A density functional theory study of CO2 and N2 adsorption on aluminium nitride single walled nanotubes

Strong binding of isolated carbon dioxide (CO2) on aluminium nitride (AlN) single walled nanotubes is verified using two different functionals. Two optimized configurations corresponding to physisorption and chemisorption are linked by a low energy barrier, such that the chemisorbed state is accessible and thermodynamically favored at low temperatures. In contrast, N2 is found only to form a physisorbed complex with the AlN nanotube, suggesting the potential application of aluminium nitride based materials for CO2 fixation. The effect of nanotube diameter on gas adsorption properties is also discussed. The diameter is found to have an important effect on the chemisorption of CO2, but has little effect on the physisorption of either CO2 or N2.

Adsorption of carbon dioxide and nitrogen on single-layer aluminum nitride nanostructures studied by density functional theory

The adsorption of carbon dioxide and nitrogen molecules on aluminum nitride (AlN) nanostructures has been explored using first-principle computational methods. Optimized configurations corresponding to physisorption and, subsequentially, chemisorption of CO2 are identified, in contrast to N2, for which only a physisorption structure is found. Transition-state searches imply a low energy barrier between the physisorption and chemisorption states for CO2 such that the latter is accessible and thermodynamically favored at room temperature. The effective binding energy of the optimized chemisorption structure is apparently larger than those for other CO2 adsorptive materials, suggesting the potential for application of aluminum nitride nanostructures for carbon dioxide capture and storage.

The effect of Fe doping on adsorption of CO2/N2within carbon nanotubes : a density functional theory study with dispersion corrections

An ab initio density functional theory (DFT) study with correction for dispersive interactions was performed to study the adsorption of N2 and CO2 inside an (8, 8) single-walled carbon nanotube. We find that the approach of combining DFT and van der Waals correction is very effective for describing the long-range interaction between N2/CO2 and the carbon nanotube (CNT). Surprisingly, exohedral doping of an Fe atom onto the CNT surface will only affect the adsorption energy of the quadrupolar CO2 molecule inside the CNT (20–30%), and not that of molecular N2. Our results suggest the feasibility of enhancement of CO2/N2 separation in CNT-based membranes by using exohedral doping of metal atoms.

The catalytic role of an isolated-Ti atom in the hydrogenation of Ti-doped Al(001) surface : An ab initio density functional theory calculation

Recent work [S. Chaudhuri, J.T. Muckerman, J. Phys. Chem. B 109 (2005) 6952] reported that two Ti-substituted atoms on an Al(0 0 1) surface can form a catalytically active site for the dissociation of H2, but the diffusion barrier of atomic H away from Ti site is as high as 1.57 eV. By using ab initio density functional calculations, we found that two hydrogen molecules can dissociate on isolated-Ti atom doped Al(0 0 1) surface with small activation barriers (0.21 and 0.235 eV for first and second H2, respectively). Additionally, the diffusion barrier of atomic H away from Ti site is also moderate (0.47 eV). These results contribute further towards understanding the improved kinetics observed in recycling of hydrogen with Ti-doped NaAlH4.

Van der Waals-corrected density functional theory : benchmarking for hydrogen–nanotube and nanotube–nanotube interactions

Density functional theory (DFT) is a powerful approach to electronic structure calculations in extended systems, but suffers currently from inadequate incorporation of long-range dispersion, or Van der Waals (VdW) interactions. VdW-corrected DFT is tested for interactions involving molecular hydrogen, graphite, single-walled carbon nanotubes (SWCNTs), and SWCNT bundles. The energy correction, based on an empirical London dispersion term with a damping function at short range, allows a reasonable physisorption energy and equilibrium distance to be obtained for H2 on a model graphite surface. The VdW-corrected DFT calculation for an (8, 8) nanotube bundle reproduces accurately the experimental lattice constant. For H2 inside or outside an (8, 8) SWCNT, we find the binding energies are respectively higher and lower than that on a graphite surface, correctly predicting the well known curvature effect. We conclude that the VdW correction is a very effective method for implementing DFT calculations, allowing a reliable description of both short-range chemical bonding and long-range dispersive interactions. The method will find powerful applications in areas of SWCNT research where empirical potential functions either have not been developed, or do not capture the necessary range of both dispersion and bonding interactions.

BWW ontology as a lens on IS design theory: Extending the design science research roadmap

The Design Science Research Roadmap (DSR-Roadmap) [1] aims to give detailed methodological guidance to novice researchers in Information Systems (IS) DSR. Focus group evaluation, one phase of the overall study, of the evolving DSR-Roadmap revealed that a key difficulty faced by both novice and expert researchers in DSR, is abstracting design theory from design. This paper explores the extension of the DSR-Roadmap by employing IS deep structure ontology (BWW [2-4]) as a lens on IS design to firstly yield generalisable design theory, specifically 'IS Design Theory' (ISDT) elements [5]. Consideration is next given to the value of BWW in the application of the design theory by practitioners. Results of mapping BWW constructs to ISDT elements suggest that the BWW is promising as a common language between design researchers and practitioners, facilitating both design theory and design implementation

Indigenous/digital heterogeneities : an actor-network-theory approach

This thesis analysed the theoretical and ontological issues of previous scholarship concerning information technology and indigenous people. As an alternative, the thesis used the framework of actor-network-theory, especially through historiographical and ethnographic techniques. The thesis revealed an assemblage of indigenous/digital enactments striving for relevance and avoiding obsolescence. It also recognised heterogeneities- including user-ambivalences, oscillations, noise, non-coherences and disruptions - as part of the milieu of the daily digital lives of indigenous people. By taking heterogeneities into account, the thesis ensured that the data “speaks for itself” and that social inquiry is not overtaken by ideology and ontology.

Matrix metalloproteinase biosensor based on a porous silicon reflector

Matrix metalloproteinases (MMPs) are proteolytic enzymes important to wound healing. In non-healing wounds, it has been suggested that MMP levels become dysfunctional, hence it is of great interest to develop sensors to detect MMP biomarkers. This study presents the development of a label-free optical MMP biosensor based on a functionalised porous silicon (pSi) thin film. The biosensor is fabricated by immobilising a peptidomimetic MMP inhibitor in the porous layer using hydrosilylation followed by amide coupling. The binding of MMP to the immobilised inhibitor translates into a change of effective optical thickness (EOT) over the time. We investigate the effect of surface functionalisation on the stability of pSi surface and evaluate the sensing performance. We successfully demonstrate MMP detection in buffer solution and human wound fluid at physiologically relevant concentrations. This biosensor may find application as a point-of-care device that is prognostic of the healing trajectory of chronic wounds.

Development of a large scale flexible LED display matrix for the screen industry

This project addresses the viability of lightweight, low power consumption, flexible, large format LED screens. The investigation encompasses all aspects of the electrical and mechanical design, individually and as a system, and achieves a successful full scale prototype. The prototype implements novel techniques to achieve large displacement colour aliasing, a purely passive thermal management solution, a rapid deployment system, individual seven bit LED current control with two way display communication, auto-configuration and complete signal redundancy, all of which are in direct response to industry needs.

Segmentation of cone-beam CT using a hidden Markov random field with informative priors

Purpose: Flat-detector, cone-beam computed tomography (CBCT) has enormous potential to improve the accuracy of treatment delivery in image-guided radiotherapy (IGRT). To assist radiotherapists in interpreting these images, we use a Bayesian statistical model to label each voxel according to its tissue type. Methods: The rich sources of prior information in IGRT are incorporated into a hidden Markov random field (MRF) model of the 3D image lattice. Tissue densities in the reference CT scan are estimated using inverse regression and then rescaled to approximate the corresponding CBCT intensity values. The treatment planning contours are combined with published studies of physiological variability to produce a spatial prior distribution for changes in the size, shape and position of the tumour volume and organs at risk (OAR). The voxel labels are estimated using the iterated conditional modes (ICM) algorithm. Results: The accuracy of the method has been evaluated using 27 CBCT scans of an electron density phantom (CIRS, Inc. model 062). The mean voxel-wise misclassification rate was 6.2%, with Dice similarity coefficient of 0.73 for liver, muscle, breast and adipose tissue. Conclusions: By incorporating prior information, we are able to successfully segment CBCT images. This could be a viable approach for automated, online image analysis in radiotherapy.

Social influences and the physical activity intentions of parents of young-children families: An extended Theory of Planned Behavior Approach

Evidence within Australia and internationally suggests parenthood as a risk factor for inactivity; however, research into understanding parental physical activity is scarce. Given that active parents can create active families and social factors are important for parents’ decision making, the authors investigated a range of social influences on parents’ intentions to be physically active. Parents (N = 580; 288 mothers and 292 fathers) of children younger than 5 years completed an extended Theory of Planned Behavior questionnaire either online or paper based. For both genders, attitude, control factors, group norms, friend general support, and an active parent identity predicted intentions, with social pressure and family support further predicting mothers’ intentions and active others further predicting fathers’ intentions. Attention to these factors and those specific to the genders may improve parents’ intentions to be physically active, thus maximizing the benefits to their own health and the healthy lifestyle practices for other family members.

Predicting the retention of first-time donors using an extended Theory of Planned Behavior

BACKGROUND: Donor retention is vital to blood collection agencies. Past research has highlighted the importance of early career behavior for long-term donor retention, yet research investigating the determinants of early donor behavior is scarce. Using an extended Theory of Planned Behavior (TPB), this study sought to identify the predictors of first-time blood donors' early career retention. STUDY DESIGN AND METHODS: First-time donors (n = 256) completed three surveys on blood donation. The standard TPB predictors and self-identity as a donor were assessed 3 weeks (Time 1) and at 4 months (Time 2) after an initial donation. Path analyses examined the utility of the extended TPB to predict redonation at 4 and 8 months after initial donation. RESULTS: The extended TPB provided a good fit to the data. Post-Time 1 and 2 behavior was consistently predicted by intention to redonate. Further, intention was predicted by attitudes, perceived control, and self-identity (Times 1 and 2). Donors' intentions to redonate at Time 1 were the strongest predictor of intention to donate at Time 2, while donors' behavior at Time 1 strengthened self-identity as a blood donor at Time 2. CONCLUSION: An extended TPB framework proved efficacious in revealing the determinants of first-time donor retention in an initial 8-month period. The results suggest that collection agencies should intervene to bolster donors' attitudes, perceived control, and identity as a donor during this crucial post–first donation period.

Random Breath Testing in Australia: Is there an Optimum Level of Intensity?

Background: Random Breath Testing (RBT) is the main drink driving law enforcement tool used throughout Australia. International comparative research considers Australia to have the most successful RBT program compared to other countries in terms of crash reductions (Erke, Goldenbeld, & Vaa, 2009). This success is attributed to the programs high intensity (Erke et al., 2009). Our review of the extant literature suggests that there is no research evidence that indicates an optimal level of alcohol breath testing. That is, we suggest that no research exists to guide policy regarding whether or not there is a point at which alcohol related crashes reach a point of diminishing returns as a result of either saturated or targeted RBT testing. Aims: In this paper we first provide an examination of RBTs and alcohol related crashes across Australian jurisdictions. We then address the question of whether or not an optimal level of random breath testing exists by examining the relationship between the number of RBTs conducted and the occurrence of alcohol-related crashes over time, across all Australian states. Method: To examine the association between RBT rates and alcohol related crashes and to assess whether an optimal ratio of RBT tests per licenced drivers can be determined we draw on three administrative data sources form each jurisdiction. Where possible data collected spans January 1st 2000 to September 30th 2012. The RBT administrative dataset includes the number of Random Breath Tests (RBTs) conducted per month. The traffic crash administrative dataset contains aggregated monthly count of the number of traffic crashes where an individual’s recorded BAC reaches or exceeds 0.05g/ml of alcohol in blood. The licenced driver data were the monthly number of registered licenced drivers spanning January 2000 to December 2011. Results: The data highlights that the Australian story does not reflective of all States and territories. The stable RBT to licenced driver ratio in Queensland (of 1:1) suggests a stable rate of alcohol related crash data of 5.5 per 100,000 licenced drivers. Yet, in South Australia were a relative stable rate of RBT to licenced driver ratio of 1:2 is maintained the rate of alcohol related traffic crashes is substantially less at 3.7 per 100,000. We use joinpoint regression techniques and varying regression models to fit the data and compare the different patterns between jurisdictions. Discussion: The results of this study provide an updated review and evaluation of RBTs conducted in Australia and examines the association between RBTs and alcohol related traffic crashes. We also present an evidence base to guide policy decisions for RBT operations.