I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[18165]
Abstract: In this contribution, we introduce a simple approach to quickly estimate the environment-induced crack velocity (CV) as a function of the calculated applied stress intensity factor (K) developed during the slow strain rate testing of aluminum alloys exposed to aqueous or humid air-type environments. The CV-K behavior for a commercial aluminum-magnesium alloy, AA5083-H131, sensitized and pre-exposed to a 0.6 m NaCl solution has been estimated from slow strain rate test data. The predicted threshold K and crack velocities match recently published data for the same alloy in similarly sensitized conditions where the CV-K data were obtained using state-of-the-art fracture mechanics-based testing.
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Jun 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[10366, 13848, 17632]
Abstract: Many insects have triplets of camera type eyes, called ocelli, whose function remains unclear for most species. Here, we investigate the ocelli of the bumblebee, Bombus terrestris, using reconstructed 3D data from X-ray microtomography scans combined with computational ray-tracing simulations. This method enables us, not only to predict the visual fields of the ocelli, but to explore for the first time the effect that hair has on them as well as the difference between worker female and male ocelli.
We find that bumblebee ocellar fields of view are directed forward and dorsally, incorporating the horizon as well as the sky. There is substantial binocular overlap between the median and lateral ocelli, but no overlap between the two lateral ocelli. Hairs in both workers and males occlude the ocellar field of view, mostly laterally in the worker median ocellus and dorsally in the lateral ocelli. There is little to no sexual dimorphism in the ocellar visual field, suggesting that in B. terrestris they confer no advantage to mating strategies.
We compare our results with published observations for the visual fields of compound eyes in the same species as well as with the ocellar vision of other bee and insect species.
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May 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[15444]
Open Access
Abstract: The intervertebral disc (IVD) has a complex and multiscale extracellular matrix structure which provides unique mechanical properties to withstand physiological loading. Low back pain has been linked to degeneration of the disc but reparative treatments are not currently available. Characterising the disc’s 3D microstructure and its response in a physiologically relevant loading environment is required to improve understanding of degeneration and to develop new reparative treatments. In this study, techniques for imaging the native IVD, measuring internal deformation and mapping volumetric strain were applied to an in situ compressed ex vivo rat lumbar spine segment. Synchrotron X-ray micro-tomography (synchrotron CT) was used to resolve IVD structures at microscale resolution. These image data enabled 3D quantification of collagen bundle orientation and measurement of local displacement in the annulus fibrosus between sequential scans using digital volume correlation (DVC). The volumetric strain mapped from synchrotron CT provided a detailed insight into the micromechanics of native IVD tissue. The DVC findings showed that there was no slipping at lamella boundaries, and local strain patterns were of a similar distribution to the previously reported elastic network with some heterogeneous areas and maximum strain direction aligned with bundle orientation, suggesting bundle stretching and sliding. This method has the potential to bridge the gap between measures of macro-mechanical properties and the local 3D micro-mechanical environment experienced by cells. This is the first evaluation of strain at the micro scale level in the intact IVD and provides a quantitative framework for future IVD degeneration mechanics studies and testing of tissue engineered IVD replacements.
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May 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[9396]
Open Access
Abstract: X-ray computed tomography and, specifically, time-resolved volumetric tomography data collections (4D datasets) routinely produce terabytes of data, which need to be effectively processed after capture. This is often complicated due to the high rate of data collection required to capture at sufficient time-resolution events of interest in a time-series, compelling the researchers to perform data collection with a low number of projections for each tomogram in order to achieve the desired `frame rate'. It is common practice to collect a representative tomogram with many projections, after or before the time-critical portion of the experiment without detrimentally affecting the time-series to aid the analysis process. For this paper these highly sampled data are used to aid feature detection in the rapidly collected tomograms by assisting with the upsampling of their projections, which is equivalent to upscaling the θ-axis of the sinograms. In this paper, a super-resolution approach is proposed based on deep learning (termed an upscaling Deep Neural Network, or UDNN) that aims to upscale the sinogram space of individual tomograms in a 4D dataset of a sample. This is done using learned behaviour from a dataset containing a high number of projections, taken of the same sample and occurring at the beginning or the end of the data collection. The prior provided by the highly sampled tomogram allows the application of an upscaling process with better accuracy than existing interpolation techniques. This upscaling process subsequently permits an increase in the quality of the tomogram's reconstruction, especially in situations that require capture of only a limited number of projections, as is the case in high-frequency time-series capture. The increase in quality can prove very helpful for researchers, as downstream it enables easier segmentation of the tomograms in areas of interest, for example. The method itself comprises a convolutional neural network which through training learns an end-to-end mapping between sinograms with a low and a high number of projections. Since datasets can differ greatly between experiments, this approach specifically develops a lightweight network that can easily and quickly be retrained for different types of samples. As part of the evaluation of our technique, results with different hyperparameter settings are presented, and the method has been tested on both synthetic and real-world data. In addition, accompanying real-world experimental datasets have been released in the form of two 80 GB tomograms depicting a metallic pin that undergoes corruption from a droplet of salt water. Also a new engineering-based phantom dataset has been produced and released, inspired by the experimental datasets.
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May 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[14080]
Abstract: Osteoregenerative biomaterials for the treatment of bone defects are under much development, with the aim of favouring osteointegration up to complete bone regeneration. A detailed investigation of bone-biomaterial integration is vital to understanding and predicting the ability of such materials to promote bone formation, preventing further bone damage and supporting load-bearing regions. This study aims to characterise the ex vivo micromechanics and microdamage evolution of bone-biomaterial systems at the tissue level, combining high resolution synchrotron micro-computed tomography, in situ mechanics and digital volume correlation. Results showed that the main microfailure events were localised close to or within the newly formed bone tissue, in proximity to the bone-biomaterial interface. The apparent nominal compressive load applied to the composite structures resulted in a complex loading scenario, mainly due to the higher heterogeneity but also to the different biomaterial degradation mechanisms. The full-field strain distribution allowed characterisation of microdamage initiation and progression. The findings reported in this study provide a deeper insight into bone-biomaterial integration and micromechanics in relation to the osteoregeneration achieved in vivo, for a variety of biomaterials. This could ultimately be used to improve bone tissue regeneration strategies.
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Apr 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[15507]
Abstract: Diffusion magnetic resonance imaging (dMRI) is considered as a useful tool to study solid tumours. However, the interpretation of dMRI signal and validation of quantitative measurements of is challenging. One way to address these challenges is by using a standard reference material that can mimic tumour cell microstructure. There is a growing interest in using hollow polymeric microspheres, mainly prepared by multiple steps, as mimics of cells in healthy and diseased tissue. The present work reports on tumour cell-mimicking materials composed of hollow microspheres for application as a standard material in dMRI. These microspheres were prepared via one-step co-electrospraying process. The shell material was poly(d,l-lactic-co-glycolic acid) (PLGA) polymers with different molecule weights and/or ratios of glycolic acid-to-lactic, while the core was polyethylene glycol (PEG) or ethylene glycol. The resultant co-electrosprayed products were characterised by optical microscopy, scanning electron microscopy (SEM) and synchrotron X-ray micro-CT. These products were found to have variable structures and morphologies, e.g. from spherical particles with/without surface hole, through beaded fibres to smooth fibres, which mainly depend on PLGA composition and core materials. Only the shell material of PLGA polymer with ester terminated, Mw 50,000–75,000 g mol−1, and lactide:glycolide 85:15 formed hollow microspheres via the co-electrospraying process using the core material of 8 wt% PEG/chloroform as the core. A water-filled test object (or phantom) was designed and constructed from samples of the material generated from co-electrosprayed PLGA microspheres and tested on a 7 T MRI scanner. The preliminary MRI results provide evidence that hollow PLGA microspheres can restrict/hinder water diffusion as cells do in tumour tissue, implying that the phantom may be suitable for use as a quantitative validation and calibration tool for dMRI.
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Mar 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[12864]
Abstract: Previous artificial lung surrogates used hydrogels or balloon-like inflatable structures without reproducing the alveolar network or breathing action within the lung. A physiologically-accurate, air-filled lung model inspired by soft robotics is presented. The model, Soft Robotic Surrogate Lung (SRSL) is composed of clusters of artificial alveoli made of platinum-cured silicone, with internal pathways for air flow. Mechanical tests in conjunction with full-field image and volume correlation techniques characterise the SRSL behaviour. SRSLs enable both healthy and pathological lungs to be studied in idealised cases. Although simple in construction, the connected airways demonstrate clearly the importance of an inflatable network for capturing basic lung behaviour (compared to more simplified lung surrogates). The SRSL highlights the potentially damaging nature of local defects caused by occlusion or overdistension (present in conditions such as chronic obstructive pulmonary disease). The SRSL is developed as a potential upgrade to conventional surrogates used for injury risk predictions in trauma. The deformation of the SRSL is evaluated against blast trauma using a shock tube. The SRSL was compared to other conventional trauma surrogate materials and showed greatest similarity to lung tissue. The SRSL has the potential to complement conventional biomechanical studies and reduce animal use in basic biomechanics studies, where high severity protocols are used.
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Mar 2019
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I13-2-Diamond Manchester Imaging
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Sophie
Le Cann
,
Isabella
Silva Barreto
,
Adam
Urga
,
Vivien
Sotiriou
,
Aurelie
Levillain
,
Mikael J.
Turunen
,
Marianne
Liebi
,
Andrew J.
Bodey
,
Ulf
Johansson
,
Niamh
Nowlan
,
Hanna
Isaksson
Abstract: Long bone mineralization develops through endochondral ossification, where a cartilage template is replaced by mineralized bone. From the primary ossification center in the middle of the long bone, mineralization progresses during growth in both directions at the growth plates. While the basic sequence of bone formation during embryogenesis is known, almost no detailed characterization of early developing and new mineralized tissue and bone has been conducted. This project aims to characterize the most important steps in early mineralization of the skeleton, using a multi-scale and multi-modal approach. More specifically, bone mineralization in the embryonic mouse humerus is studied from the anatomical down to the compositional and structural level using a range of novel high-resolution imaging methods based on high-intensity x-rays (synchrotron).
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Feb 2019
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I13-2-Diamond Manchester Imaging
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Abstract: Understanding the interaction of nano/micro-particles with evolving microstructures during solidification is critical for developing new materials with improved mechanical properties through either particulate reinforcement and/or via microstructural refinement. In this study, we investigate the influence of nanoparticles on the evolving dendrites in both Mg and Al based metal matrix composites via in situ synchrotron tomography. Ultrasonic treatment was applied during the raw material preparation to break the particle agglomeration. The solidification of primary dendrites was characterized and quantified. The results reveal the underlying physical mechanisms that enable nanoparticles to modify the grain size in both alloy systems. These insights into dendrite evolution help both to inform and validate numerical models of the solidification microstructures of metal matrix composites.
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Feb 2019
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I13-2-Diamond Manchester Imaging
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Diamond Proposal Number(s):
[13848, 16052]
Open Access
Abstract: The quality of visual information that is available to an animal is limited by the size of its eyes. Differences in eye size can be observed even between closely related individuals, yet we understand little about how this affects vision. Insects are good models for exploring the effects of size on visual systems because many insect species exhibit size polymorphism. Previous work has been limited by difficulties in determining the 3D structure of eyes. We have developed a novel method based on x-ray microtomography to measure the 3D structure of insect eyes and to calculate predictions of their visual capabilities. We used our method to investigate visual allometry in the bumblebee Bombus terrestris and found that size affects specific aspects of vision, including binocular overlap, optical sensitivity, and dorsofrontal visual resolution. This reveals that differential scaling between eye areas provides flexibility that improves the visual capabilities of larger bumblebees.
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Feb 2019
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