Molecular recognition of 2,4,6-trinitrotoluene by 6-aminohexanethiol and surface-enhanced Raman scattering sensor

2,4,6-trinitrotoluene (TNT) is one of the most commonly used nitro aromatic explosives in landmine, military and mining industry. This article demonstrates rapid and selective identification of TNT by surface-enhanced Raman spectroscopy (SERS) using 6-aminohexanethiol (AHT) as a new recognition molecule. First, Meisenheimer complex formation between AHT and TNT is confirmed by the development of pink colour and appearance of new band around 500 nm in UV-visible spectrum. Solution Raman spectroscopy study also supported the AHT:TNT complex formation by demonstrating changes in the vibrational stretching of AHT molecule between 2800-3000 cm−1. For surface enhanced Raman spectroscopy analysis, a self-assembled monolayer (SAM) of AHT is formed over the gold nanostructure (AuNS) SERS substrate in order to selectively capture TNT onto the surface. Electrochemical desorption and X-ray photoelectron studies are performed over AHT SAM modified surface to examine the presence of free amine groups with appropriate orientation for complex formation. Further, AHT and butanethiol (BT) mixed monolayer system is explored to improve the AHT:TNT complex formation efficiency. Using a 9:1 AHT:BT mixed monolayer, a very low detection limit (LOD) of 100 fM TNT was realized. The new method delivers high selectivity towards TNT over 2,4 DNT and picric acid. Finally, real sample analysis is demonstrated by the extraction and SERS detection of 302 pM of TNT from spiked.

Impacts of sodic soil amelioration on hydraulic conductivity and deep drainage in the Lower Burdekin

An understanding of the influence of soil chemistry on soil hydraulic properties is of critical importance for the management of sodic soils under irrigation. The hydraulic conductivity of sodic soils has been shown to be affected by properties of the applied solution including pH (Suarez et al. 1984), sodicity and salt concentration (McNeal and Coleman 1966). The changes in soil hydraulic conductivity are the result of changes in the spacing between clay layers in response to changes in soil solution chemistry. While the importance o f soil chemistry in controlling hydraulic conductivity is known, the exact impacts of sodic soil amelioration on hydraulic conductivity and deep drainage at a given location are difficult to predict. This is because the relationships between soil chemical factors and hydraulic conductivity are soil specific and because local site specific factors also need to be considered to determine the actual impacts on deep drainage rates.

Improving deep convultional neural networks with unsupervised feature learning

The latest generation of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object classification, achieving state-of-the-art performance in several computer vision tasks including text recognition, sign recognition, face recognition and scene understanding. The depth of these supervised networks has enabled learning deeper and hierarchical representation of features. In parallel, unsupervised deep learning such as Convolutional Deep Belief Network (CDBN) has also achieved state-of-the-art in many computer vision tasks. However, there is very limited research on jointly exploiting the strength of these two approaches. In this paper, we investigate the learning capability of both methods. We compare the output of individual layers and show that many learnt filters and outputs of the corresponding level layer are almost similar for both approaches. Stacking the DCNN on top of unsupervised layers or replacing layers in the DCNN with the corresponding learnt layers in the CDBN can improve the recognition/classification accuracy and training computational expense. We demonstrate the validity of the proposal on ImageNet dataset.

Graphene quantum dots and the resonance light scattering technique for trace analysis of phenol in different water samples

A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10−8–2.16×10−6 M and 2.40×10−6–2.88×10−5 M with a detection limit of 2.20×10−8 M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.

SERS-barcoded colloidal gold NP assemblies as imaging agents for use in biodiagnostics

There is a growing need for new biodiagnostics that combine high throughput with enhanced spatial resolution and sensitivity. Gold nanoparticle (NP) assemblies with sub-10 nm particle spacing have the benefits of improving detection sensitivity via Surface enhanced Raman scattering (SERS) and being of potential use in biomedicine due to their colloidal stability. A promising and versatile approach to form solution-stable NP assemblies involves the use of multi-branched molecular linkers which allows tailoring of the assembly size, hot-spot density and interparticle distance. We have shown that linkers with multiple anchoring end-groups can be successfully employed as a linker to assemble gold NPs into dimers, linear NP chains and clustered NP assemblies. These NP assemblies with diameters of 30-120 nm are stable in solution and perform better as SERS substrates compared with single gold NPs, due to an increased hot-spot density. Thus, tailored gold NP assemblies are potential candidates for use as biomedical imaging agents. We observed that the hot-spot density and in-turn the SERS enhancement is a function of the linker polymer concentration and polymer architecture. New deep Raman techniques like Spatially Offset Raman Spectroscopy (SORS) have emerged that allow detection from beneath diffusely scattering opaque materials, including biological media such as animal tissue. We have been able to demonstrate that the gold NP assemblies could be detected from within both proteinaceous and high lipid containing animal tissue by employing a SORS technique with a backscattered geometry.

Significant deterioration in nanomechanical quality occurs through incomplete extrafibrillar mineralization in rachitic bone: Evidence from in-situ synchrotron X-ray scattering and backscattered electron imaging

Bone diseases such as rickets and osteoporosis cause significant reduction in bone quantity and quality, which leads to mechanical abnormalities. However, the precise ultrastructural mechanism by which altered bone quality affects mechanical properties is not clearly understood. Here we demonstrate the functional link between altered bone quality (reduced mineralization) and abnormal fibrillar-level mechanics using a novel, real-time synchrotron X-ray nanomechanical imaging method to study a mouse model with rickets due to reduced extrafibrillar mineralization. A previously unreported N-ethyl-N-nitrosourea (ENU) mouse model for hypophosphatemic rickets (Hpr), as a result of missense Trp314Arg mutation of the phosphate regulating gene with homologies to endopeptidase on the X chromosome (Phex) and with features consistent with X-linked hypophosphatemic rickets (XLHR) in man, was investigated using in situ synchrotron small angle X-ray scattering to measure real-time changes in axial periodicity of the nanoscale mineralized fibrils in bone during tensile loading. These determine nanomechanical parameters including fibril elastic modulus and maximum fibril strain. Mineral content was estimated using backscattered electron imaging. A significant reduction of effective fibril modulus and enhancement of maximum fibril strain was found in Hpr mice. Effective fibril modulus and maximum fibril strain in the elastic region increased consistently with age in Hpr and wild-type mice. However, the mean mineral content was ∼21% lower in Hpr mice and was more heterogeneous in its distribution. Our results are consistent with a nanostructural mechanism in which incompletely mineralized fibrils show greater extensibility and lower stiffness, leading to macroscopic outcomes such as greater bone flexibility. Our study demonstrates the value of in situ X-ray nanomechanical imaging in linking the alterations in bone nanostructure to nanoscale mechanical deterioration in a metabolic bone disease. Copyright

Automating marine mammal detection in aerial images captured during wildlife surveys: A deep learning approach

Aerial surveys conducted using manned or unmanned aircraft with customized camera payloads can generate a large number of images. Manual review of these images to extract data is prohibitive in terms of time and financial resources, thus providing strong incentive to automate this process using computer vision systems. There are potential applications for these automated systems in areas such as surveillance and monitoring, precision agriculture, law enforcement, asset inspection, and wildlife assessment. In this paper, we present an efficient machine learning system for automating the detection of marine species in aerial imagery. The effectiveness of our approach can be credited to the combination of a well-suited region proposal method and the use of Deep Convolutional Neural Networks (DCNNs). In comparison to previous algorithms designed for the same purpose, we have been able to dramatically improve recall to more than 80% and improve precision to 27% by using DCNNs as the core approach.

Scattering of electromagnetic waves from chirally coated cylinders

The problem of electromagnetic scattering from an isotropic homogeneous chirally coated conducting cylinder is analysed. The cylinder is assumed to be illuminated by either a transverse magnetic or a transverse electric wave. Mie's analysis is used to evaluate the scattering characteristics. The computed results include the evaluation of the normalized scattering width and the absorption efficiency. The results show that there is a significant reduction in the normalized scattering width as compared to a RAM coated cylinder. This reduction has been attributed to increased absorption.

Small-angle neutron scattering study of micellar structures of dimeric surfactants

Dimeric or gemini surfactants consist of two hydrophobic chains and two hydrophilic head groups co; valently connected by a hydrocarbon spacer. Small-angle neutron scattering measurements from bis-cationic C16H33N+(CH3)(2)-(CH2)(m)-N+(CH3)(2)C(16)H(33)2Br(-) dimeric surfactants, referred to-as 16-m-16, for different length of hydrocarbon spacers m-3-6, 8, 10, and 12, are reported. The measurements have been carried out at various concentrations: C=2.5 and 10 mM for all m and C=30 and 50 mM for m greater than or equal to 5. It is found that micellar structure depends on the length of the spacer. Micelles are disks for m=3, cylindrical for m=4, and prolate ellipsoidals for other values of m. These structural results are in agreement with the theoretical predictions based on the packing parameter. It has also been observed that conformation of the spacer and the hydrophobic chains in the interior of the micelle change as the length of the spacer is increased. The concentration dependence for m greater than or equal to 5 shows that the effect of surfactant concentration on the size of the micelle is more pronounced for m=5 and 12 than for the intermediate spacers. The fractional charge on the micelle increases with the increase in spacer length and decreases when the concentration is increased.

Design and a deep customer insight approach to innovation

This paper proposes and explores the Deep Customer Insight Innovation Framework in order to develop an understanding as to how design can be integrated within existing innovation processes. The Deep Customer Insight Innovation Framework synthesises the work of Beckman and Barry (2007) as a theoretical foundation, with the framework explored within a case study of Australian Airport Corporation seeking to drive airport innovations in operations and retail performance. The integration of a deep customer insight approach develops customer-centric and highly integrated solutions as a function of concentrated problem exploration and design-led idea generation. Businesses’ facing complex innovation challenges or seeking to making sense of future opportunities will be able to integrate design into existing innovation processes, anchoring the new approach between existing market research and business development activities. This paper contributes a framework and novel understanding as to how design methods are integrated into existing innovation processes for operationalization within industry.

Evidence of clustering in an aqueous electrolyte solution: a small-angle X-ray scattering study

The work reported hen was motivated by a desire to verify the existence of structure - specifically MP-rich clusters induced by sodium bromide (NaBr) in the ternary liquid mixture 3-methylpyridine (Mf) + water(W) + NaBr. We present small-angle X-ray scattering (SAXS) measurements in this mixture. These measurements were obtained at room temperature (similar to 298 K) in the one-phase region (below the relevant lower consolute points, T(L)s) at different values of X (i.e., X = 0.02 - 0.17), where X is the weight fraction of NaBr in the mixture. Cluster-size distribution, estimated on the assumption that the clusters are spherical, shows systematic behaviour in that the peak of the distribution shifts rewards larger values of cluster radius as X increases. The largest spatial extent of the clusters (similar to 4.5 nm) is seen at X = 0.17. Data analysis assuming arbitrary shapes and sizes of clusters gives a limiting value of cluster size (- 4.5 nm) that is not very sensitive to X. It is suggested that the cluster size determined may not be the same as the usual critical-point fluctuations far removed from the critical point (T-L). The influence of the additional length scale due to clustering is discussed from the standpoint of crossover from Ising to mean-field critical behaviour, when moving away from the T-L.

Dynamics of a dilute sheared inelastic fluid. I. Hydrodynamic modes and velocity correlation functions

The hydrodynamic modes and the velocity autocorrelation functions for a dilute sheared inelastic fluid are analyzed using an expansion in the parameter epsilon=(1-e)(1/2), where e is the coefficient of restitution. It is shown that the hydrodynamic modes for a sheared inelastic fluid are very different from those for an elastic fluid in the long-wave limit, since energy is not a conserved variable when the wavelength of perturbations is larger than the ``conduction length.'' In an inelastic fluid under shear, there are three coupled modes, the mass and the momenta in the plane of shear, which have a decay rate proportional to k(2/3) in the limit k -> 0, if the wave vector has a component along the flow direction. When the wave vector is aligned along the gradient-vorticity plane, we find that the scaling of the growth rate is similar to that for an elastic fluid. The Fourier transforms of the velocity autocorrelation functions are calculated for a steady shear flow correct to leading order in an expansion in epsilon. The time dependence of the autocorrelation function in the long-time limit is obtained by estimating the integral of the Fourier transform over wave number space. It is found that the autocorrelation functions for the velocity in the flow and gradient directions decay proportional to t(-5/2) in two dimensions and t(-15/4) in three dimensions. In the vorticity direction, the decay of the autocorrelation function is proportional to t(-3) in two dimensions and t(-7/2) in three dimensions.

Dynamics of a dilute sheared inelastic fluid. II. The effect of correlations

The effect of correlations on the viscosity of a dilute sheared inelastic fluid is analyzed using the ring-kinetic equation for the two-particle correlation function. The leading-order contribution to the stress in an expansion in epsilon=(1-e)(1/2) is calculated, and it is shown that the leading-order viscosity is identical to that obtained from the Green-Kubo formula, provided the stress autocorrelation function in a sheared steady state is used in the Green-Kubo formula. A systemmatic extension of this to higher orders is also formulated, and the higher-order contributions to the stress from the ring-kinetic equation are determined in terms of the terms in the Chapman-Enskog solution for the Boltzmann equation. The series is resummed analytically to obtain a renormalized stress equation. The most dominant contributions to the two-particle correlation function are products of the eigenvectors of the conserved hydrodynamic modes of the two correlated particles. In Part I, it was shown that the long-time tails of the velocity autocorrelation function are not present in a sheared fluid. Using those results, we show that correlations do not cause a divergence in the transport coefficients; the viscosity is not divergent in two dimensions, and the Burnett coefficients are not divergent in three dimensions. The equations for three-particle and higher correlations are analyzed diagrammatically. It is found that the contributions due to the three-particle and higher correlation functions to the renormalized viscosity are smaller than those due to the two-particle distribution function in the limit epsilon -> 0. This implies that the most dominant correlation effects are due to the two-particle correlations.

Fast decay of the velocity autocorrelation function in dense shear flow of inelastic hard spheres

We find in complementary experiments and event-driven simulations of sheared inelastic hard spheres that the velocity autocorrelation function psi(t) decays much faster than t(-3/2) obtained for a fluid of elastic spheres at equilibrium. Particle displacements are measured in experiments inside a gravity-driven flow sheared by a rough wall. The average packing fraction obtained in the experiments is 0.59, and the packing fraction in the simulations is varied between 0.5 and 0.59. The motion is observed to be diffusive over long times except in experiments where there is layering of particles parallel to boundaries, and diffusion is inhibited between layers. Regardless, a rapid decay of psi(t) is observed, indicating that this is a feature of the sheared dissipative fluid, and is independent of the details of the relative particle arrangements. An important implication of our study is that the non-analytic contribution to the shear stress may not be present in a sheared inelastic fluid, leading to a wider range of applicability of kinetic theory approaches to dense granular matter.

Measurement of Partition Coefficients of Substituted Benzoic Acids between Two Immiscible Solvents by Hyper-Rayleigh Scattering

We demonstrate that the hyper-Rayleigh scattering technique can be employed to measure the partition coefficient (k(p)) of a solute in a mixture of two immiscible solvents. Specifically, partition coefficients of six substituted benzoic acids in water/toluene (1:1 v/v) and water/chloroform (1:1 v/v) systems have been measured. Our values compare well with the k(p) values measured earlier by other techniques, The advantages offered by this technique are also discussed.