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Glassy materials differ greatly from crystalline solids; their lack of long range order makes it difficult to model their behaviour. While a lot of work has been done regarding the properties of glass-forming polymers, their exact nature is not well understood. This thesis primarily focuses on the chain-length dependence of glassy dynamics, in particular poly(methyl methacrylate) (PMMA), which is of interest due to its commercial and industrial applications. Using dielectric spectroscopy, rheology, and calorimetry, the relaxation behaviour of chain-modes and the segmental, alpha, relaxation were determined as a function of chain-length. Time-temperature superposition adequately describes the rheology data, even though decoupling between chain-modes and segmental relaxations were observed. Changes occur in the behaviour of the glass transition temperature, T_g, at the molecular weight, M, of the "dynamic bead", M_R. Relaxation times of the alpha relaxation and chain-modes of PMMA and other polymer systems collapse when renormalized by T_g, suggesting universal behaviour. This occurs when the number of correlated monomers, N_a, in the alpha relaxation corresponds to M_R. N_a was determined using modulated calorimetry and dielectric spectroscopy. A clear change in N_a was observed at M_R for less flexible PMMA and polystyrene, whereas this was less pronounced for the more flexible poly(dimethyl siloxane). This may relate to a change from intermolecular to mainly intramolecular behaviour. Furthermore, for PMMA the activation enthalpies of the alpha and beta relaxations below T_g are approximately equal at M_R, suggesting these relaxations act on similar lengthscales. The activation enthalpy of the beta relaxation also becomes M invariant for M > M_R, suggesting M_R characterises the beta relaxation. Finally, the ionic conductivity was determined for PMMA and two poly(propylene glycol) (PPG) chain-length systems. The alpha relaxation and conductivity were coupled for PPG, whereas for PMMA decoupling occurred for M > M_R. This demonstrates that polymer behaviour leads to this decoupling in PMMA. We also show that non-polymeric systems do not exhibit this decoupling behaviour.

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This thesis investigates methods of increasing the imaging speed of Stochastic Optical Reconstruction Microscopy (STORM); a superresolution imaging technique which breaks the diffraction limit by imaging single molecules. Initially the imaging conditions were optimised to maximize both the Signal-to-Noise Ratio (SNR) and the number of molecules localised in order to push the system to image at the fastest rate possible. It was found that the lowest readout laser power possible should be used at a frame rate between 100 - 150 fps. The optimum concentration of MEA - a component of the STORM imaging buffer - was found to be 100 mM. Whilst the optimized conditions afford some speed increase, there is a more fundamental question to be investigated: how many localisations are required for an accurate reconstruction of the sample? The answer to this question will allow a reduction in the image acquisition time by only imaging until the minimum number of molecules have been localised. The density of localisations was studied over time and a simple histogram analysis suggested that using a trade off between density and localisation limited regimes is a valid method to increase the imaging speed by determining a "finishing point". The localisation density increased linearly over time for all samples tested, however some areas reached the cut off density more quickly than others. Using several analysis methods and simulated data it was shown that the blinking behaviour of molecules is a random process and that the variability in resolution across an image is mostly due to a non uniform labelling distribution. Finally, dual colour samples were imaged, as labelling the target structure with two coloured dyes was hypothesised to double the imaging speed. This was found to be true, however there was no overall reduction in acquisition time as dual labelled samples have a slower increase in localisation density over time.

The Deep Underground Neutrino Experiment (DUNE) is a next-generation neutrino experiment which will be built at the Sanford Underground Research Facility (SURF), and will receive a wide-band neutrino beam from Fermilab, 1300 km away. At this baseline DUNE will be able to study many of the properties of neutrino mixing, including the neutrino mass hierarchy and the value of the CP-violating complex phase (δCP). DUNE will utilise Liquid Argon (LAr) Time Projection Chamber (TPC) (LArTPC) technology, and the Far Detector (FD) will consist of four modules, each containing 17.1 kt of LAr with a fiducial mass of around 10 kt. Each of these FD modules represents around an order of magnitude increase in size, when compared to existing LArTPC experiments. The 35 ton detector is the first DUNE prototype for the single (LAr) phase design of the FD. There were two running periods, one from November 2013 to February 2014, and a second from November 2015 to March 2016. During the second running period, a system of TPCs was installed, and cosmic-ray data were collected. A method of particle identification was developed using simulations, though this was not applied to the data due to the higher than expected noise level. A new method of determining the interaction time of a track, using the effects of longitudinal diffusion, was developed using the cosmic-ray data. A camera system was also installed in the detector for monitoring purposes, and to look for high voltage breakdowns. Simulations concerning the muon-induced background rate to nucleon decay are performed, following the incorporation of the MUon Simulations UNderground (MUSUN) generator into the DUNE software framework. A series of cuts which are based on Monte Carlo truth information is developed, designed to reject simulated background events, whilst preserving simulated signal events in the n→K++e− decay channel. No background events are seen to survive the application of these cuts in a sample of 2 × 109 muons, representing 401.6 years of detector live time. This corresponds to an annual background rate of < 0.44 events·Mt−1·year−1 at 90% confidence, using a fiducial mass of 13.8 kt.

Neutrino physics is approaching the precision era, with current and future experiments aiming to perform highly accurate measurements of the parameters which govern the phenomenon of neutrino oscillations. The ultimate ambition with these results is to search for evidence of CP-violation in the lepton sector, currently hinted at in the world-leading analyses from present experiments, which may explain the dominance of matter over antimatter in the Universe. The Deep Underground Neutrino Experiment (DUNE) is a future long-baseline experiment based at Fermi National Accelerator Laboratory (FNAL), with a far detector at the Sanford Underground Research Facility (SURF) and a baseline of 1300 km. In order to make the required precision measurements, the far detector will consist of 40 kton liquid argon and an embedded time projection chamber. This promising technology is still in development and, since each detector module is around a factor 15 larger than any previous experiment employing this design, prototyping the detector and design choices is critical to the success of the experiment. The 35-ton experiment was constructed for this purpose and will be described in detail in this thesis. The outcomes of the 35-ton prototype are already influencing DUNE and, following the successes and lessons learned from the experiment, confidence can be taken forward to the next stage of the DUNE programme. The main oscillation signal at DUNE will be electron neutrino appearance from the muon neutrino beam. High-precision studies of these νe interactions requires advanced processing and event reconstruction techniques, particularly in the handling of showering particles such as electrons and photons. Novel methods developed for the purposes of shower reconstruction in liquid argon are presented with an aim to successfully develop a selection to use in a νe charged-current analysis, and a first-generation selection using the new techniques is presented.