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Lubricants are used widely in industry to reduce the effects of friction and wear. Lubricant formulations for engine applications are typically composed of a base oil and various additives, each having a different function. This complexity means that their properties are not well understood, and it is difficult to study lubricants while they are in operation in an engine. The rheology of the base oils, which make up the majority of the lubricant formulation, is particularly important as the lubricants are exposed to a wide range of pressures and shear rates. Recent high-pressure experiments at Edinburgh indicate that model base oils - squalane and a poly-α-olefin (PAO) mixture - are no longer hydrostatic media above roughly 1 GPa. Diamond-anvil cell measurements show that the hydrostatic limit for these base oils is in the range of 0.74 to 1.24 GPa, as they appear to undergo solidification. X-ray diffraction shows no Bragg peaks, suggesting that a glassy structure, and not a crystalline structure, is formed. In this work, the structure, dynamics, and thermodynamics of model base oils were studied using molecular-dynamics (MD) simulations. The equation of state, self-diffusion coefficient, viscos ity, and radial distribution functions were calculated over a wide range of pressures, from 0.0001 to 10 GPa. The results show that molecular diffusion is essentially arrested above about 0.1 GPa, which supports the hypothesis that the samples are kinetically trapped in metastable amorphous-solid states. The shear viscosity is immeasurably large at very high pressures, but the coefficient governing its increase from ambient pressure is in good agreement with the available literature data. Subtle changes in the short-range real-space correlations are related to a collapse of the molecular conformations with increasing pressure, while the evolution of the static structure factor shows excellent correlation with the available X-ray diffraction data. Next, oleamide, an industrially relevant organic friction modifier (OFM), was introduced to the base oil systems, where they formed clusters both with and without the presence of water. Taking a step towards engine conditions, these base oil and OFM systems were placed under confinement between iron oxide surfaces. It was observed that the oleamide would adsorb onto the surfaces and form a layer. If water was present, it would out-compete the oleamide for surface coverage, even being able to remove pre-existing oleamide from the iron oxide. The oleamide would then form a layer on top of the water. The free energy of adsorption for oleamide onto iron oxide surfaces was computed using umbrella sampling, and agreed well with experimental measurements. Computing association constants for oleamide showed that, at the experimental conditions and concentrations, it would adsorb onto the surfaces as monomers rather than in a cluster. The association constants were also in excellent agreement with experimental measurements. The final part of this work involved adding shear to the confined base oil/OFM systems to simulate the movement of the engine during operation. Initial frictional measurements using pure base oil systems correlated well with literature data from both experiments and simulations, and the effects of the OFM and water contamination on friction were then explored. Oleamide was found to reduce friction in most cases, being particularly effective for thin lubricating films under relatively low-shear conditions (< 107 s −1 ). Additionally, water was shown to have a larger effect on reducing friction than oleamide under a wide range of conditions. These effects showed good qualitative agreement with experimental measurements. High-pressure simulations showed some evidence that the base oils will undergo the same pressure-induced solidification that was observed in the initial bulk simulations. This work has made steps towards building up a comprehensive picture of how typical base oils and organic friction modifiers interact under engine conditions, starting from simple bulk systems and gradually adding in complexity to get closer to engine conditions. The simulations have been extensively compared and validated with experimental measurements, showing consistently strong agreement. The simulation methods described here are applicable to other lubricant components to continue elucidating how these complex formulations work.

The field of Computer Aided Drug Design (CADD) has experienced substantial developments over the last few decades thanks to a rapid growth incomputing power. In particular, Molecular Dynamics (MD) simulations and associated techniques have earned increased attention within the pharmaceutical sector thanks to their rising accuracy and diminishing cost. However, there are still limitations in the usage of these methods, due to thedifficulty of sampling the rugged energy landscapes of protein-ligand complexes. The main theme of this work is to address the sampling problem of MD methods for predicting the binding free energies of different biomolecular complexes. This work starts using MD simulations as a sampling technique for a relative free energy calculation protocol using the Sire Open Molecular Dynamics (SOMD) software. This protocol was then integrated in a ligand design workflow to optimize the binding selectivity of cyclophilin (Cyps) inhibitors. Cyps are proteins known to play a vital role in various diseases, such as cancer, Alzheimer and viral infections. Most Cyp inhibitors to date,however, are cyclic peptides that have potency in the nanomolar range but produce severe side effects, are complex to synthesize and display complex pharmacokinetic profiles. Thus, there is a need for new selective smallmolecules targeting specific Cyps isoforms, in order to gain new insightsfor the inhibition of these therapeutically vital proteins. The computational workflow was able to suggest auspicious designs that they will be synthesized and characterized using biophysical techniques from Alison Hulme's lab. Following, MD simulation methods were employed for the more challenging task of predicting the absolute free energies of binding of protein-ligand complexes. For this purpose, an Alchemical Free Energy (AFE) protocol was generated and its efficiency was evaluated in the Statistical Assessment of Modelling of Proteins and Ligands (SAMPL6) challenge. SAMPL challenges involve a series of blinded predictions of standard binding freeenergies for toy host-guest molecules. The results obtained from our protocol were ranked among the top submissions in terms of accuracy and correlation with experimental data. Encouraged by these results, we wanted to compare the efficiency of the AFE protocol versus a Markov State Modelling (MSM) protocol for the calculation of the standard binding free energy of a ligand to the intrinsically disordered protein c-Myc. The oncoprotein c-Myc is overexpressed in over 70% of human cancers and its inhibition has been considered the holygrail in cancer therapy. Due to its structural elasticity it is difficult to perform structure-based drug design methods for the discovery of novel compounds. The results showed that MSM can describe accurately the binding process of the ligand to the oncoprotein c-Myc, but the binding free energies were similar with the ones of the AFE protocol. Finally, an adaptive sampling protocol was established for the computation of the standard binding free energy and binding selectivity of lead-like ligands for the flexible protein MDM2. MDM2 is a vital protein that acts as an inhibitory mechanism of the transcription factor p53. p53 plays animportant role in the regulation of cellular processes and suppression of tumor development. For this reason, it is important to develop methods for the discovery of novel ligands that could inhibit the MDM2-p53 interaction through binding to the MDM2 protein. The results of the adaptive sampling study were encouraging as the protocol was able to predict binding selectivity trends for the MDM2-ligand complexes approximately six times faster than the original AFE protocol.

Dental erosion is a pandemic affecting 3.6 billion people in the world. Over 95 % of enamel is composed of calcium hydroxyapatite (HAP). Enamel is acellular, and as a result of our lifestyle and daily wear and tear this HAP is irreparably damaged. Currently the main treatment for this damage is a metal or porcelain filling which loses adhesion over time creating larger dental carries. To develop a method that can regenerate natural enamel would provide an evasive alternative to the current dental methods and help stop the dental erosion pandemic. In nature, the growth and nucleation of HAP during enamel formation is regulated by a protein called amelogenin. The protein has hydrophilic-hydrophobic polarity which allows the protein to assemble and has a phosphinic acid group on serine-16 that is crucial in growth and regulation of HAP. Taking inspiration from this protein, self-assembling block copolymers could be used as a synthetic alternative. The benefit of using synthetic polymers in enamel restoration and erosion prevention is that the promotion of CaP can be tuned by changing the functional groups and size of the polymer easily by using controlled radical polymerisation (CRP). They also provide an inexpensive alternative to using protein induced mineralisation methods. Block copolymers can be formed by CRP. They have been useful in many applications such as drug delivery due their ability to form self-assembled structures such as micelle and cylinders. In previous research on dental erosion the focus has been on the ability of polymers to prevent enamel erosion however their ability to promote HAP growth has not been yet investigated. Here phosphonic and carboxylic acids containing block copolymers have been synthesised through ring opening polymerisation (ROP) and reversible addition fragmentation chain-transfer (RAFT) polymerisation in order to form self-assembled structures that promote HAP growth and prevent erosion. PEG-poly(heptenolactone) and PEG-polycaprolatone-poly(heptenolactone) containing carboxylic acids and phosphonate moieties were synthesised using PEG and PEGpolycaprolatone as initiators. In the RAFT polymerisation , phosphonate monomer di(methacryloyloxy)methyl phosphonate (MAPC1), tert-butyl methacrylate (TBuMA), hydroxyethylmethacrylate (HEMA) and 2(dimethylamino)ethyl methacrylate (DMAE) were polymerised with methyl methacrylate (MMA). The resulting polymers were coupled with PEG through esterification and then further polymerised with a second monomer to give a triblock copolymer. Many of the triblock copolymers had critical micelle concentrations and dispersities which were determined through fluorescence spectroscopy and gel permeation chromatography respectively. The morphology of nine polymers were explored further though transmission electron microscopy (TEM). It was found that PMMA-b-PMAPC1acid-b-PEG, PMAPC1acid-b-PMMA-bPEG, PDMAE-b-PMMA-b-PEG all formed spheres between 25 to 50 nm. PHEMA-b-PMMA-b-PEG formed a mixture of short cylinders (worms) and spheres (20 nm and 35 nm respectively) and PMAPC1-b-PEG, PMAPC1acid-b-PEG and PMAA-b-PMMA-b-PEG did not self-assemble. The ability of block copolymers to promote CaP growth was analysed by dynamic light scattering (DLS) as a preliminary test. Of these polymers, PMMA-b-PMAPC1 acid-b-PEG, PMAPC1acid-bPMMA-b-PEG, PHEMA-b-PMMA-b-PEG and PMAPC1acid-b-PEG promoted the precipitation CaP. PMAPC1acid-b-PMMA-b-PEG, on the other hand, did not. PMMA-b-PMAPC1 acid-b-PEG was taken forward and the morphology of the CaP was view under scanning electron microscopy (SEM) and transmission electron microscopy (TEM). The SEM micrographs showed a ball-like matrix of CaP which was confirmed electron dispersive x-ray spectroscopy (EDS). The TEM micrographs also show the ball-like matrix and electron diffraction was also utilized and showed that these structures are amorphous. The PMAPC1acid-b-PMMA-b-PEG, PHEMA-b-PMMA-b-PEG and PMAPC1acid-b-PEG polymers were taken to investigate their ability to protect enamel against acid erosion. Profilometry was used to measure the loss of enamel and SEM was used to observe changes in the enamel surface. PHEMA-b-PMMA-b-PEG and PMAPC1acid-b-PEG provided an acid resistant covering over the enamel resulting in a reduction in enamel loss, however PMAPC1acid-b-PMMA-b-PEG showed minimal reduction. This work has displayed the potential for block copolymers to be a prospective candidate in enamel restoration. However how the polymer controls CaP precipitation needs to be explored further. In particular, how many phosphonic and hydroxyl groups are needed to promote CaP growth. It would also be essential to determine the stability of the amorphous CaP form with PMMA-b-PMAPC1acid-b-PEG to see if at longer periods, the CaP crystallizes.

Polymers can be decorated with functional groups (FGs) to confer specific and tuneable properties to the molecules. By varying the chemical architecture, concentration, and distribution of the FGs on the polymer, it is possible to control the chemical and physical properties of the polymers. Such functionalised polymers are applied broadly, in chemical synthesis, biological science, chemical engineering, medicine, agriculture, food science, optical science, and the energy sector. This thesis is devoted to the study of functionalised polyethylene/polypropylene (PE/PP) copolymers used to control friction and wear in combustion engines. The aim is to investigate how the distribution of FGs on linear PE/PP copolymers controls the structural, dynamical, and tribological properties of the molecules when dissolved in n-heptane (representing an oil), either in bulk, or confined and sheared between solid iron oxide surfaces (representing the moving parts of engines). Large-scale atomistic molecular dynamics simulations are used to gain detailed and unique insights on the links between molecular-scale and tribological properties. Simulations of isolated copolymers in solution are carried out to explore how the radius of gyration, end-toend distance, and scattering form factor are dictated by the distribution of a proprietary FG. It is shown that the size of a copolymer can vary by as much as 38% by varying the FG distribution, due to the association of the FGs in solution. It is found that solvophobic interactions are responsible for this association, and the results are supported by simulations of different FGs without the opportunity to stack. Predicted form factors will enable comparisons to be made with future X-ray and neutron scattering experiments. The shear viscosity is found to correlate well with the FG distribution and copolymer size at low concentration, while at high concentration the viscosity does not seem to depend with FG distribution, in agreement with the lack of variation in static structure. Next, the properties of copolymers solutions confined between iron oxide surfaces are explored, in static conditions and under shear. It is found that the FG distribution strongly affects the nature of the adsorption of the copolymers, and the response of the adsorbed film to shear, as measured by mass-density and velocity profiles across the liquid layer.

Engine oils are of great significance in the automotive industry as they provide lubrication of the moving mechanical components of the engine, thus decreasing friction, and preventing wear and corrosion. There is little understanding of the underlying molecular-scale mechanisms that contribute to the low-friction environment, and how the additives in lubricant oils behave under engine-like conditions. Previous research is based mainly on experimental work and empirical evidence, although in the past decade, computational techniques have been used successfully to simulate the engine environment and verify experimental results. This work is mainly focused on the computational investigation of certain surface active additives under a range of relevant physical conditions, such as high pressure and high shear rate, in order to provide an insight into the behaviour of these compounds at the atomistic level. The simulations are performed using molecular dynamics (MD) and they explore important microscopic processes such as adsorption and self assembly in bulk and under confined conditions. In the first part of the thesis, the focus is on lubricant additives in oil. Surfactant adsorption helps protect the surface from contact with other engine parts, whereas aggregation plays a major role in preventing impurities and byproducts from depositing onto the surfaces. The frictional and structural properties are studied over production runs. The additives studied are polyisobutylsuccinimide-polyamine (PIBSA-PAM), glycerol monooleate (GMO), synovene, and glyceryl monolinoleate (GML), and squalane is used as the lubricating oil. The additives tend to adsorb onto the surfaces, or form micelles, which break under high shear conditions. Interesting trends are identified, linking self assembly with friction and shear rate, and the co-operative interactions between the additives are highlighted. In the second part of the thesis, MD simulations are used to study self-assembly and surface adsorption of ionic surfactants in water. An investigation on the self assembly properties of the surfactant compounds hexadecyltrimethylammonium bromide (CTAB) and didodecyldimethylammonium bromide (DDAB) in water is performed, and the results are linked to experimental findings. The molecules are confined between muscovite mica surfaces, and are found to adsorb and form lamellar structures on mica. The morphology of the mica surface is deemed crucial for the structure of the adsorbed formations, and the simulation results are compared with recent experimental measurements by calculating the scattering-length density profiles and the reflectivity. This study provides a detailed analysis of a range of surface active molecules, either in bulk or confined conditions, and emphasises the importance of the co-operative interactions between two or more additives in bulk and confined solutions.

The main theme of this work is the design and development of new molecular simulation protocols, to achieve more accurate and reliable estimates of free energy changes for processes relevant to the structure-based drug design. The works starts with an insight into the reproducibility problem for alchemical free energy calculations. Even if simulations are run with similar input files, the use of different simulation engines could give different free energy results. As part of a collaborative effort, the implementation details of AMBER, GROMACS, SOMD and CHARMM simulation codes were studied and free energy protocols for each software were validated to converge towards a reproducibility limit of about 0.20 kcal.mol-1 for hydration free energies of small organic molecules. Following, new simulation methods for the estimation of lipophilicity coefficients (log P and log D) for drug like molecules were developed and validated. log P values were computed for a dataset of 5 molecules with increasing fluorination level. Predictions were in line with the experimental measures and the simulations also allowed new insights into the water-solute interactions that drive the partitioning process. Then, as part of the SAMPL5 challenge, log D values for 53 drug-like molecules were computed. In this context two different simulation models were derived in order to take into account the presence of protonated species. The results were encouraging but also highlighted limits in alchemical free energy modelling. As an additional task of the SAMPL5 contest, three different protocols were validated for predicting absolute binding affinities for 22 host-guest systems. The first model yielded a free energy of binding based on free energy changes in solvated and complex phase; the second added the long range dispersion correction to the previous model; the third one used a standard state correction term. All three protocols were among the top-ranked submission in SAMPL5, with a correlation coefficient R2 of about 0.7 against experimental data. Finally, the origins and magnitude of the finite size artefacts in alchemical free energy calculations were investigated. Finite size artefacts are especially predominant in calculations that involve changes in the net-charge of a solute. A new correction scheme was devised for the Barker Watts Reaction Field approach and compared with the literature. Hydration free energy calculations on simple ionic species were carried out to validate the consistency of the scheme and the approach was further extended to host-guest binding affinities predictions.

Energetic materials (explosives, propellants and pyrotechnics; EMs) encompass a broad range of materials. These materials are used across a wide spectrum of applications, including civil and defence. For example, HMX, RDX and TNT are well known EMs with defence applications. Silver fulminate is instead used in house-hold Christmas crackers and ammonium nitrate is used for numerous industrial applications. Common to all EMs is their propensity to rapidly release energy upon external perturbation. The amount and type of energy that is required to initiate an EM can vary across orders of magnitude. Some materials (e.g. triaminotriperoxide, TATP) initiate with < 1 J of impact energy, while others (e.g. triaminotrinitrobenzene, TATB) cannot be initiated without > 100 J of impact energy. Understanding which materials can be handled safely is therefore of critical importance for maintaining the safe use of EMs across all sectors. Current trends in EM research include a drive to develop new materials with decreased sensitivities. While it is relatively straightforward to selectively modify some properties (e.g. environmental impact), very little is understood about what constitutes a sensitive material. At present, a new EM must be synthesised and its sensitivity tested. However, with no a priori knowledge of the potential sensitivity of a novel EM, synthesis is accompanied by substantial hazard, as well as time and financial costs. It is therefore pressing to develop a fundamental understanding of what dictates a sensitive material, and hence develop a mechanism to predict these properties. A particularly promising model to explore impact sensitivity of EMs is based on vibrational up-pumping, i.e. the up-conversion of vibrational energy. This thesis explores the application of this model to a set of azide, organic molecular and polymorphic materials. Azide-based EMs share the common N3− explosophore. The electronic structure of this anion was followed as a function of its normal modes of vibration. It was found that excitation of the bending mode is sufficient to induce athermal electronic excitation of the molecule, and spontaneous decomposition. This is valid both in the gas and solid states. It is therefore suggested that this vibrational mode is largely responsible for decomposition of the azide materials. Based on calculations of the complete phonon dispersion curves, the various pathways to vibrational energy up-pumping were explored, namely via overtone and combination pathways. In particular, the relative rates of up-pumping into the N3 − bending mode were investigated. Remarkable agreement is found between these up-pumping rates and the relative ordering of the impact sensitivity of these azides. The calculated vibrational structures of organic molecular EMs were first compared with experimental inelastic neutron scattering spectra and found to provide accurate representation of the low temperature vibrational structure of these complex crystals. The decomposition pathways for organic EMs are not known and hence no target frequency could be unambiguously identified. Instead, the up-pumping model was developed for these materials by investigating the total rate of energy conversion into the internal vibrational manifold. A number of qualitative trends were identified, which may provide a mechanism for the rapid classification of EMs from limited vibrational information. The overtone pathways were found to offer a good agreement with experimental impact sensitivities of these compounds. However, the increased complexity of the vibrational structure of the organic EMs as compared to the azides required a more thorough treatment of the up-pumping mechanism to correctly reflect experimental sensitivities. The effects of temperature on up-pumping were also explored. The sensitivity of organic EMs is known to differ across polymorphic forms. Most notable are the HMX polymorphs. The calculated vibrational structure of two HMX polymorphs was confirmed by inelastic neutron scattering spectroscopy. The up-pumping model developed for molecular organic EMs was therefore extended to a comparison of these two HMX polymorphs. The polymorphic forms of FOX-7 were also investigated under the premise of the up-pumping model. Upon heating, FOX-7 undergoes two polymorphic transformations, which increases the layering of the materials. It therefore offered an opportunity to explore the widely-held hypothesis that layered materials are less sensitive than non-layered materials. The metastable γ-form was successfully recovered, and its experimental impact sensitivity investigated by BAM drop-hammer method. However, upon impact, the γ- polymorph appeared to convert to the α-form and initiate at the same input energy. Hence a considerable deficiency of experimental methods is identified when studying polymorphic materials. FOX-7 was therefore explored within the framework of the up-pumping model. The inelastic neutron scattering spectrum was collected for γ-FOX-7, which confirmed the calculated vibrational structure. It was shown that within the up-pumping model, the layered γ-polymorph is predicted to be less sensitive than the α-form, and results from a decrease in the maximum phonon-bath frequency. Hence a new mechanism is proposed to describe the insensitivity of layered compounds. The work presented in this thesis explores the applications of vibrational up-pumping to rationalise and predict the relative impact sensitivities of a range of EMs. Despite the approximations employed in construction of the model, it leads to excellent correlation with experimental results in all cases. This work therefore opens the door to a new fully ab initio approach to designing new EMs based solely on knowledge of the solid-state structure.

This thesis presents detailed electronic structure calculations and mixed quantum-classical dynamics simulations of the photodynamics of two small polyatomic molecules using "on-the-fly" surface-hopping. Most of the emphasis in this work is on CS2, which upon absorption of a UV photon undergoes a complex photodissociation process propagating across the potential energy surfaces of multiple singlet and triplet electronic states, under the influence of both nonadiabatic and spin-orbit coupling. Backed by extensive CASSCF and post-CASSCF electronic structure calculations, excitation to the 11B2 state is considered as a first exploration of the dynamics over the first picosecond, accounting for the lowest-lying four singlet and four triplet states. Following this, dynamics occurring after excitation to the 21B2 state, which is the state typically excited in time-resolved experimental studies of this system, are simulated. The additional computational complexity (with dynamics evolving on 19 interacting singlet and triplet states) and the limitations of "on-the-fly" techniques for a simulation of this size is discussed. This motivates initial steps towards generating full-dimensional grid-based surfaces for CS2 on which dynamics could later be simulated. These studies reinforce the importance of spin-orbit coupling in the dynamics and shine a light on the competitive nature of the singlet and triplet dissociation channels. Secondly, the short-time dynamics of trimethylamine are simulated, also using surface-hopping. Two sets of simulations are compared with regard to their description of the main dynamical features of the system, including dissociation of a methyl fragment and the extensive interplay between the low-lying 3pxyz and 3s Rydberg states, behaviour characteristic of tertiary substituted aliphatic amine systems. It is concluded that the sixth singlet state (3d) plays a significant role in the dissociation mechanism. The calculations and simulations here demonstrate the increasing utility of the conceptually intuitive surface-hopping approach in studying two contrasting classes of photochemical reactions, namely over-the-barrier photodissociation in CS2 and the photodynamics of low-lying Rydberg states in trimethylamine. In both cases, a comparison is made with complementary time-resolved experimental work by collaborators, articulating the need for experiment and theory to work together to provide a complete description of these fundamental chemical processes.

Advances in molecular-simulation methods allow for ever larger systems of particles to be studied and on longer timescales. Calculations are reaching such a scale that they can be used to address a vast range of key questions across chemistry, physics, and engineering. In this work, molecular dynamics and Monte Carlo simulations are employed to address two key areas: the structure and dynamics of simple aqueous ionic salt solutions at high concentrations; and the structure, dynamics, and phase behaviour of dipolar fluids (such as colloidal ferrofluids). The first part of the work begins with a study of the structure and dynamics in metastable, supersaturated, aqueous solutions of potassium chloride, and the possible relevance of these to the phenomenon of non-photochemical laser-induced nucleation (NPLIN). It is thought that the potassium and chloride ions form long-lived, amorphous clusters that may, under the influence of nanosecond laser pulses, undergo structural reorganisation to form post-critical crystal nuclei. It is found that spontaneous nucleation does not occur on the simulation timescale, but that amorphous clusters do form with cluster lifetimes comparable to those of the shortest laser pulses that can be used in NPLIN ( 100 picoseconds). Next, an alternative scenario for NPLIN involving rapid laser heating of impurity particles is examined by simulating heated carbon nanoparticles in saturated aqueous solutions of sodium chloride. The concentration at which an aqueous sodium chloride solution first crystallises on the simulation timescale is determined. A spherical carbon impurity is then added to a system with concentration close to, but lower than, the concentration at which crystallisation occurs on the simulation timescale. The effects that adding, and heating, this impurity has on the structure of this near-crystallising system are then observed. The second part of the work discusses model dipolar fluids, of direct relevance to colloidal ferrofluids (suspensions of magnetised nanoparticles in simple carrier liquids). The two-body, dipole-dipole interaction is long-ranged and anisotropic, and it is computationally expensive to handle in molecular simulations. Here a new method is proposed that relies on a formal mapping between the partition function of a dipolar fluid and that of a hypothetical fluid with many-body, short-ranged, isotropic interactions. Only the leading-order two-body interactions (akin to the van der Waals attraction) and three-body interactions (corresponding to the Axilrod-Teller potential) are retained. It is shown that this simple model is sufficient to reproduce the characteristic particle chaining and the associated disappearance of the vapour-liquid phase transition of dipolar fluids. Finally, the dynamical response of ferrofluids to oscillating magnetic fields (the dynamic magnetic susceptibility [DMS]) is studied. The DMS of ferrofluids, predicted by a new theory that takes into account the leading-order effects of dipole-dipole interactions, are critically compared to those found using Brownian-dynamics simulations of monodisperse systems of dipolar particles. This new theory is found to provide more accurate predictions of the DMS than previous theories, with the DMS predicted to a high degree of accuracy for systems with dipolar coupling strength in the experimentally achievable region.

In the mid-1800s, monitoring networks were established to investigate atmospheric composition impacts, and the conditions giving rise to them. The development of these networks, in terms of coordination and standardisation between contributing sites, has resulted in large advances in knowledge of the nature of atmospheric composition. Currently thousands of sites collect high quality atmospheric composition measurements globally. This thesis contends that in order to maximise the information derived from these measurements, a further advancement in standardisation is required to encompass the interpretation of monitoring network data. Currently there are limited examples of a common interpretation of data applied across all sites in a monitoring network, especially in relation to specific atmospheric composition impacts. In this thesis, a ‘chemical climatology’ framework is outlined which provides a common basis for targeting analysis towards identifying the linkage between a specific atmospheric composition impact and its causal drivers. Case studies apply the chemical climatology framework to demonstrate its utility in deriving scientific and policy relevant conclusions using measurement data from the UK monitoring supersites located at Harwell and Auchencorth. Prior to this, the representativeness of each site is quantified through the application of cluster analysis to ozone data at 100 rural European sites to identify groupings of sites with similar ozone variation. Harwell was representative of rural locations within 120 km of London, while Auchencorth was representative of a larger, transboundary spatial domain including the remainder of the rural UK. The first case study links the impact of ozone on human health (quantified by SOMO10 and SOMO35 metrics) and vegetation (flux-based PODY) to meteorological and emissions drivers. Between 1990 and 2013 at Harwell, there was a significant decrease in the contribution of European ozone to determining the impacts. Improvement in the human health impact was heavily dependent on the choice of metric (SOMO35 decreased, no change in SOMO10), and the vegetation impacts had not improved as high ozone episodes frequently coincided with plant conditions which reduced ozone uptake. These chemical climates emphasise the need for ozone mitigation on larger (hemispheric) scales than currently implemented. Secondly, the impact of 27 measured VOCs on the extent of the regional ozone increment is assessed. The photochemical loss of VOCs is then linked to reported gridded VOC emissions using air mass back trajectory analysis. Ethene and m+p-xylene had the largest diurnal photochemical loss during maximum monthly regional ozone increment, but the key conclusion was the limitation introduced through the reporting of gridded VOC emissions in heavily aggregated source sectors. Finally, the conditions producing the long term health impact of particulate matter (quantified by annual average PM10 and PM2.5 concentrations) at each site are derived through integration of measurements of PM10 and PM2.5 with measurements of PM constituents. It is shown that the frequent, moderate PM10 and PM2.5 concentrations made a larger contribution to annual average values compared to the relatively infrequent high, episodic concentrations. The contribution of PM constituents and the contribution of local vs regional emissions to the range of PM concentrations is investigated. It was concluded that similar reductions in the contribution of secondary inorganic aerosol to the moderate PM10 and PM2.5 concentrations could be achieved from both the reduction of frequently traversed, smaller emissions sources, and less frequently traversed, larger emissions sources. The final chapter demonstrates the benefits from the extension of this framework to an entire monitoring network. It is envisioned that for each atmospheric composition impact, a standard set of statistics would be calculated which quantify the ‘impact’, ‘state’ and ‘drivers’ of that chemical climate. Calculation of ozone human health chemical climates across 100 European monitoring sites demonstrate this concept. This standardised interpretation of monitoring network data not only allows consistent comparison of an impact, but the common basis for determining how the impact is derived allows for the consideration of novel mitigation strategies and their spatial applicability.

Glycerol monooleate (GMO) is a common engine oil lubricant additive used to reduce friction and wear in engines. The aim of this thesis is to investigate the properties of GMO in bulk and under confined conditions with shear using molecular dynamics simulations. The self-assembly of GMO into reverse micelles (RMs) in toluene and n-heptane solvents is studied at a range of concentrations and subsequently with several common engine impurities over simulation timescales of 5-30 ns. The dimensional properties of the RMs are found to correspond well with experimentally studied SANS/SAXS measurements. Secondly, the properties of GMO confined between mica surfaces are studied under quiescent and shear conditions. Under shear, the performance of GMO as a friction modifier is studied and the structural and frictional properties are examined. In particular, the mass density and velocity profiles of the fluid are used to gain insights into the structure and dynamics of the confined GMO fluid films, under a variety of shear rates and surface separation. The data is found to fit excellently to the universal friction curve. Following this the effect of hydrolysing the GMO to oleic acid is studied in bulk and under shear, it is found that increasing oleic acid concentration typically reduces the propensity to self-assemble and under confinement increases the friction coefficient. And finally, a study on a range of other similar surfactants is conducted to investigate the effect of unsaturation, head group and chain length on the calculated friction coefficient and the structure of the surfactant films.

The number of three-dimensional structures of potential protein targets available in several platforms such as the Protein Data Bank is subjected to a constant increase over the last decades. This observation should be an additional motivation to use structure-based methodologies in drug discovery. In the recent years, different success stories of Structure Based Drug Design approach have been reported. However, it has also been shown that a lack of druggability is one of the major causes of failure in the development of a new compound. The concept of druggability can be used to describe proteins with the capability to bind drug-like compounds. A general consensus suggests that around 10% of the human genome codes for molecular targets that can be considered as druggable. Over the years, the protein druggability was studied with a particular interest to capture structural descriptors in order to develop computational methodologies for druggability assessment. Different computational methods have been published to detect and evaluate potential binding sites at protein surfaces. The majority of methods currently available are designed to assess druggability of a static structure. However it is well known that sometimes a few local rearrangements around the binding site can profoundly influence the affinity of a small molecule to its target. The use of techniques such as molecular dynamics (MD) or Metadynamics could be an interesting way to simulate those variations. The goal of this thesis was to design a new computational approach, called JEDI, for druggability assessment using a combination of empirical descriptors that can be collected ‘on-the-fly’ during MD simulations. JEDI is a grid-based approach able to perform the druggability assessment of a binding site in only a few seconds making it one of the fastest methodologies in the field. Agreement between computed and experimental druggability estimates is comparable to literature alternatives. In addition, the estimator is less sensitive than existing methodologies to small structural rearrangements and gives consistent druggability predictions for similar structures of the same protein. Since the JEDI function is continuous and differentiable, the druggability potential can be used as collective variable to rapidly detect cryptic druggable binding sites in proteins with a variety of MD free energy methods.

NPLIN was studied in supersaturated solutions (S = 1.06) of potassium chloride (KCl) and bromide (KBr). The fraction of samples nucleated (f) follows a nonlinear dependence on peak power density that approaches f = 1 at higher incident powers. It is shown that a lower threshold power is required for nucleation using 532 nm laser pulses than at 1064 nm, and that a higher fraction of samples nucleate when exposed to 532 nm pulses at a given laser power. Comparison with KCl shows higher fractions of KBr samples nucleate with lower threshold values at both wavelengths. Samples of KCl of equal supersaturation at two different temperatures (23 and 33 °C) exposed to 1064 nm pulses show that those at 33 °C are significantly more labile to nucleation. The ratio of samples nucleated at 33 °C compared to those at 23 °C was 2.11 ± 0.47. A classical nucleation model based on activation of subcritical solute clusters accounts remarkably well for the experimental data and provides phenomological values of the crystal–solution interfacial tension (γ) at 23 °C for KCl and KBr of 5.283 and 4.817 mJ m-2. At 33 °C, the model yields a best-fit value of γ = 5.429 mJ m-2 for KCl. As an extension of this work the use of an evanescent wave (ew) generated by total internal reflection was investigated as a method to cause nucleation in supersaturated KCl solution. Evanescent wave NPLIN (ew-NPLIN) was shown to cause nucleation. The results showed a higher laser-power threshold required for nucleation and sample lability greater than that of bulk NPLIN. In a second approach to understanding NPLIN, the structures of concentrated solutions were probed by a series of laser scattering experiments. Evidence showing populations of particles in solution was provided by Rayleigh laser scattering (RLS) experiments. Scattering in solutions prepared to be nearly saturated (S = 0.95) was observed using a low magnification (×10) microscope objective; almost all solutions showed the presence of scattering objects moving freely in solution. For those that showed no particles, it was noted that the solutions were typically of higher solute concentration (> 11 mol% solute). Ammonium nitrate solution showed no particles using ×10 magnification, however particles were identified when higher magnification was used (×50 and ×100). Video footage of the Rayleigh scattering observed in aqueous solutions of glycine, urea and ammonium nitrate obtained using ×50 magnification were analysed using a custom nanoparticle tracking software. The results showed a population of particles in aqueous urea and glycine solutions with particle concentrations of the order 108 particles cm-3 and mean hydrodynamic diameter of approximately 267 ± 1 and 173 ± 2 nm respectively. Not enough particles were identified in ammonium nitrate solution to complete the tracking analysis; however a fluctuating background scatter suggested a population of particles with sizes below the limit of resolution of the optical system. Using aqueous urea solution as a model system the structure of the particles identified in solution was investigated using scanning microscopy. The second-harmonic scattering (SHS) signal measured in concentrated aqueous urea solution was measured as a function of solution concentration (C) over a range of saturation conditions from undersaturated (S = 0.15) to supersaturated (S = 1.86). The results show a non-linear increase in SHS signal with local maxima near S = 0.95 and 1.75 suggesting a change in solution structure near these points. Rayleigh scattering images indicate the presence of particles in nearly saturated (S = 0.95) urea solutions. Time-dependent SHS measurements indicate that signals originate from individual events encountered during scanning of the sample through the focal volume of the probe laser, consistent with second harmonic generation (SHG) from particles. SHG from aqueous dispersions of barium titanate (BaTiO3) nanoparticles with diameters < 200 nm, showed signals ~20 times larger than urea solutions. The results suggest the existence of a population of semi-ordered clusters of urea that changes with solution concentration.

Lubricants oils play an important role in a wide range of industrial and mechanical processes, where they are used to reduce both the friction and wear between interacting moving surfaces. The current understanding of lubrication is mainly based on empirical evidence, obtained from experiment. In this work, computer simulations are used to gain insight into the microscopic processes that lead to the modification of friction and wear by additive molecules adsorbed on sheared surfaces lubricated by thin liquid films. The specific area of application under consideration is the lubrication of automotive engine parts. The interactions between additive molecules are first determined using density-functional theory calculations. The interactions are then validated against available experimental data, and incorporated in to large-scale molecular-dynamics (MD) simulations, which are used to explore the structure and frictional properties of lubricated surfaces. The surfaces considered are alumina and iron oxide. The lubricating oils are squalane and hexadecane, which are representative of automotive lubricants, and the additive molecules are stearic acid, oleic acid and various oleamides. MD simulations are performed over wide ranges of the relevant physical conditions, namely pressure, temperature, and shear rate. The additives adsorb on to the surfaces and provide a physical connection between the surfaces and the lubricating liquid. The structures of adsorbed films are analysed in microscopic detail using functions of atomic positions and molecular geometry. Several important trends are identified, linking molecular isomerism and architecture with the structure and stability of the adsorbed film. In addition, the simulation results are used to gain insight on recent experimental measurements of film structure. The friction coefficients in various situations are computed and analysed with reference to the structures of the adsorbed films. The synthesis of these data and observed trends yields new insights on the intimate link between the molecular properties of lubricants, and the macroscopic frictional properties of macroscopic lubricated engine parts.

Computer simulations have become a vital tool in modern science. The ability to reliably move beyond the capabilities of experiment has allowed great insights into the nature of matter. To enable the study of a wide range of systems and properties a plethora of simulation techniques have been developed and refined, allowing many aspects of complex systems to be demystified. I have used a range of these to study a variety of systems, utilising the latest technology in high performance computing (HPC) and novel, nanoscale models. Monte Carlo (MC) simulation is a commonly used method to study the properties of system using statistical mechanics and I have made use of it in published work [1] to study the properties of ferrogels in homogeneous magnetic fields using a simple microscopic model. The main phenomena of interest concern the anisotropy and enhancement of the elastic moduli that result from applying uniform magnetic fields before and after the magnetic grains are locked in to the polymer-gel matrix by cross-linking reactions. The positional organization of the magnetic grains is influenced by the application of a magnetic field during gel formation, leading to a pronounced anisotropy in the mechanical response of the ferrogel to an applied magnetic field. In particular, the elastic moduli can be enhanced to different degrees depending on the mutual orientation of the fields during and after ferrogel formation. Previously, no microscopic models have been produced to shed light on this effect and the main purpose of the work presented here is to illuminate the microscopic behaviour. The model represents ferrogels by ensembles of dipolar spheres dispersed in elastic matrices. Experimental trends are shown to be reflected accurately in the simulations of the microscopic model while shedding light on the microscopic mechanism causing these effects. These mechanisms are shown to be related to the behaviour of the dipoles during the production of the gels and caused by the chaining of dipoles in magnetic fields. Finally, simple relationships between the elastic moduli and the magnetization are proposed. If supplemented by the magnetization curve, these relationships yield the dependencies of the elastic moduli on the applied magnetic field, which are often measured directly in experiments. While MC simulations are useful for statistical studies, it can be difficult to use them to gather information about the dynamics of a system. In this case, Molecular Dynamics (MD) is more widely used. MD generally utilises the classical equations of motion to simulate the evolution of a system. For large systems, which are often of interest, and multi-species polymers, the required computer power still poses a challenge and requires the use of HPC techniques. The most recent development in HPC is the use of Graphical Processing Units (GPU) for the fast solution of data parallel problems. In further published work [2], I have used a bespoke MD code utilising GPU acceleration in order to simulate large systems of block copolymers(BC) in solvent over long timescales. I have studied thin films of BC solutions drying on a flat, smooth surface which requires long timescales due to the ’slow’ nature of the process. BC’s display interesting self-organisation behaviour in bulk solution and near surfaces and have a wide range of potential applications from semi-conductors to self-constructing fabrics. Previous studies have shown some unusual behaviour of PI-PEO diblock co-polymers adsorbing to a freshly cleaved mica surface. These AFM studies showed polymers increasing in height over time and proposed the change of affinity of mica to water and the loss of water layers on the surface as a driver for this change. The MD simulation aimed to illuminate the process involved in this phenomena. The process of evaporation of water layers from a surface was successfully simulated and gave a good indication that the process of solvent evaporation from the surface and the ingress of solvent beneath the adsorbed polymer caused the increase in height seen in experiment.

Ionic liquids (IL) are salts which are liquid at low temperatures, typically with melting points under 100 °C. In recent years ILs have been treated as novel solvents and used in a wide variety of applications such as analytical and separation processes, electrochemical devices and chemical syntheses. The properties of many ILs have been extensively studied; these studies have primarily focused on the investigation of key physical properties including viscosity, density and solubility. This thesis presents mass spectrometry (MS) and computational data to investigate the intrinsic interactions between a small number of IL ions and also their interactions with contaminants. MS was used to study gas-phase aggregates of three ILs based on the 1-butyl-3- methylimidazolium (C4mim+) cation. The influence of different ion sources was investigated on C4mimCl. Conventional electrospray ionisation (ESI) and nano-ESI techniques were compared with recently developed sonic-spray ionisation (SSI) and plasma assisted desorption ionisation (PADI). SSI was found to be beneficial to the formation of larger aggregates while PADI was significantly less efficient. Gas-phase structures of the singly charged cationic aggregates of C4mimCl were characterised with the aid of collision induced dissociation (CID) and density functional theory (DFT) calculations. Additionally, CID and DFT gave consistent results for the relative stability of the C4mimCl aggregates, showing a good agreement between experiment and theory. Mixed solutions of C4mimCl with a range of metal chloride salts were used to form aggregates incorporating both IL and metal chlorides. LiCl, NaCl, KCl, CsCl, MgCl2 and ZnCl2 were all combined with C4mimCl. Magic number characteristics were observed for a number of pure IL and mixed aggregates. Many of the mixed species were characterised using MS and DFT calculations. In particular, the relative stabilities were determined and the structures of the aggregates were calculated. It was found that the metal ions would normally act as a core for the aggregates with the stability determined by the metal-chlorine binding strength and the steric hindrance of the aggregates. It was necessary to exploit pseudopotentials as opposed to all-electron basis sets for the larger aggregates and aggregates containing heavy atoms. While water is a very effective contaminant for ILs it was not possible to observe gas-phase IL aggregates incorporating this despite using multiple methods. Additionally the presence of protonated aggregates was likewise not observed throughout the range of experiments. Possible structures where these features would be incorporated were studied with DFT to obtain some insight into their lack of formation.

The term “soft matter” applies to a variety of physical systems, such as liquids, colloids, polymers, foams, gels, and granular materials. The most fascinating aspect of soft matter lies in the fact that they are not atomic or molecular in nature. They are instead macromolecular aggregates, whose spatial extent lies in the domain 1 nm to 1 ¹m. Some of the most important examples of soft matter are polymers, which exhibit intriguing and useful physical properties. In this work, the adsorption and self assembly of linear and star polymers on smooth surfaces are studied using coarse-grained, bead-springmolecular models and Langevin dynamics computer simulations. The aim is to gain insight on atomic-forcemicroscopy images of polymer films on mica surfaces, adsorbed from dilute solution following a good solvent-to-bad solvent quenching procedure. In the case of linear polymers, under certain experimental conditions, a bimodal cluster distribution is observed. It is demonstrated that this type of distribution can be reproduced in the simulations, and rationalized on the basis of the polymer structures prior to the quench. In addition to providing insight on experimental observations, the simulation results support a number of predicted scaling laws such as the decay of the monomer density as a function of distance from the surface, and the scaling of the filmheight with the strength of the polymer-surface interactions. Star polymers represent a special class of polymers, in which one end of each linear chain is tethered to a small central core to forma single particle. The discovery of these molecules led to the synthesis of a wide range of new materials. Their structures are effectively considered as intermediate between those of colloids and linear polymers. We explore the behaviour of the star polymers (which are like “soft colloids”) in the proximity of a surface, using Langevin dynamics simulations. A number of different measurements such as the height, radius of gyration, and asphericity of adsorbed stars with different number of arms, are shown to provide valuable insights on experimental findings. The simplest soft matter systems consist of spherical, rigid colloidal particles. Examples of such particles are chemically synthesized polystyrene or silica particles. We investigated the neighbour distribution in a two-dimensional polydisperse harddisk fluid, corresponding physically to a colloidal monolayer. The disk diameter distribution was defined by a power-law with the aim of realizing a scale-free nearneighbour network. Scale-free (power-law) behaviour is found in many important networks, for example, in transportation systems, biochemical reactions, scientific and movie-actor collaborations, and sexual contacts. We have provided the first example of a scale-free network in amodel condensed-matter system. Finally, we use genetic algorithms, a method for efficiently searching for minima on energy landscapes, to investigate the ordered equilibrium structures formed by binary mixtures of anisotropic dipolar particles confined on a plane, under the presence of an external magnetic field. The anisotropy of the interparticle forces is controlled by tilting the external magnetic field with respect to the plane. Initially, as the field is tilted the structures are only slightly perturbed, but once the anisotropy exceeds a critical value, completely new structures emerge.

This works examines the question whether a vapour-liquid phase transition exists in systems of particles with purely dipolar interactions, a topic which has been the subject of a longstanding debate. Monte Carlo simulation results for two modi operandi to tackle this issue are presented. One approach examines the phase behaviour of fluids of charged hard dumbbells (CHD), each made up of two oppositely charged hard spheres with diameters σ and separation d. In the limit d/σ → 0, and with the temperature scaled accordingly, the system corresponds to dipolar hard spheres (DHS) while for larger values of d ionic interactions are dominant. The crossover between ionic and dipolar regimes is examined and a linear variation of the critical temperature T*c in dipolar reduced units as a function of d is observed, giving rise to an extrapolated T*cDHS ≈ 0:15. The second approach focuses on the dipolar Yukawa hard sphere (DYHS)fluid, which is given by a dipolar hard sphere and an attractive isotropic interaction Y of the Yukawa tail form. In this case, the DHS limit is obtained for Y → 0. It is found that T*c depends linearly on the isotropic interaction strength Y over a wide range, coinciding with the results for the CHD model and extrapolating to a similar value of T*c;DHS. However, with the use of specially adapted biased Monte Carlo techniques which are highly efficient, it is shown that the linear variation of T*c is violated for very small values of the Yukawa interaction strength, almost two orders of magnitude smaller than the characteristic dipolar interaction energy. It is found that phase separation is not observable beyond a critical value of the Yukawa energy parameter, even though in thermodynamic and structural terms, the DYHS and DHS systems are very similar. It is suggested that either some very subtle physics distinguishes the DYHS and DHS systems, or the observation of a phase transition in DHSs is precluded by finite-size effects. In the context of phase separation in highly correlated fluids, new flat-histogram Monte Carlo simulation techniques based on the Wang-Landau algorithm are evaluated and shown to be useful tools. This work presents a general and unifying framework for deriving Monte Carlo acceptance rules which facilitate flat histogram sampling. The framework yields uniform sampling rules for thermodynamic states given either by the mechanically extensive variables appearing in the Hamiltonian or, equivalently, uniformly sample the thermodynamic fields which are conjugate to these mechanical variables.