Modelling failure of composite specimens with defects under compression loading

Composite structures exhibit many different failure mechanisms, but attempts to model composite failure frequently make a priori assumptions about the mechanism by which failure will occur. Wang et al. [1] conducted compressive tests on four configurations of composite specimen manufactured with out-of-plane waviness created by ply-drop defects. There were significantly different failures for each case. Detailed finite element models of these experiments were developed which include competing failure mechanisms. The model predictions correlate well with experimental results-both qualitatively (location of failure and shape of failed specimen) and quantitatively (failure load). The models are used to identify the progression of failure during the compressive tests, determine the critical failure mechanism for each configuration, and investigate the effect of cohesive parameters upon specimen strength. This modelling approach which includes multiple competing failure mechanisms can be applied to predict failure in situations where the failure mechanism is not known in advance. © 2013 Elsevier Ltd. All rights reserved.

Single-sensor maximum power point tracking algorithms

Single-sensor maximum power point tracking algorithms for photovoltaic systems are presented. The algorithms have the features, characteristics and advantages of the widely used incremental conductance (INC) algorithm. However; unlike the INC algorithm which requires two sensors (the voltage sensor and the current sensor), the single-sensor algorithms are more desirable because they require only one sensor: the voltage sensor. The algorithms operate by maximising power at the DC-DC converter output, instead of the input. © 2013 The Institution of Engineering and Technology.

α-Synuclein senses lipid packing defects and induces lateral expansion of lipids leading to membrane remodeling.

There is increasing evidence for the involvement of lipid membranes in both the functional and pathological properties of α-synuclein (α-Syn). Despite many investigations to characterize the binding of α-Syn to membranes, there is still a lack of understanding of the binding mode linking the properties of lipid membranes to α-Syn insertion into these dynamic structures. Using a combination of an optical biosensing technique and in situ atomic force microscopy, we show that the binding strength of α-Syn is related to the specificity of the lipid environment (the lipid chemistry and steric properties within a bilayer structure) and to the ability of the membranes to accommodate and remodel upon the interaction of α-Syn with lipid membranes. We show that this interaction results in the insertion of α-Syn into the region of the headgroups, inducing a lateral expansion of lipid molecules that can progress to further bilayer remodeling, such as membrane thinning and expansion of lipids out of the membrane plane. We provide new insights into the affinity of α-Syn for lipid packing defects found in vesicles of high curvature and in planar membranes with cone-shaped lipids and suggest a comprehensive model of the interaction between α-Syn and lipid bilayers. The ability of α-Syn to sense lipid packing defects and to remodel membrane structure supports its proposed role in vesicle trafficking.

Cortical thickness estimation of the proximal femur from multi-view Dual-Energy X-ray Absorptiometry (DXA)

Hip fracture is the leading cause of acute orthopaedic hospital admission amongst the elderly, with around a third of patients not surviving one year post-fracture. Although various preventative therapies are available, patient selection is difficult. The current state-of-the-art risk assessment tool (FRAX) ignores focal structural defects, such as cortical bone thinning, a critical component in characterizing hip fragility. Cortical thickness can be measured using CT, but this is expensive and involves a significant radiation dose. Instead, Dual-Energy X-ray Absorptiometry (DXA) is currently the preferred imaging modality for assessing hip fracture risk and is used routinely in clinical practice. Our ambition is to develop a tool to measure cortical thickness using multi-view DXA instead of CT. In this initial study, we work with digitally reconstructed radiographs (DRRs) derived from CT data as a surrogate for DXA scans: this enables us to compare directly the thickness estimates with the gold standard CT results. Our approach involves a model-based femoral shape reconstruction followed by a data-driven algorithm to extract numerous cortical thickness point estimates. In a series of experiments on the shaft and trochanteric regions of 48 proximal femurs, we validated our algorithm and established its performance limits using 20 views in the range 0°-171°: estimation errors were 0:19 ± 0:53mm (mean +/- one standard deviation). In a more clinically viable protocol using four views in the range 0°-51°, where no other bony structures obstruct the projection of the femur, measurement errors were -0:07 ± 0:79 mm. © 2013 SPIE.

High purity GaAs nanowires free of planar defects: Growth and characterization

We investigate how to tailor the structural, crystallographic and optical properties of GaAs nanowires. Nanowires were grown by Au nanoparticle-catalyzed metalorganic chemical vapor deposition. A high arsine flow rate, that is, a high ratio of group V to group III precursors, imparts significant advantages. It dramatically reduces planar crystallographic defects and reduces intrinsic carbon dopant incorporation. Increasing V/III ratio further, however, instigates nanowire kinking and increases nanowire tapering. By choosing an intermediate V/III ratio we achieve uniform, vertically aligned GaAs nanowires, free of planar crystallographic defects, with excellent optical properties and high purity. These findings will greatly assist the development of future GaAs nanowire-based electronic and optoelectronic devices, and are expected to be more broadly relevant to the rational synthesis of other III-V nanowires. © 2008 WILEY-VCH Verlag GmbH & Co. KGaA.