Numerical analysis of shape transition in graphene nanoribbons

Graphene nanoribbon (GNR) with free edges can exhibit non-flat morphologies due to pre-existing edge stress. Using molecular dynamics (MD) simulations, we investigate the free-edge effect on the shape transition in GNRs with different edge types, including regular (armchair and zigzag), armchair terminated with hydrogen and reconstructed armchair. The results show that initial edge stress and energy are dependent on the edge configurations. It is confirmed that pre-strain on the free edges is a possible way to limit the random shape transition of GNRs. In addition, the influence of surface attachment on the shape transition is also investigated in this work. It is found that surface attachment can lead to periodic ripples in GNRs, dependent on the initial edge configurations.

Breast cancer detection from thermal images using bispectral invariant features

Highly sensitive infrared (IR) cameras provide high-resolution diagnostic images of the temperature and vascular changes of breasts. These images can be processed to emphasize hot spots that exhibit early and subtle changes owing to pathology. The resulting images show clusters that appear random in shape and spatial distribution but carry class dependent information in shape and texture. Automated pattern recognition techniques are challenged because of changes in location, size and orientation of these clusters. Higher order spectral invariant features provide robustness to such transformations and are suited for texture and shape dependent information extraction from noisy images. In this work, the effectiveness of bispectral invariant features in diagnostic classification of breast thermal images into malignant, benign and normal classes is evaluated and a phase-only variant of these features is proposed. High resolution IR images of breasts, captured with measuring accuracy of ±0.4% (full scale) and temperature resolution of 0.1 °C black body, depicting malignant, benign and normal pathologies are used in this study. Breast images are registered using their lower boundaries, automatically extracted using landmark points whose locations are learned during training. Boundaries are extracted using Canny edge detection and elimination of inner edges. Breast images are then segmented using fuzzy c-means clustering and the hottest regions are selected for feature extraction. Bispectral invariant features are extracted from Radon projections of these images. An Adaboost classifier is used to select and fuse the best features during training and then classify unseen test images into malignant, benign and normal classes. A data set comprising 9 malignant, 12 benign and 11 normal cases is used for evaluation of performance. Malignant cases are detected with 95% accuracy. A variant of the features using the normalized bispectrum, which discards all magnitude information, is shown to perform better for classification between benign and normal cases, with 83% accuracy compared to 66% for the original.

Molecular dynamics simulation of fracture strength and morphology of defective graphene

Different types of defects can be introduced into graphene during material synthesis, and significantly influence the properties of graphene. In this work, we investigated the effects of structural defects, edge functionalisation and reconstruction on the fracture strength and morphology of graphene by molecular dynamics simulations. The minimum energy path analysis was conducted to investigate the formation of Stone-Wales defects. We also employed out-of-plane perturbation and energy minimization principle to study the possi-ble morphology of graphene nanoribbons with edge-termination. Our numerical results show that the fracture strength of graphene is dependent on defects and environmental temperature. However, pre-existing defects may be healed, resulting in strength recovery. Edge functionalization can induce compressive stress and ripples in the edge areas of gra-phene nanoribbons. On the other hand, edge reconstruction contributed to the tensile stress and curved shape in the graphene nanoribbons.

Complexity of increasing the secure connectivity in wireless ad hoc networks

We consider the problem of maximizing the secure connectivity in wireless ad hoc networks, and analyze complexity of the post-deployment key establishment process constrained by physical layer properties such as connectivity, energy consumption and interference. Two approaches, based on graph augmentation problems with nonlinear edge costs, are formulated. The first one is based on establishing a secret key using only the links that are already secured by shared keys. This problem is in NP-hard and does not accept polynomial time approximation scheme PTAS since minimum cutsets to be augmented do not admit constant costs. The second one extends the first problem by increasing the power level between a pair of nodes that has a secret key to enable them physically connect. This problem can be formulated as the optimal key establishment problem with interference constraints with bi-objectives: (i) maximizing the concurrent key establishment flow, (ii) minimizing the cost. We prove that both problems are NP-hard and MAX-SNP with a reduction to MAX3SAT problem.

Fluid Infrastructure : A response to a natural flood disaster in Brisbane

Fluid Infrastructure: Landscape Architecture Exhibition: This exhibition showcases the work of 4th Year undergraduate landscape architecture students in response to the 2011 Queensland floods through five installations: Systima Fluid Flux Flex Fluid Connectivity The Floods Verge Fluid Evolution The focus of these installations is the post-flood conditions of Brisbane’s riverside public infrastructure, within a scenario of flood as a normalised event. It recognises that within this scenario, parts of this city cannot be described as definitively ‘land’ or ‘water,’ but are best described as ‘fluid terrains’(Mathur, A. and Da Cunha, D. 2006). The landscape design propositions within the five installations include public transport diversification (RiverRats) schemes, greenspace elevations, ephemeral gardens and evolving landscapes, creative interpretation and warning devices and systems. These propositions do not resist fluid conditions, but work with them to propose a more resilient urban river landscape than Brisbane currently has. This QUT exhibition was developed as part of the 2011 Flood of Ideas Project (http://www.floodofideas.org.au) in partnership with Healthy Waterways (Water by Design), State Library of Queensland (The Edge), Brisbane City Council, Australian Institute of Architects, University of Queensland, Green Cross Australia, Stormwater Industry Association.

Robust aerodynamic design optimisation of morphing aerofoil/wing using distributed moga

In this paper, the shape design optimisation using morphing aerofoil/wing techniques, namely the leading and/or trailing edge deformation of a natural laminar flow RAE 5243 aerofoil is investigated to reduce transonic drag without taking into account of the piezo actuator mechanism. Two applications using a Multi-Objective Genetic Algorithm (MOGA)coupled with Euler and boundary analyser (MSES) are considered: the first example minimises the total drag with a lift constraint by optimising both the trailing edge actuator position and trailing edge deformation angle at a constant transonic Mach number (M! = 0.75)and boundary layer transition position (xtr = 45%c). The second example consists of finding reliable designs that produce lower mean total drag (μCd) and drag sensitivity ("Cd) at different uncertainty flight conditions based on statistical information. Numerical results illustrate how the solution quality in terms of mean drag and its sensitivity can be improved using MOGA software coupled with a robust design approach taking account of uncertainties (lift and boundary transition positions) and also how transonic flow over aerofoil/wing can be controlled to the best advantage using morphing techniques.

How to achieve maximum charge carrier loading on heteroatom-substituted graphene nanoribbon edges: density functional theory study

The practical number of charge carriers loaded is crucial to the evaluation of the capacity performance of carbon-based electrodes in service, and cannot be easily addressed experimentally. In this paper, we report a density functional theory study of charge carrier adsorption onto zigzag edge-shaped graphene nanoribbons (ZGNRs), both pristine and incorporating edge substitution with boron, nitrogen or oxygen atoms. All edge substitutions are found to be energetically favorable, especially in oxidized environments. The maximal loading of protons onto the substituted ZGNR edges obeys a rule of [8-n-1], where n is the number of valence electrons of the edge-site atom constituting the adsorption site. Hence, a maximum charge loading is achieved with boron substitution. This result correlates in a transparent manner with the electronic structure characteristics of the edge atom. The boron edge atom, characterized by the most empty p band, facilitates more than the other substitutional cases the accommodation of valence electrons transferred from the ribbon, induced by adsorption of protons. This result not only further confirms the possibility of enhancing charge storage performance of carbon-based electrochemical devices through chemical functionalization but also, more importantly, provides the physical rationale for further design strategies.

Charge carrier exchange at chemically modified graphene edges: A density functional theory study

Heteroatom doping on the edge of graphene may serve as an effective way to tune chemical activity of carbon-based electrodes with respect to charge carrier transfer in an aqueous environment. In a step towards developing mechanistic understanding of this phenomenon, we explore herein mechanisms of proton transfer from aqueous solution to pristine and doped graphene edges utilizing density functional theory. Atomic B-, N-, and O- doped edges as well as the native graphene are examined, displaying varying proton affinities and effective interaction ranges with the H3O+ charge carrier. Our study shows that the doped edges characterized by more dispersive orbitals, namely boron and nitrogen, demonstrate more energetically favourable charge carrier exchange compared with oxygen, which features more localized orbitals. Extended calculations are carried out to examine proton transfer from the hydronium ion in the presence of explicit water, with results indicating that the basic mechanistic features of the simpler model are unchanged.

Desalination by a solar thermally driven distillation process

Desalination processes to remove dissolved salts from seawater or brackish water includes common industrial scale processes such as reverse osmosis, thermal processes (i.e. multi-stage flash, multiple-effect distillation) and mechanical vapour compression. These processes are very energy intensive. The Institute for Future Environments (IFE) has evaluated various alternative processes to accomplish desalination using renewable or sustainable energy sources. A new process - a solar, thermally driven distillation system . based on the principles of a solar still – has been examined. This work presents an initial evaluation of the process.

A multi-layered approach for site detection in UAS emergency landing scenarios using geometry-based image segmentation

This paper presents an alternative approach to image segmentation by using the spatial distribution of edge pixels as opposed to pixel intensities. The segmentation is achieved by a multi-layered approach and is intended to find suitable landing areas for an aircraft emergency landing. We combine standard techniques (edge detectors) with novel developed algorithms (line expansion and geometry test) to design an original segmentation algorithm. Our approach removes the dependency on environmental factors that traditionally influence lighting conditions, which in turn have negative impact on pixel-based segmentation techniques. We present test outcomes on realistic visual data collected from an aircraft, reporting on preliminary feedback about the performance of the detection. We demonstrate consistent performances over 97% detection rate.

Sustainable knowledge community precincts : lessons from global best practices

In the era of global knowledge economy, urban regions—seeking to increase their competitive edge, become destinations for talent and investment, and provide prosperity and quality of life to their inhabitants—have little chance achieving their development goals without forming effective knowledge-based urban development (KBUD) strategies. KBUD paradigm suggests that the economic future of cities increasingly depends on the capacity to attract, generate, retain and foster creativity, knowledge and innovation—and make space and place for knowledge generation and knowledge communities. Thus, the paper aims to shed light on the planning and development processes of the KBUD phenomenon with respect to the construction of sustainable knowledge community precincts (KCPs) aimed at making space for knowledge generation and place for knowledge communities—and provide useful lessons for the developing country cities seeking such sustainable and KBUD.

Building contemporary urban spaces of knowledge and innovation : Lessons from Australian practice

In the era of global knowledge economy, urban regions that are seeking to increase their competitive edge, become destinations for talent and investment, and provide prosperity and quality of life to their inhabitants have little chance achieving their development goals without forming effective knowledge-based urban development strategies. This paper aims to shed light on the planning and development of the knowledge-based urban development phenomenon with respect to the construction of knowledge community precincts aimed at building contemporary urban spaces of knowledge and innovation. Following to a thorough review of the literature on knowledge-based urban development, the paper undertakes policy and best practice analyses to learn from the internationally renowned Australian knowledge community precincts, from Sydney, Melbourne and Brisbane, to better understand the dynamics of knowledge community precinct development practices. The paper provides a discussion on the study findings and recommendations for successfully establishing contemporary urban spaces of knowledge and innovation.

Development of optimal designs of insulated rail joints

Proper functioning of Insulated Rail Joints (IRJs) is essential for the safe operation of the railway signalling systems and broken rail identification circuitries. The Conventional IRJ (CIRJ) resembles structural butt joints consisting of two pieces of rails connected together through two joint bars on either side of their web and the assembly is held together through pre-tensioned bolts. As the IRJs should maintain electrical insulation between the two rails, a gap between the rail ends must be retained at all times and all metal contacting surfaces should be electrically isolated from each other using non-conductive material. At the gap, the rail ends lose longitudinal continuity and hence the vertical sections of the rail ends are often severely damaged, especially at the railhead, due to the passage of wheels compared to other continuously welded rail sections. Fundamentally, the reason for the severe damage can be related to the singularities of the wheel-rail contact pressure and the railhead stress. No new generation designs that have emerged in the market to date have focussed on this fundamental; they only have provided attention to either the higher strength materials or the thickness of the sections of various components of the IRJs. In this thesis a novel method of shape optimisation of the railhead is developed to eliminate the pressure and stress singularities through changes to the original sharp corner shaped railhead into an arc profile in the longitudinal direction. The optimal shape of the longitudinal railhead profile has been determined using three nongradient methods in search of accuracy and efficiency: (1) Grid Search Method; (2) Genetic Algorithm Method and (3) Hybrid Genetic Algorithm Method. All these methods have been coupled with a parametric finite element formulation for the evaluation of the objective function for each iteration or generation depending on the search algorithm employed. The optimal shape derived from these optimisation methods is termed as Stress Minimised Railhead (SMRH) in this thesis. This optimal SMRH design has exhibited significantly reduced stress concentration that remains well below the yield strength of the head hardened rail steels and has shifted the stress concentration location away from the critical zone of the railhead end. The reduction in the magnitude and the relocation of the stress concentration in the SMRH design has been validated through a full scale wheel – railhead interaction test rig; Railhead strains under the loaded wheels have been recorded using a non-contact digital image correlation method. Experimental study has confirmed the accuracy of the numerical predications. Although the SMRH shaped IRJs eliminate stress singularities, they can still fail due to joint bar or bolt hole cracking; therefore, another conceptual design, termed as Embedded IRJ (EIRJ) in this thesis, with no joint bars and pre-tensioned bolts has been developed using a multi-objective optimisation formulation based on the coupled genetic algorithm – parametric finite element method. To achieve the required structural stiffness for the safe passage of the loaded wheels, the rails were embedded into the concrete of the post tensioned sleepers; the optimal solutions for the design of the EIRJ is shown to simplify the design through the elimination of the complex interactions and failure modes of the various structural components of the CIRJ. The practical applicability of the optimal shapes SMRH and EIRJ is demonstrated through two illustrative examples, termed as improved designs (IMD1 & IMD2) in this thesis; IMD1 is a combination of the CIRJ and the SMRH designs, whilst IMD2 is a combination of the EIRJ and SMRH designs. These two improved designs have been simulated for two key operating (speed and wagon load) and design (wheel diameter) parameters that affect the wheel-rail contact; the effect of these parameters has been found to be negligible to the performance of the two improved designs and the improved designs are in turn found far superior to the current designs of the CIRJs in terms of stress singularities and deformation under the passage of the loaded wheels. Therefore, these improved designs are expected to provide longer service life in relation to the CIRJs.

First principle studies of zigzag AlN nanoribbon

Ab initio density functional calculations were performed to study the geometry and electronic structure of a prototypical zigzag AlN nanoribbon. We find that H-terminated zigzag 10-AlN nanoribbons have a non-direct band gap and are nonmagnetic. When a transverse electric field is applied, the band gap decreases monotonically with the strength of field E. Zigzag AlN nanoribbons with the N edge unpassivated display strong spin-polarization close to the Fermi level, which will result in spin-anisotropic transport. These results suggest potential applications for the development of AlN nanoribbon-based nanoelectronics applications.

First-principle studies of electronic structure and C-doping effect in boron nitride nanoribbon

Structural and electronic properties have been studied for Boron Nitride nanoribbons (BNNR) with both zigzag and armchair shaped edge (Z-BNNR and A-BNNR) by first-principle spin-polarized total energy calculations. We found that the energy band gap of Z-BNNR is indirect and decreases monotonically with the increasing ribbon width, whereas direct energy band gap oscillation was observed for A-BNNRs. Additionally, C-substitution at either single boron or nitrogen atom site in BNNRs could induce spontaneous magnetization. Our results could be potentially useful to design magnetic nano-devices based on BNNRs.