intermolecular coupling and Au affinity of aryl viologen (ArV) molecules within plasmonic nanocavities, using a macrocyclic cucurbit[n]uril (CB[n]) host. Successful self-assembly of AuNPs using various ArV⊂CB[n] inclusion complexes was confirmed using a variety of spectroscopic and theoretical techniques. This demonstrates the possibility of multi-component molecular spacers, the modular nature of which represents a supramolecular toolbox for incorporating an expanded range of optoelectronic & chemical functionality into plasmonic hotspots. The third and final class of spacer incorporates additional optical and chemical functionality into the ArV structure via a porphyrin moiety. The design, synthesis and characterisation of the new porphyrin species and its metal complexes are reported, together with a brief investigation of the compounds' solvochromic properties and aqueous stability. The electronic structure, excitonic coupling and internal dynamics within the discrete inclusion complexes formed between the novel porphyrins and CB[n] are then probed with various spectroscopies. Finally, the porphyrins and supramolecular CB[n] complexes thereof are used to assemble plasmonic nanostructures, and the electronic interactions between the spacer and plasmonically enhanced near field are probed. This work uses established techniques to investigate the suitability of novel molecular junctions for advanced nanophotonic applications. In combination with cutting-edge plasmonic analysis techniques developed by others in parallel to this work, the functional spacer molecules developed here can now be used for enhanced exploration of light harvesting, electrocatalysis, charge transfer, charge transport, molecular switching and quantum cavity electrodynamics within self-assembled plasmonic nanojunctions.

Advancing the next generation of materials for solid-state devices requires an understanding of their underlying electronic structure; yet the disordered nature of many materials hinders progress in creating an atomic-level model. Although X-ray diffraction (XRD) is used to match crystalline models with experiment, XRD fails to characterize amorphous structures due to their lack of periodicity. However, nuclear magnetic resonance (NMR) and X-ray absorption spectroscopy (XAS) are two locally sensitive techniques that do not rely on periodicity. To compare amorphous models to experiment, it is then necessary to extend first principles calculations of NMR and XAS to amorphous materials. In this thesis, I apply first principles methods for calculating NMR and XAS spectra, to both crystalline and amorphous phases of alumina (Al₂O₃). First, I analyze the Al K-edge XAS for crystalline α- and γ-Al₂O₃ at finite temperature. Phase transitions from Al s to mixed s-p states are symmetry forbidden at 0 K, but incorporating the effects of temperature reproduces these transitions. Applying this method to γ-Al₂O₃ reproduces a peak at 1568 eV in the XAS which is not observed in the first principles calculations at 0 K. I then address the question of how to calculate these spectra for an amorphous phase. By using representative configurations of am-Al₂O₃ from ab initio molecular dynamics (AIMD), I calculate averaged NMR and XAS spectra for am-Al₂O₃. I show that both the experimental ²⁷Al isotropic chemical shifts and quadrupolar lineshapes are successfully reproduced using this method. Further, by calculating XAS spectra for each individual Al atom in this model, I am able to deconvolute the experimental XAS into site-specific spectra from four-, five-, and six-fold coordinated Al. Finally, I examine how the structure of am-Al₂O₃ is affected by hydrogen fluoride incorporation in Li-ion batteries, by calculating ²⁷Al NMR on protonated and fluorinated amorphous aluminas. These results are in line with experimental ²⁷Al NMR evidence for a pathway of HF attack involving the formation of AlO(6−x)Fx species during battery cycling.

For several decades, chemical modelling methods have underpinned the rapidly expanding and important field of computational chemistry. These methods have provided invaluable contributions to the understanding of asymmetric and catalytic reactions, in turn allowing the rational design of improved catalysts and reactions. However, recent developments in machine learning (ML) applied to reaction modelling are changing the shape of computational chemistry. ML models, once trained, could allow for much more rapid screening of chemical reactions. In this thesis, research into two distinct approaches to understanding organic reactions, modelling and ML, are presented. Several examples of the successful application of conventional density functional theory modelling are provided, followed by details of a new ML methodology which improves on current standards for the prediction of reaction barriers, whilst also providing mechanistic insights. A particular emphasis is placed on the advantages of each approach with respect to modelling asymmetric and catalytic reactions, and their subsequent application to drug discovery and natural product synthesis.

In this thesis, structures and properties of hybrid perovskites are studied at the atomic scale, with a focus on their optoelectronic applications. Three-dimensional hybrid perovskites are mainly discussed in this work for solar photovoltaic cells and a two-dimensional hybrid perovskite for a photodetector in the last chapter of results. A solar cell made of methylammonium lead iodide (MAPI) or CH₃NH₃PbI₃ has previously been measured to have excellent power conversion efficiency which was attributed to the material's band gap. This understanding of the relationship allows us to tune the band gap by mixing compositions so the theoretical efficiency of the solar cells can be optimised. Here, we first investigate the structural, energetic and electronic properties of the potential candidates, MAPI, CH₃NH₃PbBr₃, CH(NH₂)₂PbI₃ and CH(NH₂)₂PbBr₃ (FAPB). The results suggest they can be present at various crystal phases, including narrow-band-gap cubic-like and wide-band-gap hexagonal phases. Yet, the hexagonal phase of these bulk perovskites is more favourable at room temperature so the higher band gaps limit the theoretical efficiency of the solar cells. %ranging from 1.55 to 1.85 eV. Two methods of mixing are studied to improve the properties for solar applications, such as solid solution and superlattice. In the solid solution, we take into account all studied 3D perovskites mentioned above as constituents and compared their hexagonal and cubic-like phases. The results show that while the intermixed cubic-like phases of all combinations remain to have band gaps within the range of those of the constituents, their structural stability improves, i.e. more energetically favourable than hexagonal structures at room temperature. Therefore, the solid solution is suggested to be used as an alternative to bulk perovskite to build the single-junction solar cell or used for the multi-junction solar cell to improve the measured efficiency. In the superlattice, MAPI and FAPB are considered in various stacking layers. Both cubic and hexagonal phases of the heterostructures are examined in terms of structural, energetic and electronic properties. Promisingly, the cubic structures have shown improvement in band gaps and FAPB(2)/MAPI(1) even exhibits the optimal value of 1.34 eV that predicts the maximum theoretical efficiency of a single-junction solar cell. Moreover, these superlattices undergo a phase transition from hexagonal to cubic at various temperatures below the room temperature and the energy required to form a cubic interface is within the thermal excitation energy at room temperature. These findings conclude that superlattice structuring of hybrid perovskites will outcome the most efficient single-junction solar cell. The layered two-dimensional perovskite studied as a photodetector is 4-fluoro-phenylethylammonium lead iodide. The bandgap is shown in good agreement with the experiment measurement by collaborators. We predict the Schottky barrier of the electron at the interface between the perovskite and Au contact. Several mechanisms are studied to explain the measured absorption peaks within the band gap and iodine vacancy in the perovskite shows a similar absorption peak. The extent of this work has demonstrated two methods of structuring the mixed hybrid perovskites to examine the band gap and structural stability for solar cell applications. Both studies have shown the stability improves but the investigation of superlattice also successfully has predicted a mean to achieve the optimal band gap. Moreover, we have also studied the properties of the two-dimensional hybrid perovskite to support its experimental measurements in a photodetector device.

A family of coordination complexes of the type [Ru(SO2)(NH3)4X]Y exhibit optical-switching capabilities in their single-crystal state. This striking effect is caused by photoisomerization of metastable photoinduced states, which are metastable if kept at suitably low temperatures. This illustrates the possibility of these materials to operate as nanotechnological devices themselves, with the potential for optical actuation, optical-signal processing and nano-optomechanical function. This thesis presents a Plane-Wave (PW) - Density Functional Theory (DFT) based periodic methodology that can effectively model the dark- and light-induced structures, and single-crystal optical absorption spectra of these complexes. Initially, these crystalline materials are modeled via PW-based periodic and Molecular Orbital (MO)-DFT based molecular fragment models, and time-dependent DFT (TDDFT), to calculate their structural and optical properties, which are compared with experimental data. Both the periodic and molecular fragment models simulate these complexes effectively, with small deviations in key bond lengths, successfully replicating experimentally-determined structures. Both models also simulate trends in experimentally-determined optical absorption spectra effectively, with optical absorbance and coverage of the visible region increasing with the formation of the photoinduced geometries. This represents the first study of the optical properties of materials from this family of complexes via DFT-based methods. The PW-DFT study is then expanded to consider more complexes, including both photoswitches and transducers. Periodic models are shown to appreciate the competing chemical and crystallographic forces present in these complexes, namely the possible effects of the trans-influence and intermolecular interactions on the simulated optical absorption spectra. Density of states calculations are also showed to appreciate these forces, whilst illustrating the potential for optical tuning capabilities. The periodic models are also used to conduct a study of the photoisomerization process from the dark to the light-induced structures via the Nudged Elastic Band (NEB) method; thereby a 'cause-and-effect' relationship between photoisomerization and transduction is suggested to be dependent heavily on the intermolecular forces present. Synthetic work has also been carried out in parallel, resulting in the development of a more sustainable precursor-synthesis route and the synthesis of two new complexes. This thesis demonstrates that PW-TDDFT should be considered as a more than viable method for simulating the optical and electronic properties of this family of single-crystal optical switches whose functionality is based on linkage photoisomerism. It also illustrates the potential for optically tuning these complexes so that they can be developed with desired properties for tailored applications.

Mineral surfaces can significantly affect the mobility and speciation of actinides in groundwater, therefore, understanding this interaction is essential for the effective remediation of actinides in polluted areas. In this work, we use plane-wave density functional theory (DFT) to study these systems and we link our theoretical results to extended x-ray absorption fine structure (EXAFS) data. In Chapter 3, we investigate the adsorption of uranyl(VI), neptunyl(V) and plutonyl(V) on the basal surface of mackinawite. We find that uranyl(VI) and plutonyl(V) have similar affinities to the surface, whereas neptunyl(V) adsorbs more strongly. This reflects previous experimental findings where uranyl(VI) and plutonyl(V) display similar behaviour in the presence of mackinawite by undergoing reductive precipitation. This is in contrast to neptunyl(V) which has been found to undergo mononuclear inner-sphere adsorption to the surface and is reduced to Np(IV). We discuss the challenges of modelling the magnetic properties of mackinawite and the actinides, in particular, the issue of spin contamination in systems containing the paramagnetic actinide species. Chapter 4 investigates the speciation of uranyl(VI) during the sulfidation of ferrihydrite in order to elucidate the biogeochemical processes that can occur in the presence of sulfate-reducing bacteria. We use EXAFS and DFT identify a uranyl(VI)-persulfide species not observed before in environmentally relevant conditions. The effect of oxidation on the sequestering properties of mackinawite is studied in Chapter 5 by adsorbing uranyl(VI) to models of the mackinawite basal surface with oxygen atoms increasingly substituted for sulfur atoms. We find that adsorption of uranyl(VI) is stronger on mackinawite upon increasing substitution of oxygen for sulfur. We also identify a monodentate inner-sphere complex that agrees well with previous experimental EXAFS analysis of similar systems. There is debate as to whether uranium has preference for the basal or edge surfaces of the phyllosilicate mineral, muscovite. In Chapter 6, we investigate the interaction between uranyl(VI) and the basal and edge surfaces of muscovite as the experimental literature disagrees on the preference of uranyl(VI) for each surface. We find that uranyl(VI) generally has a greater affinity to the edge surface of muscovite over the basal surface and, while we cannot stabilise a complex on the basal surface that was suggested by previous interpretation of EXAFS data, we find a bidentate adsorption complex on the edge surface that agrees well with other available EXAFS data. Throughout this thesis, we show the benefits of coupling DFT with EXAFS for enhanced data analysis and highlight how using these techniques alone to analyse a system may lead to lesser quality results. These works have implications for cultivating methods for safe and effective environmental remediation and radioactive waste disposal, particularly in the context of the clean-up of legacy nuclear sites.

Homogeneous catalysis at transition metal centres is an essential and ubiquitous tool for the regioselective direct synthesis of fine chemicals from abundant resources. Quantum chemical models are used to gain insights into mechanisms of homogeneous catalysis with organo-transition metal complexes. The resulting overall kinetic barriers and barriers at branching leading to different products can help in steric and electronic tuning of ligands at the metal centre to control chemo- and regioselectivities. This thesis presents computational investigations on detailed mechanisms of alkene and alkyne alkoxycarbonylation at palladium catalysts and ruthenium-catalysed selective reduction of cardanol derivatives via transfer hydrogenation using state-of-the-art Density Functional Theory (DFT). We have explored catalytic methoxycarbonylation of ethene with a bidentate tertiary phosphine (DTBPX) and palladium. Out of three pathways, (i) carbomethoxy, (ii) ketene, and (iii) hydride-hydroxyalkylpalladium, the latter is the most plausible pathway with a computed selectivity of >99% towards the formation of methyl propanoate (MePro) and a reasonably low overall kinetic barrier of 17.8 kcal mol⁻¹. Consistent with experimental data, for a less bulky bidentate phosphine, the overall barrier increases to 30.1 kcal mol⁻¹. We have revisited in situ base mechanism of alkyne alkoxycarbonylation via a Pd catalyst with hemilabile P,N-ligands (PyPPh₂, Py = 2-pyridyl). Newly characterised acryloyl and η³-propen-1-oyl intermediates readily undergo methanolysis. The new mechanism is consistent with experimental data in terms of ligand effects on the reaction rates and selectivities, where (6-Cl-Py)PPh₂ has been shown to improve both selectivity and turnover. We further have explored the formation of a highly stable π-allyl intermediate as the reason for catalyst poisoning due to the presence of propadiene in technical propyne. Predicted regioselectivities suggest that at least 11 % of propadiene should yield this π-allyl intermediate, which requires an insurmountable barrier of 25.8 kcal mol⁻¹ to proceed to the product via methanolysis. A new ligand, (6-Cl-3-Me-Py)PPh₂, is proposed, which is more tolerant to propadiene poisoning (as only 0.2% of propadiene gets trapped at the π-allyl complex) and tremendously active (as decreases the overall barrier to 9.1 kcal mol⁻¹). Finally, we have calculated the complete pathway leading to the monoene cardanol at ruthenium-catalysed selective reduction of cardanol derivatives via transfer hydrogenation. The overall barrier of 29.2 kcal mol⁻¹ associated with the transfer hydrogenation leading to the monoene cardanol is surmountable under the elevated temperatures of the experiments (refluxing iso-propanol). The computed barrier of 46.6 kcal mol⁻¹ leading to a fully saturated cardanol product explains the 100% selectivity towards monoene cardanol.

Crystalline materials are known for their well-defined periodic structure and their properties have been widely applied in numerous fields. An ideal single crystal will exhibit a perfect ordered structure. However, in most crystalline materials defects and dislocations are commonly present and the vast majority of applications of crystalline materials concern polycrystalline materials rather than single crystals. In metals the effects of disorder and polycrystallinity have been studied extensively, but the effect on the properties of other crystals, such as organic molecular materials, are not fully understood. In this thesis the techniques of low-frequency vibrational spectroscopy by means of terahertz time-domain spectroscopy (THz-TDS) were combined with density functional theory (DFT) simulations to investigate the role and effect of disorder for small organic molecular materials including drug molecules as well as other emerging materials. Terahertz radiation is located between the far-infrared and microwave regions on the electromagnetic spectrum. At these frequencies photons excite a complex mix of inter- and intra-molecular interactions in solid state materials, particularly low-frequency vibrational modes in molecular crystals. Due to the complexities of lattice vibrations at such low frequencies, high-accuracy computational methods are necessary to interpret the experimental results. Such simulations are usually based on ideal, defect free, structures of crystals while experiments are performed on commercial or lab-synthesised samples that will exhibit some disorder. Careful comparison between the results from the ideal calculations and the experimental observation makes it possible to study the role of defects in the crystalline systems of interest. In this context THz-TDS can be considered as a complementary method to the classical crystallographic techniques, e.g. X-ray diffraction, to aid the effective structural analysis of crystals. The methodologies that were developed in this thesis are useful to provide more information for the design and the performance of novel materials such as metal-organic frameworks (MOFs) in general and MOF perovskites in particular from the perspective of low-frequency vibrations. This is meaningful for the future optimisation and screening of materials. For small organic molecules, the new method is helpful to better understand the mechanism of their phase transitions and to determine the structure of polymorphs, even in the presence of disorder. This idea is explored to investigate the fundamentals of the crystallisation process where the sensitivity of terahertz spectroscopy to both crystalline structure as well as liquid dynamics is exploited to gain further insight into the transition between disorder and order.

The 'forward problem' of ground-state density functional theory (DFT) constitutes finding the ground-state density n(x) that minimises a Kohn-Sham total energy functional defined using some exchange-correlation (xc) functional Exc[n]. Towards this end, the associated Euler-Lagrange equations, i.e. the Kohn-Sham equations, are often solved in practice, which demand a procedure that iterates an initial guess density to a selfconsistent density (the solution). A new framework is presented for evaluating the performance of self-consistent field methods in Kohn–Sham DFT. The aims of this work are two-fold. First, we explore the properties of Kohn–Sham DFT as it pertains to the convergence of self-consistent field iterations. Sources of inefficiencies and instabilities are identified, and methods to mitigate these difficulties are discussed. Second, we introduce a framework to assess the relative utility of algorithms, comprising a representative benchmark suite of over fifty Kohn–Sham simulation inputs, the scf-xn suite. This provides a new tool to develop, evaluate and compare new algorithms in a fair, well-defined and transparent manner. The 'inverse problem' of time-dependent (ground-state) DFT constitutes finding the time-(in)dependent Kohn-Sham potential vKS(x,t) that yields a given reference density n(x,t) upon solution of the time-(in)dependent Kohn-Sham equations. This inverse map can be unstable, particularly in the presence of low-density regions, and thus methods are designed to alleviate numerical difficulties in the present context. On the other hand, linear response time-dependent DFT centres around the first-order response of the xc potential due to perturbing densities – the so-called xc kernel fxc(x,x',w). Computing exact xc kernels represents a linearised version of the previous inverse problem: this state of affairs, whilst still challenging, is more manageable. Methods to ensure the robustness of exact numerical fxc computations are set out. In the context of inhomogenous onedimensional finite systems, these developments permit an improved understanding of fxc in itself, and in relation to various applications, such as the optical spectrum and ground-state correlation energies using the adiabatic connection fluctuation-dissipation theorem. We expect that certain key insights derived from this work will assist in the informed development of improved functional approximations.

This thesis reports on the effects of static and dynamic disorder on the structure and op- toelectronic properties of the hybrid metal halide perovskite family MAPbX3 (MA+ = methylammonium, CH3NH+3 , X = Cl−, Br−). Static disorder was introduced by halide substitution through solid state synthesis, providing better stoichiometric control compared to solution based techniques. Composition and temperature dependent X-ray diffraction and heat capacity measurements of MAPb(ClxBr1−x)3 revealed a suppression of the symmetry- lowering phase transitions of the end members in a wide range of intermediate compositions (0.2 < x < 0.8) down to T = 12 K. The suppression was not observed for the closely related inorganic CsPb(ClxBr1−x)3 system, highlighting the importance of the MA+ cation in direct- ing the crystal structure. Density functional theory calculations confirmed the experimental observations of the hybrid and inorganic mixed-halide systems. The findings are consis- tent with the formation of an orientational glass on the MA+ sublattice. Temperature and composition dependent photoluminescence measurements showed that photo-induced halide segregation occurred only in the orientational glass forming compositions. The local structure of the hybrid metal halide perovskites in the presence of static disorder was investigated using pair distribution function analysis of composition and temperature dependent X-ray and neutron total scattering of d6-MAPb(ClxBr1−x)3. It was found that both the local structure (r < 10 Å) and the average structure (r > 10 Å) at room temperature were well described by the same space group, in contrast to previous reports. Suppression of the symmetry lowering phase transitions in the local structure of the intermediate compositions was confirmed, corroborating the average structure measurements. The effect of dynamic disorder was studied by time resolved optical pump - diffuse X- ray probe measurements on single crystals of MAPbBr3. Anomalous time delays in the onset of changes in the scattered diffuse intensity revealed the formation of polaronic strain fields on length scales of several nm and time scales of tens of ps. Correlation with time resolved reflection and photoluminescence measurements under similar conditions showed that polaron formation led to an increase of the carrier effective mass.

The focus of this thesis is to understand a variety of emergent materials properties that are driven by quantum phenomena. A range of materials are investigated where the crystal, electronic and magnetic structures are delicately coupled to give rise to intriguing macroscopic properties. Computational methods are the primary tool for tackling these problems. This is largely centred around quantum mechanical, ab initio calculations using density functional theory (DFT), but also includes mean-field analyses and stochastic simulations of a model Hamiltonian. Tin telluride, SnTe, is a crystalline topological insulator with potential applications in a new generation of spintronics devices. In practice, SnTe shows a low temperature ferroelectric distortion and contains a large number of bulk carriers from Sn vacancies, so stands as a rare example of coexistence between metallicity and ferroelectricity. The implications of these effects for topological and transport properties require accurate modelling of the electronic structure. Here, in close collaboration with experiment, the evolution of the Fermi surface across this structural transition is probed by calculating quantum oscillation frequencies. The image analysis tools of Mathematica were exploited to develop a code for computing these frequencies from DFT electronic structure calculations. Agreement between experiment and theory is crucially dependent on the crystal structure. Calcium ruthenate, Ca2RuO4, is a layered perovskite compound with a rich phase diagram, which can be traced back to its strongly correlated electronic structure. Hydrostatic pressure can be used as a means to manipulate its crystal structure, which encourages several interesting effects. In particular, Ca2RuO4 undergoes anomalous expansion of the c axis, and a first-order structural transition coupled with a Mott insulator-metal transition. Here, this pressure response is investigated with DFT+U calculations, which account for the importance of electron correlation by adding an on-site Hubbard-like repulsion term. This work presents the first fully self-consistent electronic structure for Ca2RuO4, obtained from optimised crystal structures along a sequence of pressures. This appreciation of the coupling between lattice and electronic degrees of freedom sheds some light on its unusual phase diagram. The insulator-metal transition is reproduced and naturally coincides with a structural transition and associated orbital order. For the metallic phase, a complex energetic landscape with several competing phases emerges. Uranium gold, UAu2, is a heavy fermion metal with a complex spin-density-wave (SDW) phase at low temperature. This phase consists of frustrated, incommensurate ordering that is very robust in external fields, but suppressed by pressure to reveal unconventional superconductivity. The origin of this exotic magnetic ordering is of interest here, which is explored by several different approaches with DFT+U. Both itinerant and local-moment pictures of the magnetism are entertained. Fermi surface nesting is shown to be ineffective, but mapping the system to a Heisenberg model and computing effective exchange interactions identifies an instability towards modulated order. In addition to these material-specific investigations, the treatment of longitudinal magnetic fluctuations in computational methods is studied. Magnetic fluctuations are important for understanding materials on the border between itinerant and local-moment magnetism. The continuous-spin Ising (CSI) model is investigated here as a phenomenological model of these fluctuations. Using a bespoke simulation technique this model is extensively explored, firstly on a cubic ferromagnet and secondly on a highly frustrated, stacked triangular lattice with a variety of interaction topologies. The introduction of fluctuations is shown to alter the ground state of the prototypical frustrated triangular lattice, and to enhance the transition temperature of more severely frustrated systems. In all of these cases, different degrees of freedom in the system couple to one another, either to make an accurate theoretical description difficult, or to give rise to unexpected emergent properties. Both SnTe and Ca2RuO4 represent examples of delicately coupled crystal and electronic structures. In SnTe, the tuning of the crystal structure is vital to correctly describe the Fermi surface, while in Ca2RuO4 the Ru orbital structure very directly determines the structural properties, and drives the unusual pressure response. UAu2 introduces a non-trivial magnetic structure, which requires careful treatment of electron-electron interactions to locate. In the study of the CSI model, altering the interaction topology, which acts as a proxy for manipulating the underlying electronic structure, has drastic implications for the role of magnetic fluctuations in the system.

Solid-state materials find ubiquitous use in modern technology - from semiconductors in electronics to steel in buildings and superconductors in MRI machines. Theoretical understanding of the atomic-scale behavior of these materials can be leveraged to design new materials with desirable properties. In this thesis, we investigate the challenges that arise when this is attempted in practice. Accurate and inexpensive methods to tackle the atomic-scale problem are a prerequisite for materials discovery. We begin with a description of existing methods. This is followed by the development of a Monte Carlo method to calculate expectation values from the many-body picture without the need for a trial wavefunction, which is both a fundamental, and practical, limitation in existing techniques. Having explored first-principles methods, we turn to their use in understanding materials, beginning with an investigation of the structure of Lithium. Structure searching calculations result in a mixed-phase model at low temperatures, in good agreement with previous experimental and theoretical results. The quasi-harmonic treatment of finitetemperature thermodynamics is extended to include anharmonic nuclear vibrations, which are shown to not alter the phase diagram despite the small mass of the Li atoms. Focus then shifts towards leveraging these same methods to discover novel superconductors. This begins with an investigation of the LaH10 and YH10 compounds, where a new hexagonal phase of LaH10 provides an explanation for recent experimental measurements. Machine-learning techniques and novel screening methods are then employed to discover hydrides of Rb and Cs that exhibit superconductivity at significantly lower pressures than LaH10. Optimizations to, and automation of, the workflow then enables the discovery of superconductors on an unprecedented scale, leading to hundreds of new high-temperature superconductors. Throughout the thesis, the importance of structures that are saddle-points of the energy landscape becomes apparent. The thesis closes with the development of a new algorithm to locate saddle-points that requires no additional information beyond that used by the cheapest existing methods. This thesis demonstrates that there is progress to be made at every stage of the firstprinciples materials discovery process and highlights that improving the workflow itself is a non-trivial, but fruitful, pursuit.

Polymorphism, the ability of a material to exist in multiple structures, is a general phenomenon that is important in a wide range of fields from single crystal organic electronics to pharmaceuticals, food and explosives. This extensive impact makes predicting the existence and stability of polymorphs valuable, yet due to the large configurational space and small energy differences it remains a challenge. Here the two normal pressure polymorphs of coronene, a model molecular system for nanographenes and disk like organic semiconductors, are investigated by Raman spectroscopy and dispersion corrected Density Functional Theory (DFT-D). Gamma-coronene is the naturally occurring form, whilst the low temperature beta-phase, only recently discovered in 2015, requires the application of a magnetic field during crystal growth to form crystals in standard conditions. This work investigates the crystal growth of gamma-coronene, the vibrations of both polymorphs and their thermodynamic phase stabilities. High-purity crystals of gamma-coronene were successfully grown using a physical vapour transport method. Crystal growth of beta-coronene was attempted, but no crystals of beta-coronene were formed. Instead the beta-phase was accessed by cooling gamma-coronene crystals below the phase transition temperature of ~150 K. Structures of both polymorphs relaxed using DFT-D3 reproduce experimental lattice parameters to within 1.6% (2.1%) for gamma- (beta-) coronene. Raman active intramolecular and lattice vibrations have been followed across the gamma- to beta-phase transition, with DFT-D3 calculations used to interpret the Raman spectra and, on the basis of polarisation dependence of peak positions and intensities, mode assignment performed. The vibrational density of states and dispersion curves are calculated and Gibbs free energies in the harmonic and quasiharmonic approximations determined. At all temperatures and in both approximations gamma-coronene is predicted to be the most stable polymorph with no phase transition indicated. The error in the calculated Gibbs free energies is estimated to be 10-20 meV. Recommendations for future work are made. Further investigation is required into the crystal growth of gamma-coronene to produce a reliable and reproducible method. Vibrational frequency calculations including anharmonic effects would be beneficial in solving the few remaining mysteries in the intramolecular Raman spectra. Calculating phase stabilities with higher level theories is recommended, specifically relaxing structures and calculating lattice energies using the hybrid many-body interaction method.

Heterogeneous catalysis is universally acknowledged as a paramount approach in a wide range of the chemical, biological, and energy industries. Moreover, heterogeneous catalysis has also been applied to solving the problem of many aspects in our daily life, such as environmental enhancement, energy shortage, efficient synthesis. Just as its name implies, heterogeneous catalysis is catalysis where the phase of catalyst differs from the reactants or products. Normally it usually happens at the gas-solid or liquid-solid interface. This PhD theses mainly addresses two types of heterogeneous reactions: the one happens at the interface between gas and solid (chapter 3 and chapter 4), and the other occurs between liquid and solid (chapter 5 and chapter 6). According to the reaction properties, we tackle these two kinds of reactions with different methods. The gas-solid reactions are solved by traditional Density Functional Theory (DFT) method; while liquid-solid reactions are carried out using ab initio Molecular Dynamics (MD) simulation. Chapter 1 focuses on the background and theoretical methods applied in the projects. In chapter 2, fundamental theories and techniques in this thesis are introduced in detail, as well as VASP software packages. Chapter 3 comprehensively introduces the mechanism of Fisher-Tropsch process on stepped Ru(0001) surface. In this part, two most possible mechanisms are both discussed: CO insertion and carbide mechanism. Additionally, the coverage effect is introduced to acquire more realistic results, based on which we reveal the selectivity, activity and ratedetermined step of Fisher-Tropsch process from syngas to C2 compounds. Chapter 4 presents the distinct catalytic performances on three different types of NiO surface. The methane combustion process is investigated as a probe on these surfaces. In this part, activation of methane is studied under different coordination environment of Ni2+, such as sheet NiO, cubic NiO and octahedral NiO represented by NiO(110), NiO(100) and NiO(111), respectively. The mechanism schemes of the pathway are all simulated to search the most favorable methane oxidation route. Chapter 5 presents the calculation on Pt(111)/H2O interface to research the preference for CO adsorption in liquid with an advanced Molecular Dynamic (MD) approach, namely umbrella sampling. Both the hollow site and the top site are simulated for CO adsorption and desorption with free energy chemisorption energy obtained. In chapter 6, the slow-growth (SG) approach and constrained molecular dynamics (CMD) are adopted and combined to address the oxygen evolution reaction (OER) on the interface between water and IrO2(110) surface under electrostatic potential environment. The surface is terminated by adsorbed oxygen atoms on the iridium atoms to account for the electrochemical potential in experiments. The different reaction pathways are discussed to figure out the most possible mechanism. In order to make the reaction environment closer to the realistic condition, a constant potential model is achieved by correcting constant potential charge via workfunction calculations.

This thesis investigates the optical, kinetic, and thermodynamic properties of soot precursor molecules, namely polyaromatic hydrocarbons (PAHs), by applying ab initio quantum chemical methods. In particular, density functional theory (DFT) is applied to study the properties of several different types of PAHs, including curved PAHs, localized π-radical PAHs, and cross-linked PAHs. These studies help model the gas phase chemistry that leads to the formation of these different types of PAHs, and also help assess their relevance to the formation of soot. The optical band gaps (OBGs) of curved, cross-linked, and radical PAHs are computed using a DFT method corroborated with UV/Visible spectroscopy measurements. Curved PAHs are shown to increase the OBG due to hybridisation changes. In contrast, π-radical character was found to decrease the band gap. Crosslinks are observed to minimally impact the OBG of the monomers. The effect of σ-radicals on the OBG was also shown to be negligible. The results suggest that curved and π-radical PAHs of moderate size can also explain the optical properties of flames. The persistence of the polarity of curved aromatics in flame conditions is investigated by using DFT to calculate their barriers and rates of inversion. Curved PAHs above 11-15 (~ 0.8 nm) rings in size were seen to be unable to invert at flame temperatures. This is seen to be a function of the number of pentagons, and hence curvature. Ab initio quantum molecular dynamics of a 1 nm curved PAH and C₃H₃⁺ chemi-ion suggest molecular dipole fluctuations of 10-20%, with the chemi-ion and PAH being bound for the entire simulation. This suggests curved PAHs are persistently polar at 1500~K and can bind substantially to ions in flames. The kinetics of seven-member ring formation in PAHs containing a five-member ring is investigated. Seven-member ring formation by the hydrogen-abstraction-acetylene-addition (HACA) mechanism is studied for two different PAHs, one closed shell and one resonance-stabilised-radical (RSR) PAH. The seven-member ring forms more quickly for the RSR PAH. Seven-member ring formation by four different bay closure processes is also studied. The rate constants determined for the pathways are then used in kinetic simulations in 0D homogeneous reactors. The hydrogen abstraction based pathway is seen to dominate until higher temperatures, where the carbene pathway takes over. The results suggest that seven-member ring formation in PAHs containing a five-member ring is possible at flame temperatures. The impact of localized π-radicals on soot formation is explored by developing a simple mechanism for their formation and computing their relative concentrations under flame conditions using 0D homogeneous reactor simulations. It is seen that flame temperatures at the onset of nucleation (1400-1500~K) promote the formation of localized π-radicals on rim-based pentagonal rings, whilst lower temperatures favor fully saturated rings, and higher temperatures favor the σ-radical. A kinetic Monte Carlo study indicates that multiple localized π-radicals can form on a single PAH suggesting localized π-radicals on rim-based pentagonal rings could be important to understanding the mechanism of soot formation. The rate and equilibrium constants of cross-linking reactions between PAHs of various reactive edge types is computed. The forward rate constants confirms that reactions involving aryl σ-radicals are generally fast, but the reactions between aryl σ-radicals and localized π-radicals were notably faster than others. Computed equilibrium constants showed that reactions involving σ and π-radical PAHs are the most favorable at flame temperatures. Calculations for larger PAHs showed that the formation of bonded-and-stacked structures results in substantially enhanced equilibrium constants for the reaction of two large localized π-radicals. This suggests that combined physical and chemical interactions between larger π-radical PAHs could be important in flame environments.

Antisense-Oligonucleotides (ASOs) are a next generation of therapeutic pharmaceutical, synthesised to be complementary to short lengths of mRNAs that are implicated in diseases such as Huntingtons and Spinal Muscular Atrophy. ASOs reduce or alter the expression of target mRNA. The secondary structure of ASOs is intrinsically linked to their binding affinity and efficacy. Secondary structure unfolding and folding can occur as a result of pharmaceutical (temperature and concentration changes) and environmental stresses (buffer and pH changes). Structural characterisation of ASOs using crystallography and Nuclear Magnetic Resonance (NMR) can be both expensive and challenging. Vibrational spectroscopies (Raman Spectroscopy, Fourier-Transform Infrared Spectroscopy, Raman Optical Activity and Circular Dichroism) have the potential to be quick methods for relating small changes in oligonucleotide secondary structure to stability or efficacy, prior to experiments with Small Angle X-Ray Scattering (SAXS)/NMR for more detailed structural analysis. Vibrational spectroscopies were used on increasingly complex single-stranded RNA (ss-RNA) structures. Raman is used to look at distinct spectral features of Nucleotides; examples include the sugar pucker of the Ribose ring and Imidazole ring peaks in Purines. A collaboration to generate Density Functional Theory (DFT) data has been used to improve on assignments of RNA nucleotides. Raman peaks are then identified for mono-, di- and tri- phosphate RNA nucleotides as well as Poly-RNA samples (Polyuridylic acid) and the hybridisation of a short 12-mer oligo. This library is used to assign the identity of an additional nucleotide within an N+1-mer of an AstraZeneca/Ionis Pharmaceuticals ASO: AZD9150. Combining Raman Optical Activity with Raman spectroscopy has previously been used to characterise secondary and tertiary RNA structural motifs, including a U-C mismatch and a hairpin (Hobro, 2007). In two AstraZeneca/Ionis Pharmaceuticals ASOs (AZD4785 and AZD Compound A), nucleotide and phosphate backbone modifications (such as Locked Nucleic Acids) affect spectroscopic assignments by inducing new secondary structure conformations. Raman has been used to look at experimental conditions related to pharmaceutical stresses (Hobro, 2008); concentration, buffer exchange and pH changes were observed to cause structural changes in AZD4785. SAXS is used to look at a fibril like hybridisation of ASOs at a high concentration; following this, NMR NOESY data is used to demonstrate how heat can prevent this conformation, potentially increasing drug efficacy. Raman, ROA and SAXS were used to observe the structure of ss-RNA within the Cowpea Mosaic Virus and detect changes following modification of the RNA to encode for GFP. Transmission Electron Microscopy and SAXS were used to compare viral capsids of a CPMV virus and a Virus Like Particle. The potential of plant viruses to be used to produce unmodified RNA on a large scale, as well as act as a delivery system for ASOs, is discussed.

Improving the effectiveness of forensic fingerprinting reagents (FFRs) has been a challenge in the field of forensic chemistry for the previous four decades. Fluorescent methods offer significant improvement over their non-fluorescent counter parts and the focus of several previous studies have been to develop new fluorescent FFRs via a synthetic trial-and-error process. In this study, a computational Density Functional Theory (DFT) approach is used to work towards predicting the fluorescence activity of a system in an attempt to contribute to the development process. Aiming to inform the fluorescent FFR design process, this study asks: Is time-dependant DFT (TDDFT) able to replicate non-fluorescent behaviour of existing FFRs by identifying non-radiative features along their excited state potential energy surface (PES)? Reporting the validation of TDDFT as a predictive tool, this study presents the accurate calculation of optical properties belonging to products of the existing FFRs, 2,2-dihydroxyindane-1,3-dione (ninhydrin) and 1,8-diazafluoren-9-one (DFO), and has proposed chemical structures of the products of 1,2-indanedione and 2-hydroxy-1,4-napthoquinone (lawsone). Investigation of the PES representing a mechanism related to excited state intramolecular proton transfer (ESIPT) in the ninhydrin product, DYDA, and the DFO product revealed non-radiative characteristics in the former, indicating that an internal 10° dihedral rotation of DYDA leads to a non-radiative relaxation mechanism. The relevance of these findings with respect to the solid-state structures is also offered through analysis of the crystal packing in previously reported X-ray crystal structures. It is recommended that further investigation be carried out on a larger set of chromophoric systems to further validate the presented workflow, validation of which will offer an informative predictive tool to be utilised in a product-to-reactant approach to the design of new fluorescent FFRs.

In high-Cu pressure vessel steels used for nuclear fission reactors, the formation of Cu rich precipitates (CRPs) substantially contributes to the reactor pressure vessel's (RPV) embrittlement following long periods of neutron irradiation and elevated temperatures. The RPV cannot easily be modified or replaced once reactor operation has begun making RPV embrittlement a significant factor in preventing reactor lifetime extensions, particularly given the RPV is a safety critical component. To limit CRP formation and embrittlement, strict limits are placed on the Cu contents of modern RPV steels. Even in reduced quantities Cu may still influence the late-life embrittlement of RPVs by assisting the formation of MnNiSi-rich complex precipitate phases. In this project we work to understand Cu nanoprecipitate morphologies in ferritic RPV steels, and how the surfaces of those nanoprecipitates interact with other solute species, using density functional theory (DFT). In our first manuscript we use DFT to calculate the interfacial energy densities (gamma) of six Fe-Cu interface orientations that may form the surface of a CRP's Cu nanoprecipitate core region. We identify the {110} orientation as possessing the lowest energy density, allowing us to infer that Cu nanoprecipitates are likely to take morphologies with surfaces dominated by this orientation. Using Wulff construction and optimisation techniques we identify low energy Cu nanoprecipitate morphologies based upon our DFT derived gamma values. Through these techniques we find that as Cu nanoprecipitates increase in size, their surfaces are increasingly comprised of non-{110} orientated interfaces allowing for more spherical geometries. Our second and third manuscripts demonstrate Ni possesses a reasonably strong attraction to Fe-Cu interfaces, which is significantly enhanced by the presence of vacancies on the interface. Si is seen to interact more weakly and less attractively than Ni with undecorated interfaces, with significant repulsion observed for higher interfacial Si concentrations. However, we see that the presence of vacancies and Ni on the interface can result in substantially more attractive Si segregation. These findings suggest it is likely that Ni segregates to the Fe-Cu interface initially after which co-segregation interactions draw Si to the interfacial region. With a sufficiently high vacancy density it may be possible for Si to segregate to Fe-Cu interfaces undecorated by Ni. These findings demonstrate that the formation of large mixed-solute shells around the Cu nanoprecipitate core region is likely to require some degree of co-segregation interaction and may be further enhanced by elevated vacancy densities.

Condensed matter physics spans molecules, fluids, and solids. Mathematical models have been developed to simulate physical systems, but exact solutions are special leaving the many-body Schr\"odinger equation analytically intractable. Therefore, approximations have to be constructed to make those difficult-to-solve problems tractable. This thesis adapts different levels of approximation, developing an exact formalism for a quantum operator, investigating the origins of intriguing phenomena in solids using first principle methods, and heuristic data-driven machine learning to guide biomedical developments. The quantum Monte Carlo method is used to study molecules where the formalism for force constants matrix is created for the first time using variational and diffusion Monte Carlo, which are the most accurate technique in electronic structure calculation but more resource demanding. We make the atomic relaxation and vibrational frequency calculation possible via the direct approach. The performance has been tested on a diverse set of case studies, with varying symmetries and mass distributions, and shows the established formalism outperforms leading computational methods over an order of magnitude in terms of the accuracy of vibrational frequency relative to experiment. This opens the way for self-contained quantum Monte Carlo simulations from relaxing atomic positions to calculating vibrational frequencies without being limited to the accuracy from density functional theory for structure relaxation. Density functional theory is applied to investigate the large and complex solids of perovskites and heterostructures efficiently. We explore the origins of Raman modes for transient photophysics in layered $2$D perovskites and discover the twisting of organic cations could influence the excitons in the inorganic layer. Understanding the coherent interplay of excitons, spins, and phonons facilitates the design of efficient light emission devices and solar cells. Inspired by an unexpected exchange bias effect in topological insulator superlattices, we introduce magnetic models to investigate the doping effect and predict the interfacial coupling between dopants induces exchange bias. We provide a new pathway for achieving the high-temperature quantum anomalous Hall effect in exchange bias stabilised magnetic systems by interface engineering. Finally, we show machine learning can deliver new insights for systems lacking theoretical models, and where data collection is expensive and difficult. We design a neural network model capable of handling missing data and estimating prediction uncertainties. We apply it to study the efficacy of biomedical stem cell fluids for cartilage repair and identify critical properties, optimal dose, and predicted therapeutic outcomes for personalised therapy. We provide references for scientists and clinicians to design better therapy strategies, and the technology can be adapted for addressing research problems across different subjects.

This PhD thesis reports computational investigations of the binding of dihydrogen to a selection of transition metal hydrides to determine and quantify the interaction between the dihydrogen and substrate. The work has been performed using Density Functional Theory. The impetus for these studies came from materials developed by the Antonelli group who have shown that the materials MH3 (M= Ti, V, and Cr) can bind dihydrogen in such quantities that is practical for implementation into a vehicular energy system. An exploration of these materials showed that they can all, to varying degrees, undergo the Kubas interaction, confirming the experimental interpretation of the binding. More recently the novel material KMH-1 (Kubas manganese hydride) was developed by the Antonelli group showing even greater promise as a storage solution for hydrogen. Computational techniques were used to confirm the nature of the material, suggesting a manganese oxidation state of around +1.2, as well as Kubas binding of the H2. Further mechanistic study was carried out concerning this material to find potential reaction routes for its production from the precursor material bistrimethylsilylmethyl manganese (II). An extension of study on the KMH-1 material was performed to include the other transition metals from Ti to Zn to investigate their potential hydrogen storage properties.

In this thesis, we explore the formation of char during lignin pyrolysis. This is accomplished using computational chemistry to study the energetics and mechanisms of reactions involved in lignin char formation. In Chapter 1, the background for the project is given, highlighting the global climate and energy crises, as well as providing an overview of biomass, biofuels, and biomass thermochemical conversion techniques. Lastly, the research gap is outlined and the key research topic of the thesis is introduced. In Chapter 2, we assess the stability of a range of lignin derived phenolic bio-oil compounds through the calculation of bond dissociation enthalpies. Here we show that methoxy functional groups exhibit much lower bond dissociation enthalpies than other groups found in lignin derived phenolic compounds which is in agreement with literature reports of their scarcity at higher pyrolysis temperatures. Conversely, unsaturated functionalities exhibit high resistance to homolytic cleavage and are more thermally stable. In Chapter 3, we propose a reaction mechanism for the formation of aromatic char clusters from the products of lignin decomposition. Here, through investigation of sixteen parallel pathways, we show clearly how unsaturated lignin derived monomers may concatenate through cycloaddition reactions and subsequently aromatise through elimination reactions to yield polycyclic char clusters. Chapter 4 is concerned with the aggregation of these char clusters through a continuation of the reactions reported in the previous chapter. By employing the Same Level Different Basis approach, the growth of condensed char clusters up to eleven rings is modelled and the impact of cluster size on reaction barriers is assessed. Chapter 5 contains concluding remarks that draw upon the results reported in Chapters 2-4. This chapter also proposes new avenues for the investigation of lignin char formation and the potential impact of the work contained herein to other closely related fields.

The Fischer-Tropsch process has the potential to be fundamental to a future without dependence on fossil fuels. It converts syngas, a readily available resource, into high quality hydrocarbons, with water being the primary byproduct. Like many gas-to-liquid processes, it is catalysed on a transition metal surface, and the lifetime of the catalyst bed largely dictates the process’s economic viability. Predictive computational models can shed light on the mechanisms driving catalyst deactivation. This work focuses particularly on reactors with a titania-supported cobalt catalyst. One part of this project is an investigation using VASP studying the adsorption and mobility of several cobalt species that might form on the TiO2 support surface. It is found that reactor species generally have a strong effect on the binding properties of cobalt, and that this effect could either strengthen or weaken its bond to the surface depending on how reactive the functional group is with the support surface. In particular, the carbon monoxide feedstock was found to favourably bind to surface- adsorbed cobalt and create highly mobile species. In practice the support surface is rarely dry, and this effect is also found on a model hydrated surface. This painted a clear picture that the carbon monoxide feed may have an effect on the sintering process by inducing surface and gas-phase transport of highly dispersed cobalt. Plane-wave DFT suffers from unfavourable cubic scaling and its extended basis makes vacuum space costly, limiting its applicability to large clusters and surface structures. The linear-scaling DFT code ONETEP is a good candidate for investigating these classes of system. While its metals treatment for systems smaller than the thousands of atoms scale using ensemble DFT (EDFT) is also cubic-scaling, it is able to offload a lot of the cost of the calculation onto linear-scaling parts and also maintains a linear-scaling memory cost. Another part of this project was to develop ONETEP to be able to perform studies of chemistry on adsorbed and free catalyst nanoparticles. Two main pieces of crucial functionality have been added to ONETEP - free-spin EDFT and nudged elastic band transition-state searching. The former allows ensemble DFT to be performed at non-integer net spin and non-integer charge, and also adds the ability to relax the spin state during a calculation - previously ONETEP was constrained to fixed integer net spin. This is crucial in cases where the net spin of a magnetic system is not necessarily known or may be altered by, for example, surface adsorbates. The latter is a popular and robust transition state searching method that reliably minimizes a path connecting a product and reactant. The dimer method is also being developed for ONETEP primarily as a transition state refinement tool. Early applications of the new functionality in ONETEP is demonstrated in an investigation of carbon monoxide binding on cobalt HCP and FCC nanoparticles of around 50 atoms. These adsorption energies are compared, where available, to surface adsorption energies from literature. Generally, the abundance of edges on these small particles make surface adsorption energies site dependent and different to clean surface values, and adsorption sites near edges are generally stronger than the surface values. Additionally, two CO dissociation pathways on the FCC cluster are examined, starting from the surface making up the majority on the FCC Wulff particle. A modest decrease in activation energy is identified, and the presence of new pathways involving particle edges is highlighted for future study.

In this thesis we focus on calculating the shape of small bubbles and droplets near surfaces, in regimes where intermolecular forces are significant. In the first part of this thesis we focus on vapour nanobubbles where we use classical density functional theory (DFT) to determine the interfacial free energy (the binding potential) of simple model fluids in contact with a planar surface. This is done by calculating sequences of constrained density profiles for varying amounts of vapour adsorbed between the wall and the bulk liquid. This allows us to determine multi-scale properties of fluids at interfaces, and thereby determine the structure and the thermodynamics of vapour adsorption at solvophobic interfaces and how these depend on the microscopic properties of the fluid. We then use the binding potentials obtained as an input to the interfacial Hamiltonian (IH) model and study the properties of vapour nanobubbles at equilibrium.

The perovskite family of materials is extremely large and provides a template for designing materials for different purposes. Among them, hybrid organic-inorganic perovskites (HOIPs) are very interesting and have been recently identified as possible next generation light harvesting materials because they combine low manufacturing cost and relatively high power conversion efficiencies (PCEs). In addition, some other applications like light emitting devices are also highly studied. This thesis starts with an introduction to the solar cell technologies that could use HOIPs. In Chapter 2, previously published results on the structural, electronic, optical and mechanical properties of HOIPs are reviewed in order to understand the background and latest developments in this field. Chapter 3 discusses the computational and experimental methods used in the following chapters. Then Chapter 4 describes the discovery of several hybrid double perovskites, with the formula (MA)$_2$M$^I$M$^{III}$X$_6$ (MA = methylammonium, CH$_3$NH$_3$, M$^I$ = K, Ag and Tl, M$^{III}$ = Bi, Y and Gd, X = Cl and Br). Chapter 5 presents studies on the variable presure and temperature response of formamidinium lead halides FAPbBr$_3$ (FA = formamidinium, CH(NH$_2$)$_2$) as well as the mechanical properties of FAPbBr$_3$ and FAPbI$_3$, followed by a computational study connecting the mechanical properties of halide perovskites ABX$_3$ (A = K, Rb, Cs, Fr and MA, X = Cl, Br and I) to their electronic transport properties. Chapter 6 describes a study on the phase stability, transformation and electronic properties of low-dimensional hybrid perovskites containing the guanidinium cation Gua$_x$PbI$_{x+2}$ (x = 1, 2 and 3, Gua = guanidinium, C(NH$_2$)$_3$). The conclusions and possible future work are summarized in Chapter 7. These results provide theoreticians and experimentalists with insight into the design and synthesis of novel, highly efficient, stable and environmentally friendly materials for solar cell applications as well as for other purposes in the future.

This thesis studies the adsorption behaviour of aromatic molecules on iron surfaces using density functional theory (DFT) calculations. The adsorbates studied are benzene (C₆H₆), naphthalene (C₈H₁₀) and quinolinium (C₇H₁₀N⁺) as well as a molecule composed of these fragments known to inhibit acid corrosion on steels used in the oil and gas industry (naphthylmethylquinolinium, C₂₀H₁₆N⁺ or NMQ+). This work represents an effort towards a mechanistic understanding of acid corrosion inhibition of steel as well the development of a general understanding of aromatic adsorption on iron, which has rarely been studied computationally or experimentally. First, the results of a DFT study of benzene adsorption on the three most stable surface facets of bcc iron, including flat {110}, kinked {100} and stepped {211} surfaces, are presented. All stable adsorption sites are identified and the most energetically favourable adsorption sites are compared across the three surfaces. In general, sites which appear centered over hollow-like surface sites are preferred. The effect of van der Waals (vdW) corrected DFT on binding site energetics and geometries has also been studied by way of the Tkatchenko-Scheffler (TS) correction. It shows a strong influence on the adsorption energies, some effect on the relative energetic ordering of sites and little to no effect on adsorption geometries. Second, the adsorption of naphthalene and quinolinium is studied on the most stable surface of bcc iron, Fe{110}, using DFT. Quinolinium and naphthalene differ only by one atom but their electronic structure differences result in significant changes in preferred adsorption site energetics and geometries. Quinolinium tends to adsorb preferentially in geometries which allow its nitrogen atom to bind in an atop position on the Fe{110} surface, in agreement with prior DFT work on $NH_{x}$ adsorbed on Fe{211} showing tetravalent arrangements of adsorbed nitrogen are preferred. The preferred naphthalene adsorption configuration presents the highest overall symmetry of all investigated naphthalene sites. The adsorption energy for the top quinolinium geometry is 1.12~eV stronger than that found for the best naphthalene adsorption geometry. Finally, the adsorption behaviour of NMQ+ on the Fe{110} surface is studied using DFT. Prior to the DFT adsorption study, a semi-empirical level conformational search on the NMQ+ ion is conducted to identify preferred gas phase conformations of the ion. Energetically favoured structures are optimised using DFT, which further refines the search and identifies two different favourable gas phase NMQ+ conformations. Six different starting NMQ+ geometries on the Fe{110} surface are tested based on the two favourable gas phase conformations, and reveal a strongly favoured site (1.4 eV stronger adsorption than the next best site) which presents double dehydrogenation of the quinolinium moiety. The next best site also presents double dehydrogenation, but on the methyl linker and quinolinium moiety. Beyond providing insight into the mode of action of molecules intended for corrosion inhibition of steels, this work provides a fundamental understanding of the behaviour of adsorbed aromatic molecules on iron surfaces, which can play a role in a number of industrially relevant applications, including organic solar cells, transistors and LEDs, heterogeneous catalysts and medical implants.

Metalloproteins play a crucial role in many key biological processes, from oxygen transport to photosynthesis. In the case of photosynthesis, the oxygen evolving complex (OEC) - a CaMn₄O₅ cluster - catalyses water-to-oxygen-gas conversion. From a computational standpoint, accurately modelling the electronic structure of the OEC and other metalloproteins ab initio is difficult, due to two challenges. Firstly, there is that of the strong electronic correlation present due to the partially-filled 3d-subshells of the transition metal atoms, a classic example of where semi-local density functional theory (DFT) - a go-to method for computational physicists - fails. The second challenge is that of size: as this thesis will demonstrate, we must consider large cluster models that are thousands of atoms in size, which takes us beyond the reach of both plane-wave DFT and quantum chemistry methods. This thesis explores the capacity of density functional theory-plus-U (DFT+U) and dynamical mean field theory (DMFT) to meet both of these challenges. It will demonstrate how both DFT+U and DMFT can be readily married with linear-scaling DFT, meaning that these theories can be applied to protein systems containing thousands of atoms. In particular, this thesis presents the unification of ONETEP (a linear-scaling DFT code) and TOSCAM (a DMFT solver). It also presents a novel approach for determining Hubbard and Hund's parameters via linear response that is compatible with linear-scaling DFT and resolves inconsistencies between the linear response method and the DFT+U corrective functional. These techniques are then applied to haem, haemocyanin, and the OEC, providing insight into the role of strong correlation in their electronic structure and function. In so doing, this thesis demonstrates how one can perform large-scale simulations of metalloproteins that account for strong electronic correlation. The results of this thesis are of significant interest due to both the importance of metalloproteins in nature, and the wealth of potential applications that would spring from a thorough understanding of their catalytic and binding properties.

This work presents a method for the computation of electron energy loss spectra for large systems using the onetep code. The foundations of density functional theory will be discussed, with a focus on the linear scaling methods employed by onetep. A method for the prediction of spectra will be shown, with emphasis on the construction of the matrix elements needed. This method is tested against both other DFT codes and experiment. Once the ability of onetep to predict EEL spectra has been established the code is used to predict the spectra associated with oxygen vacancy defects in the anatase (101) surface. These spectra are found to agree with the limited experimental data available. EEL spectra for nitrogen dopants in anatase are also predicted, based on literature geometries for these. The energetics of the oxygen vacancy is also explored, using the ability of onetep to perform calculations on large cells to address elastic finite size effects and employing a correction scheme to remove electrostatic finite size effects. Finally, the properties of an extended grain boundaries defect in GaAs were investigated, focussing on properties relevant for optoelectronics.

The application of chiroptical methods such as vibrational circular dichroism (VCD) spectroscopy is valuable in the assignment of absolute chirality. Assignment of chirality traditionally involves visual comparison of calculated and experimental spectra which can be subjective and time consuming. Experimental VCD spectra for 40 compounds were acquired on different VCD spectrometers over the course of this work. To these data were added several compounds from published literature for which VCD data was already available. By successive trials over a dataset containing 60 compounds and their VCD spectra, various automated methods for interpretation of VCD spectra are developed and investigated, with the aim of achieving a confidence level assignment algorithm for absolute chirality. The algorithm functions by comparing baseline-corrected VCD spectra of a compound with theoretically predicted spectra for each enantiomeric form. The prediction method for VCD spectra involves conformational searching at the molecular mechanics level to find stable conformational minima, followed by quantum calculations using density functional theory (DFT) to find the vibrational modes. DFT calculations are performed using the B3LYP and B3PW91 functionals, in conjunction with the 6-31G(d,p) and cc-pVTZ basis sets. Comparison between calculated and observed data is performed using a novel multiplicative percentage scoring method, scanning through a range of scale factors between 0.95 and 1.00. The degree of similarity is given a score ranging from -100% to +100%, with percentage values given such that uncertain cases need not be ignored or overconfidently assigned, but can be realistically evaluated according to existing spectral data. This analysis is optimised using a database of 30 pairs of small-molecule organic compounds, including many drug-like and drug precursor molecules. Through these and further computational methods we present a reliable and time-efficient method for determination of absolute chirality, with the aim of developing into a standardized procedure for small-molecule organic compounds.

Molecular simulation is applied to understanding the behaviour of alkane liquids with the eventual goal of being able to predict the viscosity of an arbitrary alkane mixture from first principles. Such prediction would have numerous scientific and industrial applications, as alkanes are the largest component of fuels, lubricants, and waxes; furthermore, they form the backbones of a myriad of organic compounds. This dissertation details the creation of a potential, a model for how the atoms and molecules in the simulation interact, based on a systematic approximation of the quantum mechanical potential energy surface using machine learning. This approximation has the advantage of producing forces and energies of nearly quantum mechanical accuracy at a tiny fraction of the usual cost. It enables accurate simulation of the large systems and long timescales required for accurate prediction of properties such as the density and viscosity. The approach is developed and tested on methane, the simplest alkane, and investigations are made into potentials for longer, more complex alkanes. The results show that the approach is promising and should be pursued further to create an accurate machine learning potential for the alkanes. It could even be extended to more complex molecular liquids in the future.

This thesis presents a combined experimental and theoretical approach on studying Mg-ion battery electrode materials, where Nuclear Magnetic Resonance (NMR) spectroscopy plays a central role in identifying the local structure and dynamics of the magnesium ions. Density Functional Theory (DFT) techniques are used extensively to (i) calculate and rationalise the observed NMR shifts, (ii) provide insights into the dynamics involved in such electrode materials, and (iii) guide the synthesis of candidate electrode materials. This work begins by a systematic study of 25Mg solid-state NMR in paramagnetic oxides, where the presence of transition metals makes them suitable for applications in high-voltage cathode materials. DFT methods for predicting and rationalising the paramagnetic NMR shifts are developed, with experimental verifications on synthesised samples. Feasibility of using advanced NMR pulse sequences such as Rotor-Assisted Population Transfer and Magic Angle Turning is demonstrated on such systems to afford enhanced resolution and sensitivity. This approach of combined NMR and DFT techniques is then applied to two of magnesium vanadates for high-voltage cathode applications. In particular, DFT-based thermodynamic energies are used to rationally design the synthetic steps leading to the said vanadate materials, followed by DFT prediction of the migration barriers. The prepared material was subject to experimental characterisation using NMR and diffraction techniques, with an initial cycling data in an electrochemical cell. In the final part, a combined experimental and ab initio investigation on Mg3Bi2, a promising Mg-ion battery anode material, is presented. Previous reports on variable-temperature 25Mg NMR spectroscopy is validated by DFT calculations on the migration barrier and defect energetics. Mechanistic insights on the migration mechanism are presented using the hybrid eigenvector-following transition state searching method, where the relativistic effects of heavy bismuth is shown to influence the migration barrier. We show that the defect formation energy of a Mg vacancy is critical in the apparent Mg diffusion barrier, which is heavily influenced by sample preparation conditions.

The emerging 2D materials are potential solutions to the scaling of electronic devices to smaller sizes with lower energy cost and faster computing speed. Unlike traditional semiconductors e.g. Si, Ge, 2D materials do not have surface dangling bonds and the short-channel effect. A wide variety of band structure is available for different functions. The aim of the thesis is to calculate the electronic structures of several important 2D materials and study their application in particular devices, using density functional theory (DFT) which provides robust results. The Schottky barrier height (SBH) is calculated for hexagonal nitrides. The SBH has a linear relationship with metal work function but the slope does not always equal because Fermi level pinning (FLP) arises. The chemical trend of FLP is investigated. Then we show that the pinning factor of Si can be tuned by inserting an oxide interlayer, which is important in the application to dopant-free Si solar cells. Apart from contact resistance, we want to improve the conductivity of the electrode. This can be done by using a physisorbed contact layer like FeCl3, AuCl3, and SbF5 etc. to dope the graphene without making the graphene pucker so these dopants do not degrade the graphene's carrier mobility. Then we consider the defect formation of 2D HfS2 and SnS2 which are candidates in the n-type part of a tunnel FET. We found that these two materials have high mobility but there are also intrinsic defects including the S vacancy, S interstitial, and Hf/Sn interstitial. Finally, we study how to make defect states chemically inactive, namely passivation. The S vacancy is the most important defect in mechanically exfoliated 2D MoS2. We found that in the most successful superacid bis(trifluoromethane) sulfonamide (TFSI) treatment, H is the passivation agent. A symmetric adsorption geometry of 3H in the -1 charge state can remove all gap states and return the Fermi level to the midgap.

In Condensed Matter Physics, the computational expense to evaluate the total potential energy of a collection of atoms using standard ab initio methods is typically large. This limits the scale of phenomena that can be studied in both length and time. Data-driven techniques have established a pragmatic extension to ab initio calculations, balancing reductions in the calculation time with potential losses of accuracy in the properties of interest. Both paradigms compliment one another and when used appropriately, are valuable tools that enable and stimulate research in Materials Science. Unlike traditional efforts, modern techniques to include data employ flexible functional forms, extending the applicability of such methods to a diverse range of physical quantities. Recently, interest in utilising data in total energy calculations has turned towards the electron density. With an electron density that is close to the ground state, data-derived kinetic energy functionals in orbital-free density functional theory can be applied to evaluate the total energy without using gradients of the functional with respect to the electron density. For this purpose, a number of approaches to calculate data-derived densities have been proposed in recent years. In this thesis, we begin by reviewing several fixed-form expressions to approximate the potential energy of hexagonal layered crystals and show how a flexible form is essential to fully utilise the available data. We then focus on developing new approaches to approximate ground state electron densities and on novel applications that help to further unify data-driven and ab initio techniques within electronic structure. By calculating reliable uncertainty estimates, we show that data-derived densities can be incorporated into density functional theory in a "safe" manner. We also show that with accurate initial densities and for systems that otherwise have a poor initial estimate, we can reduce the number of self-consistent field iterations that are necessary to reach self-consistency in Kohn-Sham density functional theory. We hope that the work in this thesis will contribute to improving initial states in density functional theory, support the application of data-derived orbital-free kinetic energy functionals and encourage an ever closer and mutually beneficial cohesion between data-driven and ab initio techniques throughout the Natural Sciences.

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.

This thesis is concerned with study of vibrational dynamics and their effect on charge transport in thin films of organic semiconductors. Two classes of organic semiconductors are investigated- crystalline small molecules and conjugated polymers. Although device performance of both classes of materials has greatly improved over last two decades, detailed understanding of relationship between structure and transport properties is still missing- so far development of organic semiconductors has mostly been based on experimental approach, with theoretical models providing post factum justification rather than guiding rational design of novel compounds. In this thesis I establish methodology to investigate both inter- and intramolecular vibrational modes by combining latest computational techniques with experimental pressure-dependent Raman spectroscopy. The dominant factor limiting charge delocalization in crystalline small molecules are low frequency, large amplitude intermolecular modes. However, theoretical modeling of these modes require use of periodic boundary conditions increasing computational cost by orders of magnitude when compared to commonly used vacuum phase simulations. I report comparative study of two implementations (CRYSTAL09 and CASTEP) of density functional theory (DFT) and dispersion correction (Grimme and Tkatchenko-Scheffler) and evaluate their applicability to predict low frequency vibrational modes in 2,7-Dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT) and 2,8-Difl uoro-5,11-bis(triethylsilylethynyl)anthradithiophene (dif-TES-ADT). Charge transport in conjugated polymers is strongly affected by energetic disorder arising from spatial variations in backbone conformation. I combine vacuum phase DFT simulations of intramolecular vibrational modes with pressure-dependent Raman spectroscopy to study planarity and torsional backbone disorder of 2,5-bis(3-alkylthiophene-2-yl)thieno[3,2-b]thiophene (pBTTT), indacenodithiophene-co-benzo-thiadiazole (IDT-BT), diketopyrrolopyrrole-benzotriazole (DPP-BTZ) and naphtalene-bithiophene (NDI-T2) at pressures up to 3.9 GPa. It is shown that Raman spectra of pBTTT and NDI-T2 demonstrate dependence of mode intensities on hydrostatic pressure, whereas spectra of IDT-BT and DPP-BTZ exhibit lack of dependence. Simulations of theoretical spectra performed as a function of backbone torsion indicate that pBTTT undergoes deplanarization of already non-planar backbone and that NDI-T2 backbone is planarized, whereas backbones of IDT-BT and DPP-BTZ are resilient to changes of conformation. Finally, I perform large scale molecular dynamics simulations of crystalline, semi-crystalline and disordered phases of IDT-BT and DPP-BT in order to investigate effect of disorder on backbone conformation. Both compounds were previously reported to exhibit extremely low degree of energetic disorder- I assign this phenomenon to their surprisingly strong resilience to side chain disorder. In both systems simulations demonstrate novel mechanism of disorder accommodation- their backbones bend rather than twist and retain low degree of torsional variation even in amorphous phase.

The replacement of fossil fuel powered base-load electricity generation with fluctuating renewable energy resources is dictating that complementary nuclear power, more than ever before, must extend its traditional role of base-load generation by developing flexible power manoeuvring capabilities. In light water nuclear reactors, fuel pellets are encased in zirconium alloy cladding tubes. The pellet-cladding interaction (PCI) can result in fuel rod failure due to a stress corrosion cracking (SCC) process. Reactor operations are currently stringently bounded by an empirically-based knowledge of PCI. In order to safely relax these overly-conservative operating restrictions, a mechanistic understanding of PCI must be developed. In particular, fission products released from the fuel pellets, such as iodine, can interact aggressively with the inner cladding surface, which is additionally subject to points of high stress concentration due to mechanical contact with the pellets. Such conditions are conducive to SCC, and it has been shown that zirconium grain boundaries (GBs) are important in this process. In this work, we thus focus on simulating from first-principles, grain boundaries in zirconium. We additionally probe the effects of iodine and caesium on GB properties. We build significantly on existing work by including in our analysis the properties of multiple grain boundaries---four symmetric tilt GBs and three twist GBs. In particular we survey the interfacial energetics and explore the microscopic degrees of freedom of each GB. We characterise the GBs according to their effect on the geometric properties of the surrounding atoms. In our defect analysis, we consider the segregation favourability of iodine, caesium and vacancy defects at three distinct sites of four GBs in zirconium. We find both iodine and caesium segregation to the GBs to be energetically favourable, with the preference of caesium being the strongest. We additionally consider the effect of increasing the defect concentration. The data we have generated during this work could be used for the fitting and validation of a zirconium-iodine empirical potential, which would allow accurate simulations at much larger length scales than are currently possible.

This thesis presents work done on the calculation of the effects of anharmonic nuclear motion on the properties of solid materials from first principles. Such anharmonic effects can be significant in many cases. A vibrational self-consistent field (VSCF) method is used as the basis for these calculations, which is then improved and applied to a variety of solid state systems. Firstly, work done to improve the efficiency of the VSCF method is presented. The standard VSCF method involves using density functional theory (DFT) to map the Born-Oppenheimer (BO) energy surface that the nuclei move in, a computationally expensive process. It is shown that the accurate forces available in plane-wave basis DFT can be used to help map the BO surface more accurately and reduce the computational cost. This improved VSCF+f method is tested on molecular and solid hydrogen, as well as lithium and zirconium, and is found to give a speed-up of up to 40%. The VSCF method is then applied to two different systems of physical interest. It is first applied to the case of the neutral vacancy in diamond, in order to resolve a known discrepancy between harmonic ab initio calculations and experiment -- the former predict a static Jahn-Teller distortion, whilst the latter leads to a dynamic Jahn-Teller effect. By including anharmonic corrections to the energy and nuclear wavefunction, we show that the inclusion of these effects results in agreement between first-principles calculations and experiment for the first time. Lastly, the VSCF method is applied to barium titanate, a prototypical ferroelectric material which undergoes a series of phase transitions from around 400 K downwards. The nature of these phase transitions is still unclear, and understanding them is an active area of research. We describe the physics of the phase transitions of barium titanate, including both anharmonicity and the effect of polarisation caused by long wavelength vibrations, to help understand the important physics from first principles.

Lithium-ion batteries have transformed energy storage and technological applications. They stand poised to convert transportation from combustion to electric engines. The discharge/charge rate is a key parameter that determines battery power output and recharge time; typically, operation is on the timescale of hours but reducing this would improve existing applications and open up new possibilities. Conventionally, the rate at which a battery can operate has been improved by synthetic strategies to decrease the solid-state diffusion length of lithium ions by decreasing particle sizes down to the nanoscale. In this work, a different approach is taken toward next-generation high-power and fast charging lithium-ion battery electrode materials. The phenomenon of high-rate charge storage without nanostructuring is discovered in niobium oxide and the mechanism is explained in the context of the structure–property relationships of Nb2O5. Three polymorphs, T-Nb2O5, B-Nb2O5, and H-Nb2O5, take bronze-like, rutile-like, and crystallographic shear structures, respectively. The bronze and crystallographic shear compounds, with unique electrochemical properties, can be described as ordered, anion-deficient nonstoichiometric defect structures derived from ReO3. The lessons learned in niobia serve as a platform to identify other compounds with related structural motifs that apparently facilitate high-rate lithium insertion and extraction. This leads to the synthesis, characterisation, and electrochemical evaluation of the even more complicated composition–structure–property relationships in ternary TiO2–Nb2O5 and Nb2O5–WO3 phases. Advanced structural characterisation including multinuclear solid-state nuclear magnetic resonance spectroscopy, density functional theory, X-ray absorption spectroscopy, operando high-rate X-ray diffraction, and neutron diffraction is conducted throughout to understand the evolution of local and long-range atomic structure and changes in electronic states.

Research on two-dimensional (2D) materials currently occupies a sizeable fraction of the materials science community, which has led to the development of a comprehensive body of knowledge on such layered structures. However, the goal of this thesis is to deepen the understanding of the comparatively unknown heterostructures composed of different stacked layers. First, we utilise linear-scaling density functional theory (LS-DFT) to simulate intricate interfaces between the most promising layered materials, such as transition metal dichalcogenides (TMDC) or black phosphorus (BP) and hexagonal boron nitride (hBN). We show that hBN can protect BP from external influences, while also preventing the band-gap reduction in BP stacks, and enabling the use of BP heterostructures as tunnelling field effect transistors. Moreover, our simulations of the electronic structure of TMDC interfaces have reproduced photoemission spectroscopy observations, and have also provided an explanation for the coexistence of commensurate and incommensurate phases within the same crystal. Secondly, we have developed new functionality to be used in the future study of 2D heterostructures, in the form of a linear-response phonon formalism for LS-DFT. As part of its implementation, we have solved multiple implementation and theoretical issues through the use of novel algorithms.

This thesis studies the physics of multilayer heterostructures grown from topological insulators (TIs), primarily bismuth selenide and antimony telluride, and other topologically trivial materials. This is done by extending a standard low-energy 3D TI Hamiltonian and varying its associated material parameters across the simulation domain. New results arising from the position-dependent TI interface model are found. For the first time, this method is incorporated into a density-functional theory (DFT) solver in order to study the self-consistent charge density in multilayer TI heterostructures due to the interface states. The thesis is structured as follows. The introduction (Ch. 1) presents a pedagogical review of the theory of 3D TIs and low-energy Hamiltonians used to study them, as well as typical methods in solid state physics that are made use of throughout the thesis. Chapter 2 presents the position-dependent Hamiltonian, showing new evidence for topological features of bulk states including varying degrees of band mixing and inversion; also, interface state tunnelling is shown to be affected by atomic layer orbital overlap, and incomplete localisation of surface states is demonstrated for antimony telluride. Chapter 3 presents a new DFT model of TI heterostructure interfaces and shows how conduction through TI interface states can be controlled with an electric field. Chapter 4 covers the extension of the model in Ch. 1 to 2D cross-sections of TI wires and heterostructures, showing for the first time evidence of localisation of conduction almost entirely within the inner interfaces of a 2D heterostructure wire. Chapter 5 presents our work with magnetic fields, demonstrating evolution of interface and bulk states with changing magnetic field and Landau level, as well as presenting new evidence for more complex spin structures in bismuth selenide arising from Landé factor signs. Our conclusions are presented in Chapter 6.

In this thesis we use density functional theory (DFT) to study the solvent mediated interactions between solvophobic, solvophilic and patchy nanostructures namely rectangular cross section blocks. We calculate both the density profiles and local compressibility around the blocks and the results obtained for our model system provide a means to understanding the basic physics of solvent mediated interactions between nanostructures, and between objects such as proteins in water, that possess hydrophobic and hydrophilic patches. Our results give an improved understanding of the behaviour of liquids around solvophobic objects and solvophobicity (hydrophobicity) in general. Secondly, we look into the physics incorporated in standard mean-field DFT. This is normally derived by making what appears to be a rather drastic approximation for the two body density distribution function: ρ(2)(r,r′) ≈ ρ(r)ρ(r′), where ρ(r) is the one-body density distribution function. We provide a rationale for why the DFT often does better than this approximation would make you expect. Finally, we develop a lattice model to understand the nature of the pattern formation exhibited by certain systems of particles deposited on liquid-air interfaces and in particular the nature of the transitions between the different patterned structures that are observed. This is done using Monte Carlo computer simulations and DFT and links the observed microphase ordering with the micellisation process seen e.g. in surfactant systems.

The physical and chemical properties of materials are intimately related to their underlying crystal structure: the detailed arrangement of atoms and chemical bonds within. This thesis uses computational methods to predict crystal structure, with a particular focus on structures and stable phases that emerge at high pressure. We explore three distinct systems. We first apply the ab initio random structure searching (AIRSS) technique and density functional theory (DFT) calculations to investigate the high-pressure behaviour of beryllium, magnesium and calcium difluorides. We find that beryllium fluoride is extensively polymorphic at low pressures, and predict two new phases for this compound - the silica moganite and CaCl$_2$ structures - to be stable over the wide pressure range 12-57 GPa. For magnesium fluoride, our results show that the orthorhombic `O-I' TiO$_2$ structure ($Pbca$, $Z=8$) is stable for this compound between 40 and 44 GPa. Our searches find no new phases at the static-lattice level for calcium difluoride between 0 and 70 GPa; however, a phase with $P\overline{6}2m$ symmetry is energetically close to stability over this pressure range, and our calculations predict that this phase is stabilised at high temperature. The $P\overline{6}2m$ structure exhibits an unstable phonon mode at large volumes which may signal a transition to a superionic state at high temperatures. The Group-II difluorides are isoelectronic to a number of other AB$_2$-type compounds such as SiO$_2$ and TiO$_2$, and we discuss our results in light of these similarities. Compressed hydrogen sulfide (H$_2$S) has recently attracted experimental and theoretical interest due to the observation of high-temperature superconductivity in this compound ($T_c$ = 203 K) at high pressure (155 GPa). We use the AIRSS technique and DFT calculations to determine the stable phases and chemical stoichiometries formed in the hydrogen-sulfur system as a function of pressure. We find that this system supports numerous stable compounds: H$_3$S, H$_7$S$_3$, H$_2$S, H$_3$S$_2$, H$_4$S$_3$, H$_2$S$_3$ and HS$_2$, at various pressures. Working as part of a collaboration, our predicted H$_3$S and H$_4$S$_3$ structures are shown to be consistent with XRD data for this system, with H$_4$S$_3$ identified as a major decomposition product of H$_2$S in the lead-up to the superconducting state. Calcium and oxygen are two elements of generally high terrestrial and cosmic abundance, and we explore structures of calcium peroxide (CaO$_2$) in the pressure range 0-200 GPa. Stable structures for CaO$_2$ with $C2/c$, $I4/mcm$ and $P2_1/c$ symmetries emerge at pressures below 40 GPa, which we find are thermodynamically stable against decomposition into CaO and O$_2$. The stability of CaO$_2$ with respect to decomposition increases with pressure, with peak stability occurring at the CaO B1-B2 phase transition at 65 GPa. Phonon calculations using the quasiharmonic approximation show that CaO$_2$ is a stable oxide of calcium at mantle temperatures and pressures, highlighting a possible role for CaO$_2$ in planetary geochemistry, as a mineral redox buffer. We sketch the phase diagram for CaO$_2$, and find at least five new stable phases in the pressure/temperature ranges 0 $\leq P\leq$ 60 GPa, 0 $\leq T\leq$ 600 K, including two new candidates for the zero-pressure ground state structure.

The photosynthetic water splitting reaction performed in green plants, algae and cyanobacteria is perhaps one of the most important reactions on the planet. The reaction is catalysed by a tetranuclear manganese cluster that is driven by sunlight and as such has received a high degree of interest in the context of solar fuels research. Due to the intricacy of the bioinorganic systems, the molecular mechanisms of the reactions are unknown and structural elucidation of the active sites is complicated. Computational techniques can provide considerable support in the analysis and interpretation of the complex EPR spectra of such biological systems. In this work, the molecular and electronic structures of several multinuclear manganese containing bioinorganic systems are investigated using BS-DFT. A particular focus of this work is the provision of high quality calculated EPR parameters yielding structural and mechanistic insight. In the first results chapter, the MnIIIMnIV superoxidised state of manganese catalase as well as azide inhibited manganese catalase is studied. Several variants are proposed and analysed on the basis of their calculated EPR parameters. The results presented in this chapter offer a new interpretation of previous experimental assignments. Chapter 6 features investigations on the S2 state of the Oxygen Evolving Complex of Photosystem II. In this chapter both the native OEC as well as the strontium substituted OEC are studied, in order to investigate how replacement of the calcium ion affects the structure of the OEC. The final results chapter presents calculations on the split signal S2Yz dot radical formed on the transition from the S2 to S3 state, as well as studying the S3 state. The calculation of various EPR hyperfine couplings and their comparison with available experimental data has provided key insights into the electronic structure of the OEC.

This thesis entails the utilisation of ab initio density functional theory (DFT) in conjunction with neutron and synchrotron spectroscopy to study the mechanical, vibrational, and dielectric response of metal-organic framework (MOF) materials at the molecular level. MOFs are crystalline materials with nanoscale porosity, which have garnered immense scientific and technological interest for a wide variety of innovative engineering applications. One part of the thesis involves using low-frequency lattice vibrations to characterise the various physical motions that are possible for framework materials. These collective modes detected at terahertz (THz) frequencies have been used to reveal a broad range of exciting possibilities. New evidence has been established to demonstrate that THz modes are intrinsically linked to anomalous elasticity underpinning gate-opening and pore-breathing mechanisms, and to shear-induced phase transitions and the onset of structural instability. The phenomenon of molecular rotor mechanisms and trampoline-like motions are also observed, along with the first experimental confirmation of coordinated shear dynamics. Additionally, a new method to characterise the effects of temperature, and hence thermally-induced structural amorphisation is reported. Finally, for the first time, the frequency-dependent (dynamic) dielectric response of MOF materials, across the extended infrared (IR) spectral region was reported. The results were obtained from experimental synchrotron radiation IR reflectivity and DFT to reveal the low-&kcy; dielectric response of MOFs and established structure-property trends that highlight them as promising systems for microelectronic device applications.