Mechanics of microfilaments networks : a cross-scales study

The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

Impact of the piston secondary motion on its slap force

A theoretical model is developed for the analysis of piston secondary motion. Based on this model, the slap force of a specific L6 diesel engine was compared when considering different boundary conditions, such as lubricating oil on cylinder liner, surface roughness, deformation of cylinder liner and piston skirt. It is concluded that it is necessary to consider the secondary motion of piston in the analysis of the inner excitation for an internal combustion engine. A more comprehensive consideration of the boundary condition (i.e., more close to the actual condition) will lead to a smaller maximum slap force, and among all boundary conditions considered in this paper, the structural deformation of the piston skirt and cylinder liner is the most influential factor. The theoretical model developed and findings obtained in this study will benefit the future analysis and design of advanced internal combustion engine structures.

Label-free SERS for natural product provenance

Introduction Natural product provenance is important in the food, beverage and pharmaceutical industries, for consumer confidence and with health implications. Raman spectroscopy has powerful molecular fingerprint abilities. Surface Enhanced Raman Spectroscopy’s (SERS) sharp peaks allow distinction between minimally different molecules, so it should be suitable for this purpose. Methods Naturally caffeinated beverages with Guarana extract, coffee and Red Bull energy drink as a synthetic caffeinated beverage for comparison (20 µL ea.) were reacted 1:1 with Gold nanoparticles functionalised with anti-caffeine antibody (ab15221) (10 minutes), air dried and analysed in a micro-Raman instrument. The spectral data was processed using Principle Component Analysis (PCA). Results The PCA showed Guarana sourced caffeine varied significantly from synthetic caffeine (Red Bull) on component 1 (containing 76.4% of the variance in the data). See figure 1. The coffee containing beverages, and in particular Robert Timms (instant coffee) were very similar on component 1, but the barista espresso showed minor variance on component 1. Both coffee sourced caffeine samples varied with red Bull on component 2, (20% of variance). ************************************************************ Figure 1 PCA comparing a naturally caffeinated beverage containing Guarana with coffee. ************************************************************ Discussion PCA is an unsupervised multivariate statistical method that determines patterns within data. Figure 1 shows Caffeine in Guarana is notably different to synthetic caffeine. Other researchers have revealed that caffeine in Guarana plants is complexed with tannins. Naturally sourced/ lightly processed caffeine (Monster Energy, Espresso) are more inherently different than synthetic (Red Bull) /highly processed (Robert Timms) caffeine, in figure 1, which is consistent with this finding and demonstrates this technique’s applicability. Guarana provenance is important because it is still largely hand produced and its demand is escalating with recognition of its benefits. This could be a powerful technique for Guarana provenance, and may extend to other industries where provenance / authentication are required, e.g. the wine or natural pharmaceuticals industries.

Tuneable resonance properties of graphene by nitrogen-dopant

Doping as one of the popular methods to manipulate the properties of nanomaterials has received extensive application in deriving different types of graphene derivates, while the understanding of the resonance properties of dopant graphene is still lacking in literature. Based on the large-scale molecular dynamics simulation, reactive empirical bond order potential, as well as the tersoff potential, the resonance properties of N-doped graphene were studied. The studied samples were established according to previous experiments with the N atom’s percentage ranging from 0.43%-2.98%, including three types of N dopant locations, i.e., graphitic N, pyrrolic N and pyridinic N. It is found that different percentages of N-dopant exert different influence to the resonance properties of the graphene, while the amount of N-dopant is not the only factor that determines its impact. For all the considered cases, a relative large percentage of N-dopant (2.98% graphitic N-dopant) is observed to introduce significant influence to the profile of the external energy, and thus lead to an extremely low Q-factor comparing with that of the pristine graphene. The most striking finding is that, the natural frequency of the defective graphene with N-dopant appears uniformly larger than that of the pristine defective graphene. While for the perfect graphene, the N-dopant shows less influence to its natural frequency. This study will enrich the current understanding of the influence of dopants on graphene, which will eventually shed lights on the design of different molecules-doped graphene sheet.

Computation of ECG signal features using MCMC modelling in software and FPGA reconfigurable hardware

Computational optimisation of clinically important electrocardiogram signal features, within a single heart beat, using a Markov-chain Monte Carlo (MCMC) method is undertaken. A detailed, efficient data-driven software implementation of an MCMC algorithm has been shown. Initially software parallelisation is explored and has been shown that despite the large amount of model parameter inter-dependency that parallelisation is possible. Also, an initial reconfigurable hardware approach is explored for future applicability to real-time computation on a portable ECG device, under continuous extended use.

Thermal stability and decomposition kinetics of styrene-butadiene rubber nanocomposites filled with different particle sized kaolinites

A series of styrene-butadiene rubber (SBR) nanocomposites filledwith different particle sized kaolinites are prepared via a latex blending method. The thermal stabilities of these clay polymer nanocomposites (CPN) are characterized by a range of techniques including thermogravimetry (TG), digital photos, scanning electron microscopy (SEM) and Raman spectroscopy. These CPN show some remarkable improvement in thermal stability compared to that of the pure SBR. With the increase of kaolinite particle size, the residual char content and the average activation energy of kaolinite SBR nanocomposites all decrease; the pyrolysis residues become porous; the crystal carbon in the pyrolysis residues decrease significantly from 58.23% to 44.41%. The above results prove that the increase of kaolinite particle size is not beneficial in improving the thermal stability of kaolinite SBR nanocomposites.

A biomechanical analysis of growing rods used in the management of early onset scoliosis

INTRODUCTION Managing spinal deformities in young children is challenging, particularly early onset scoliosis (EOS). Surgical intervention is often required if EOS has been unresponsive to conservative treatment particularly with rapidly progressive curves. An emerging treatment option for EOS is fusionless scoliosis surgery. Similar to bracing, this surgical option potentially harnesses growth, motion and function of the spine along with correcting spinal deformity. Dual growing rods are one such fusionless treatment, which aims to modulate growth of the vertebrae. The aim of this study was to ascertain the extent to which semiconstrained growing rods (Medtronic, Sofamor, Danek, Memphis, TN) with a telescopic sleeve component, reduce rotational constraint on the spine compared with standard "constrained / rigid" rods and hence potentially provide a more physiological mechanical environment for the growing spine. METHODS Six 40-60kg English Large White porcine spines served as a model for the paediatric human spine. Each spine was dissected into a 7 level thoracolumbar multi-segment unit (MSU), removing all non-ligamentous soft tissues and leaving 3cm of ribs either side. Pure nondestructive axial rotation moments of ±4Nm at a constant rotation rate of 8deg.s-1 were applied to the mounted MSU spines using a biaxial Instron testing machine. Displacement of each vertebral level was captured using a 3D motion tracking system (Optotrak 3020, Northern Digital Inc, Waterloo, ON). Each spine was tested in an un-instrumented state first and then with appropriately sized semi-constrained growing rods and rigid rods in alternating sequence. The rods were secured by multi-axial pedicle screws (Medtronic CD Horizon) at levels 2 and 6 of the construct. The range of motion (ROM), neutral zone (NZ) size and stiffness (Nm.deg-1) were calculated from the Instron load-displacement data and intervertebral ROM was calculated through a MATLAB algorithm from Optotrak data. RESULTS Irrespective of the order of testing, rigid rods significantly reduced the total ROM compared with semi-constrained rods (p<0.05) with in a significantly stiffer spine for both left and right axial rotation (p<0.05). Analysing the intervertebral motion within the instrumented levels 2-6, rigid rods showed reduced ROM compared with semi-constrained growing rods and compared with un-instrumented motion segments. CONCLUSION Semi-constrained growing rods maintain similar stiffness in axial rotation to un-instrumented spines, while dual rigid rods significantly reduce axial rotation. Clinically the effect of semi-constrained growing rods as observed in this study is that they would be expected to allow growth via the telescopic rod components while maintaining the axial flexibility of the spine, which may reduce occurrence of the crankshaft phenomenon.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

Optimal Bayesian experimental design for models with intractable likelihoods using indirect inference applied to biological process models

This paper addresses the problem of determining optimal designs for biological process models with intractable likelihoods, with the goal of parameter inference. The Bayesian approach is to choose a design that maximises the mean of a utility, and the utility is a function of the posterior distribution. Therefore, its estimation requires likelihood evaluations. However, many problems in experimental design involve models with intractable likelihoods, that is, likelihoods that are neither analytic nor can be computed in a reasonable amount of time. We propose a novel solution using indirect inference (II), a well established method in the literature, and the Markov chain Monte Carlo (MCMC) algorithm of Müller et al. (2004). Indirect inference employs an auxiliary model with a tractable likelihood in conjunction with the generative model, the assumed true model of interest, which has an intractable likelihood. Our approach is to estimate a map between the parameters of the generative and auxiliary models, using simulations from the generative model. An II posterior distribution is formed to expedite utility estimation. We also present a modification to the utility that allows the Müller algorithm to sample from a substantially sharpened utility surface, with little computational effort. Unlike competing methods, the II approach can handle complex design problems for models with intractable likelihoods on a continuous design space, with possible extension to many observations. The methodology is demonstrated using two stochastic models; a simple tractable death process used to validate the approach, and a motivating stochastic model for the population evolution of macroparasites.

Electromagnetic propulsion and separation by chirality of nanoparticles in liquids

We introduce a new mechanism for the propulsion and separation by chirality of small ferromagnetic particles suspended in a liquid. Under the action of a uniform dc magnetic field H and an ac electric field E isomers with opposite chirality move in opposite directions. Such a mechanism could have a significant impact on a wide range of emerging technologies. The component of the chiral velocity that is odd in H is found to be proportional to the intrinsic orbital and spin angular momentum of the magnetized electrons. This effect arises because a ferromagnetic particle responds to the applied torque as a small gyroscope. © 2012 American Physical Society.

Plasma–surface interactions at nanoscales : a combinatorial theoretical, process diagnostics and surface microanalysis approach

This paper introduces an integral approach to the study of plasma-surface interactions during the catalytic growth of selected nanostructures (NSs). This approach involves basic understanding of the plasma-specific effects in NS nucleation and growth, theoretical modelling, numerical simulations, plasma diagnostics, and surface microanalysis. Using an example of plasma-assisted growth of surface-supported single-walled carbon nanotubes, we discuss how the combination of these techniques may help improve the outcomes of the growth process. A specific focus here is on the effects of nanoscale plasma-surface interactions on the NS growth and how the available techniques may be used, both in situ and ex situ to optimize the growth process and structural parameters of NSs.

Defects induced ferromagnetism in plasma-enabled graphene nanopetals

Ferromagnetism in graphene is fascinating, but it is still a big challenge for practical applications due to the weak magnetization. In order to enhance the magnetization, here, we design plasma-enabled graphene nanopetals with ultra-long defective edges of up to 105 m/g, ultra-dense lattice vacancies, and hydrogen chemisorptions. The designed graphene nanopetals display robust ferromagnetism with large saturation magnetization of up to 2 emu/g at 5 K and 1.2 emu/g at room temperatures. This work identifies the plasma-enabled graphene nanopetals as a promising candidate for graphene-based magnetic devices.

Crystalline Si nanoparticles below crystallization threshold : effects of collisional heating in non-thermal atmospheric-pressure microplasmas

Nucleation and growth of highly crystalline silicon nanoparticles in atmospheric-pressure low-temperature microplasmas at gas temperatures well below the Si crystallization threshold and within a short (100 μs) period of time are demonstrated and explained. The modeling reveals that collision-enhanced ion fluxes can effectively increase the heat flux on the nanoparticle surface and this heating is controlled by the ion density. It is shown that nanoparticles can be heated to temperatures above the crystallization threshold. These combined experimental and theoretical results confirm the effective heating and structure control of Si nanoparticles at atmospheric pressure and low gas temperatures.