MRC Laboratory of Molecular Biology
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Printed gas sensors.
No full textThe rapid development of the Internet of Things (IoT)-enabled applications and connected automation are increasingly making sensing technologies the heart of future intelligent systems. The potential applications have wide-ranging implications, from industrial manufacturing and chemical process control to agriculture and nature conservation, and even to personal health monitoring, smart cities, and national defence. Devices that can detect trace amounts of analyte gases represent the most ubiquitous of these sensor platforms. In particular, the advent of nanostructured organic and inorganic materials has significantly transformed this field. Highly sensitive, selective, and portable sensing devices are now possible due to the large surface to volume ratios, favorable transport properties and tunable surface chemistry of the sensing materials. Here, we present a review on the recent development of printed gas sensors. We first introduce the state-of-the-art printing techniques, and then describe a variety of gas sensing materials including metal oxides, conducting polymers, carbon nanotubes and two-dimensional (2D) materials. Particular emphases are given to the working principles of the printing techniques and sensing mechanisms of the different material systems. Strategies that can improve sensor performance via materials design and device fabrication are discussed. Finally, we summarize the current challenges and present our perspectives in opportunities in the future development of printed gas sensors
The influence of constraint rolls on temperature evolution and distribution in radial ring rolling
No full textProducing nearer to net-shape hot rolled rings whilst meeting demanding product property requirements is a major industrial challenge, especially in high value materials such as nickel-based superalloys. Recent process innovations propose additional tooling to improve control over the geometric accuracy, but it is not known what influence this will have on the temperature distribution and product properties. To study this, a set of 24 thermally-coupled numerical simulations was conducted for a key material test case, Inconel 718, with a furnace temperature of 1030 °C. The thermal parameters used in the model were validated against an a newly-conducted full industrial trial, and both average surface temperature prediction and rolling tool temperature were found to be accurate to within ±10 °C. The set of simulations focused on the production of two target ring geometries; for each target ring, four different rolling scenarios were developed, covering a realistic range of machine operating parameters. All eight of these scenarios were simulated with three different tooling set-ups, using two, four and six constraint rolls. For a typical rolling scenario with two constraint rolls, the average surface temperature was found to drop by 79 °C after transfer to the machine, and then by a further 54 °C during rolling. Trebling the number of constraint rolls doubled the temperature drop to 113 °C. By comparison, a factor 2.7 increase in rolling time led to a factor 3.0 increase in temperature loss to 166 °C. Simulations for the second, slenderer, target geometry predicted comparable surface temperature drops, but increased temperature loss in the core of the ring. In Inconel 718 regions of the ring that drop below 900 °C experience strongly retarded dynamic recrystallization, rendering them prone to damage. Trebling the constraint rolls was found to increase the area vulnerable to damage by 0–20%, across the 8 scenarios. These predictions suggest that the influence of constraint rolls could to some extent be mitigated by reasonable reductions in rolling or transfer time. However, if used to produce slenderer, nearer to net-shape rings with larger overall reductions and longer process times then temperature and product property control will be difficult
Combined InSAR and Terrestrial Structural Monitoring of Bridges
No full textThis article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge's own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies
A simple, reliable and robust reinforcement method for the fabrication of (RE)–Ba–Cu–O bulk superconductors
No full textA 2-D correlation to evaluate fuel-cladding gap thermal conductance in mixed oxide fuel elements for sodium-cooled fast reactors
No full textThe paper defines a parameterization for the fuel-cladding gap thermal conductance in a Sodium Cooled Fast Reactor. This collaboration took place within the EU-funded ESFR-SMART project. This requires use of predictive codes that have been validated where possible against experimental data. This study relied on 7 fuel performance codes thus providing confidence in the recommended correlation. A single pin model for both the inner and outer fuel was built. The fuel was burned for 2100 Effective Full Power Days, with the axial power distribution varying over time. This paper presents a comparison between the codes' results and a 2-D correlation for the heat conductance with respect to fuel burn-up and fuel rating. The fuel is broken down into nodes with specific fuel rating and burn-up, leading to the gap conductance expressed as a function of nodal fuel rating and burn-up. Data was then compiled for all the nodes, for both fissile and fertile regions, for both inner and outer fuel for all 7 codes. A 2D fit was applied to the data thus obtained. The results obtained show a general increase of heat conductance with fuel rating and burn-up, from 0.22 at 0 burn-up and 10 to 0.45 at 0 burnup and 50 and to 1.00 at 150 and 50. Some spread between codes has been noted and appears to be consistent with the spread published earlier by several code developers. Sensitivity to various modelling assumptions is under investigation. This is aided by the use of numerous fuel performance codes which enables a wide ranging and thorough sensitivity analysis
Load transfer within the bolted joint of a laminate made from ultra-high molecular weight polyethylene fibres
No full textThe mechanism of load transfer within the bolted joint of a laminate sheet made from ultra-high molecular weight polyethylene (UHMWPE) plies is investigated both experimentally and by an analytical model. The nature of load transfer and the active failure mechanisms are obtained as a function of joint geometry and of the lateral clamping force on the faces of the laminate (by pre-tensioning of the bolt). A combination of X-ray tomography and optical microscopy reveal that the dominant failure mechanism in the clamped joint is shear failure involving splits of the 0° plies and sliding at the interface between the 0° and 90° plies. A simple analytical model is developed for this shear failure mechanism and, upon noting the competing failure mechanisms of bearing failure, bolt shear and of tensile failure of the 0° plies, a failure mechanism map is constructed in terms of the geometry of the bolted joint, for the case of no pre-tension of the bolt. The analytical model for shear failure suggests that the enhancement in joint strength with increased pre-tensioning of bolt is due to the fact that the shear strength of the UHMWPE increases with increasing hydrostatic pressure
Lattice benchmarking of deterministic, Monte Carlo and hybrid Monte Carlo reactor physics codes for the soluble-boron-free SMR cores
No full textSince the use of deterministic transport code WIMS can significantly reduce the computational time compared to the Monte Carlo (MC) code Serpent and hybrid MC code MONK, one of the major objectives of this study is to observe whether deterministic code WIMS can provide accuracy in reactor physics calculations while comparing Serpent and MONK. Therefore, numerical benchmark calculations for a soluble-boron-free (SBF) small modular reactor (SMR) assembly have been performed using the WIMS, Serpent and MONK. Although computationally different in nature, these codes can solve the neutronic transport equations and calculate the required neutronic parameters. A comparison in neutronic parameters between the three codes has been carried out using two types of candidate fuels: 15% 235U enriched homogeneously mixed all-UO2 fuel and 18% 235U enriched micro–heterogeneous ThO2-UO2 duplex fuel in a 2D fuel assembly model using a 13×13 arrangement. The eigenvalue/reactivity (k∞) and 2D assembly pin power distribution at different burnup states in the assembly depletion are compared using three candidate nuclear data files: ENDF/B-VII, JEF2.2 and JEF3.1. A good agreement in k∞ values was observed among the codes for both the candidate fuels. The differences in k∞ between the codes are ~200 pcm when cross-sections based on the same nuclear data file are used. A higher difference (up to ~450 pcm) in the k∞ values is observed among the codes using cross-sections based on different data files. Finally, it can be concluded from this study that the good agreement in the results between the codes found provides enhanced confidence that modeling of SBF, SMR propulsion core systems with micro-heterogeneous duplex fuel can be performed reliably using deterministic neutronics code WIMS, offering the advantage of less expensive computation than that of the MC Serpent and hybrid MC MONK codes
The swelling of cellulose foams due to liquid transport
No full textCellulose-based foams are available commercially in a dry pre-compressed state, but can swell upon infiltration by a suitable liquid. A series of experiments reveal that pre-compressed foams can swell in one direction by an order of magnitude when infiltrated by water or glycerol; in contrast, no swelling accompanies infiltration by ethanol. The kinetics (and underlying mechanisms) of infiltration and of swelling are quantified by a series of critical experiments on both pre-compressed foam and pre-expanded foam, using water, glycerol and ethanol. Infiltration is driven by capillarity, cell wall diffusion and by opening of capillaries during swelling of the foam. Ethanol-infiltration of pre-expanded foam or of pre-compressed foam occurs by a combination of capillary action and diffusion without swelling of the foam. Water induces swelling of the pre-compressed foam on a time scale of 1 s, whereas glycerol swells the foam progressively over 105 s, after an initial incubation period of 103 s. When the foam is in the pre-expanded state, water and glycerol seep horizontally into the foam by capillary action; in contrast, water-rise and glycerol-rise in the vertical direction is initially by capillary action and then, once the Jurin height has been attained, diffusion leads to a much slower rate of seepage. Confirmation of the existence of a Jurin height for the vertical rise of water into pre-compressed foam or pre-expanded foam is obtained by X-ray computer tomography. Infiltration into pre-compressed foam by water or by glycerol involves the propagation of a swelling front, with liquid feeding first by capillary flow and then by diffusion within the cell walls. An understanding of liquid infiltration and the resultant swelling of foams is the first step in the design of actuating multi-scale lattices made from pre-compressed foam
A generative model for molecular distance geometry
No full textGreat computational effort is invested in generating equilibrium states for molecular systems using, for example, Markov chain Monte Carlo. We present a probabilistic model that generates statistically independent samples for molecules from their graph representations. Our model learns a low-dimensional manifold that preserves the geometry of local atomic neighborhoods through a principled learning representation that is based on Euclidean distance geometry. In a new benchmark for molecular conformation generation, we show experimentally that our generative model achieves state-of-the-art accuracy. Finally, we show how to use our model as a proposal distribution in an importance sampling scheme to compute molecular properties
Accelerating the discrete dipole approximation via circulant preconditioning
No full textThe discrete dipole approximation (DDA) is a popular numerical method for electromagnetic scattering calculations. The standard DDA formulation involves the uniform discretization of the underlying volume integral equation, leading to a linear system of convolution form. This permits a matrix-vector product to be performed with O(nlogn) complexity via the fast-Fourier transform (FFT). Thus, in principle, the system can be solved rapidly using an iterative method. However, it is well known that the convergence of iterative methods becomes increasing slow as the optical size and refractive index of the scattering obstacle are increased. In this paper, we present a preconditioning strategy based on the multi-level circulant preconditioner of Chan and Olkin [Numer. Algorithms 6, 89 (1994)] and assess its performance for improving this rate of convergence. In particular, we approximate the system matrix by a circulant matrix which can be inverted efficiently using the FFT. We present numerical experiments for scattering by highly oblate non-absorbing hexagonal plates, demonstrating that this approach serves as an effective preconditioning strategy, reducing simulation times by orders of magnitude in many cases. A Matlab implementation of this work is freely available online