1,442 research outputs found

    Broadband computational rheology for material characterisation

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    Rheology is a wide-reaching field whose applications are underpinned by a prior knowledge of the ‘viscoelastic’ properties of (complex) materials generally employed across industries such as oil and gas, food processing, cosmetics, and biophysics; the latter being the main focus of this thesis. Biomedical studies often only have access to small sample volumes, which make conventional bulk rheology techniques unsuitable for their characterization, this has led to the development of a new field called microrheology, where new techniques can characterise the viscoelastic properties of complex fluids by using only a few microlitres of a sample volume. As a branch of rheology, microrheology utilises the same underpinning principles and aims to calculate a material’s properties, including the complex shear modulus, which in turn describes how the material behaves. The following thesis is aimed at investigating the use of microrheology with optical tweezers in a series of papers exploring different areas within the field of microrheology. Each paper targets certain gaps within the field and as such this thesis is fairly broad reaching touching on algorithm development, machine learning and shear flow analysis. Chapter 2 presents the work “i-RheoFT: Fourier transforming sampled functions without artefacts”, and introduces an open access MATLAB code, “i-RheoFT”, which can evaluate the Fourier transform of any generic time-dependent function with a finite number of data points. I-RheoFT could be of particular interest and use to those who study sampled or time-averaged functions. The paper investigates three experimental parameters employing i-RheoFT: (i) the density of initial experimental data points that describe the signal, (ii) the interpolation function used to perform virtual oversampling of the signal, which is required for accurate evaluation of the Fourier transform, and (iii) the effect that signal noise has on the Fourier transform. As the chapter shows, a high number of initial data points or a high signal-to-noise ratio corresponds to a good performance for each interpolation function used. Alternatively, a low number of initial points or signal-to-noise ratio corresponds to poor performance across each interpolation function used. As one would expect, there exists a threshold, for both the signal-to-noise and the number of initial points, at which the performance becomes acceptable and has been identified in both cases in the chapter. More recently further development of this work has led to the creation of two open source applications [1, 2] available for download, these aim to compute the complex shear modulus from bulk rheology and atomic force microscopy measurements respectively. Moreover, since its publication this work has been used in three studies [3–5], two of which feature the author of this thesis as a co-author. Chapter 3 examines the claim that linear microrheology with optical tweezers should not be used for the study of living systems due to the variation between the time required to collect statistically valid data and the mutational time of the studied living system. This work is a first step at enhancing conventional statistical mechanics analysis of particle trajectories, captured using microrheology with optical tweezers, by exploiting machine learning techniques to reduce the current measurement time from tens of minutes down to as little as one second. The chapter describes how computer simulated trajectories, of Newtonian fluids with viscosities spanning three decades, have been used to corroborate the requirement for sufficiently long measurements to offer a good estimation of the fluid viscosity using conventional analytical techniques. In addition, the work provides a method for estimating the measurement time of a microrheology with optical tweezers experiment, based on the relative viscosity of the fluid being analysed to produce an uncertainty as low as 1%. Furthermore, this chapter presents a machine learning algorithm that can predict the viscosity of both simulated and real trajectories, carrying an error as low as ∌ 0.3%, using only one second of data. It is believed that with this machine learning enhancement, microrheology with optical tweezers will become a powerful tool for studies involving living systems. Chapter 4 presents an investigation into flow induced self-assembly (FISA) of particles suspended in a viscoelastic shear thinning fluid subjected to simple shear flow. This phenomena is currently not fully understood and little has been done in literature so far to investigate the possible effects of the shear-induced elastic instability. In this work, a bespoke cone and plate shear cell is used to provide new insights on the FISA dynamics. In particular, we have fine tuned the applied shear rates to investigate the chaining phenomenon of micron-sized spherical particles suspended into a viscoelastic fluid characterised by a distinct onset of elastic instability. This has allowed us to reveal three phenomena never reported in literature before, i.e.: (I) the onset of the elastic instability is strongly correlated with an enhancement of FISA; (II) particle chains break apart when a constant shear is applied for ‘sufficiently’ long-time (i.e. much longer than the fluids’ longest relaxation time). This latter point correlates well with the outcomes of parallel superposition shear measurements, which (III) reveal a fading of the elastic component of the suspending fluid during continuous shear flows

    Crystal Structures of Metal Complexes

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    This reprint contains 11 papers published in a Special Issue of Molecules entitled "Crystal Structures of Metal Complexes". I will be very happy if readers will be interested in the crystal structures of metal complexes

    Virtual Mirrors: Non-Line-of-Sight Imaging Beyond the Third Bounce

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    Non-line-of-sight (NLOS) imaging methods are capable of reconstructing complex scenes that are not visible to an observer using indirect illumination. However, they assume only third-bounce illumination, so they are currently limited to single-corner configurations, and present limited visibility when imaging surfaces at certain orientations. To reason about and tackle these limitations, we make the key observation that planar diffuse surfaces behave specularly at wavelengths used in the computational wave-based NLOS imaging domain. We call such surfaces virtual mirrors. We leverage this observation to expand the capabilities of NLOS imaging using illumination beyond the third bounce, addressing two problems: imaging single-corner objects at limited visibility angles, and imaging objects hidden behind two corners. To image objects at limited visibility angles, we first analyze the reflections of the known illuminated point on surfaces of the scene as an estimator of the position and orientation of objects with limited visibility. We then image those limited visibility objects by computationally building secondary apertures at other surfaces that observe the target object from a direct visibility perspective. Beyond single-corner NLOS imaging, we exploit the specular behavior of virtual mirrors to image objects hidden behind a second corner by imaging the space behind such virtual mirrors, where the mirror image of objects hidden around two corners is formed. No specular surfaces were involved in the making of this paper

    Enhancing the Structural Stability of α-phase Hybrid Perovskite Films through Defect Engineering Approaches under Ambient Conditions

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    This thesis investigates methods whereby perovskite solar cell power conversion efficiency and material stability may be improved. Hybrid perovskites have gained increased attention for optoelectronic applications due to favourable properties such as strong absorption, facile processing, and changeable band-gap. Despite excellent improvements in power conversion efficiency of devices, perovskite films are unstable, degrading with relative ease in the presence of moisture, oxygen, light, heat, and electric fields. The focus of this thesis is on ambient atmosphere stability, concerned with the influence of moisture in particular on perovskite film fabrication, degradation, and device functionality. In order to shed light on the impact of ambient atmosphere on perovskite films, experiments are designed to investigate films during fabrication and degradation. The influences firstly of stoichiometry during ambient fabrication, and then ionic substitution (with caesium and formadinium) upon moisture-induced degradation are investigated. Finally, films and devices with a novel composition incorporating Zn are fabricated under ambient conditions to investigate the effect of Zn addition on perovskite film stability

    Elucidating the Relationships Between Spider Size, Joint Stiffness, and the Mechanical Frequency Response of the Body

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    Spiders use vibrations to sense their surroundings. It has been suggested that the vibration perception in spiders may be altered by the mechanics of the body. I studied the biomechanics of spiders, at the level of leg joints and the whole body. To study joints, I quantified the allometry of leg joint stiffness in spiders. I found that the stiffness of spider joints increased nearly isometrically with increasing body mass, partly by having shorter and thicker leg segments and also by other unknown means. Using these data, I developed empirically validated biomechanical models which predicted the effects of mechanics on vibrational filtering within the body. Interestingly, both models and empirical data showed that the relatively linear increase in joint stiffness with mass meant that the mechanical filtering of spider bodies may be size independent, indicating that spiders of different masses or ecologies may sense the world in similar ways

    Universal imprinting of chirality with chiral light by employing plasmonic metastructures

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    Chirality, either of light or matter, has proved to be very practical in biosensing and nanophotonics. However, the fundamental understanding of its temporal dynamics still needs to be discovered. A realistic setup for this are the so-called metastructures, since they are optically active and are built massively, hence rendering an immediate potential candidate. Here we propose and study the electromagnetic-optical mechanism leading to chiral optical imprinting on metastructures. Induced photothermal responses create anisotropic permittivity modulations, different for left or right circularly polarized light, leading to temporal-dependent chiral imprinting of hot-spots, namely imprinting of chirality. The above effect has not been observed yet, but it is within reach of modern experimental approaches. The proposed nonlinear chiroptical effect is general and should appear in any anisotropic material; however, we need to design a particular geometry for this effect to be strong. These new chiral time-dependent metastructures may lead to a plethora of applications.Comment: Main (29 pages, 6 figures) and supplemental (46 pages, 35 figures

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Terahertz Near-Field Microscopy on Resonant Structures and Thin Films

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    A high-flux cold atom source based on a nano-structured atom chip

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    Modern physics is challenged by existential questions about the most fundamental interactions of matter. While three of the four known fundamental forces are modeled in the grand unified theory [1], gravity seems to be incompatible in its current formulation. Many physicists search to unify them, but often the invented models violate well-tested assumptions such as the Einstein Equivalence Principle, a cornerstone of General Relativity. Despite macroscopic tests of this principle have already been carried out to high precision [2–4], quantum tests exploiting matter-wave interferometry [5–7] may provide complementary information [8] with even higher precision [9–11]. These yield their ultimate performance with Bose-Einstein condensates (BECs) over long evolution times as conventionally achieved by free-fall in space [12]. As such, a new generation of high performance BEC sources is required with strict budgets on size, weight and power demands. Efforts to miniaturize these sources have been pursued with promising results using atom chips [13–15], but further miniaturization of these setups is necessary. In an attempt to simplify the usage of atom chips, the following thesis describes the development of a nano-structured atom chip that allows for single-beam magneto-optical trapping. The chip is implemented in a dedicated atom chip test facility that has been planned, built and characterized in the scope of this thesis. The facility features a state-of-the-art master oscillator power amplifier laser system, compact control electronics [13,15–17] and a high-flux 2D+-MOT as an atomic source. Despite the simplified setup, magneto-optical trapping of 1.1 × 10^9 Rubidium atoms was achieved within 1 s which is comparable to other atom chip setups and well above previous achievements with grating MOTs [18–23]. Illuminating the grating with a beam profile from a custom-built top-hat beam expander was instrumental to achieve balanced laser cooling in a large volume above the grating. This allowed to cool 4.7 × 10^8 atoms to 13 ”K and transfer 2.4 × 10^8 atoms into a large-volume Ioffe-Pritchard type magnetic chip trap, demonstrating the required mode-matching between the laser cooled atoms and the magnetic trap. The trapped atoms were then used to characterize the magnetic field environment of the test facility using radio frequency spectroscopy gauging the surrounding magnetic bias coils. These results demonstrate the feasibility of using a nano structured atom chip to build a single-beam BEC source which could become the foundation of future high-performance quantum sensors on ground and in space

    Gut-brain interactions affecting metabolic health and central appetite regulation in diabetes, obesity and aging

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    The central aim of this thesis was to study the effects of gut microbiota on host energy metabolism and central regulation of appetite. We specifically studied the interaction between gut microbiota-derived short-chain fatty acids (SCFAs), postprandial glucose metabolism and central regulation of appetite. In addition, we studied probable determinants that affect this interaction, specifically: host genetics, bariatric surgery, dietary intake and hypoglycemic medication.First, we studied the involvement of microbiota-derived short-chain fatty acids in glucose tolerance. In an observational study we found an association of intestinal availability of SCFAs acetate and butyrate with postprandial insulin and glucose responses. Hereafter, we performed a clinical trial, administering acetate intravenously at a constant rate and studied the effects on glucose tolerance and central regulation of appetite. The acetate intervention did not have a significant effect on these outcome measures, suggesting the association between increased gastrointestinal SCFAs and metabolic health, as observed in the observational study, is not paralleled when inducing acute plasma elevations.Second, we looked at other determinants affecting gut-brain interactions in metabolic health and central appetite signaling. Therefore, we studied the relation between the microbiota and central appetite regulation in identical twin pairs discordant for BMI. Second, we studied the relation between microbial composition and post-surgery gastrointestinal symptoms upon bariatric surgery. Third, we report the effects of increased protein intake on host microbiota composition and central regulation of appetite. Finally, we explored the effects of combination therapy with GLP-1 agonist exenatide and SGLT2 inhibitor dapagliflozin on brain responses to food stimuli
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