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.

Multiple Literacies Theory: Discourse, sensation, resonance and becoming

This thematic issue on education and the politics of becoming focuses on how a Multiple Literacies Theory (MLT) plugs into practice in education. MLT does this by creating an assemblage between discourse, text, resonance and sensations. What does this produce? Becoming AND how one might live are the product of an assemblage (May, 2005; Semetsky, 2003). In this paper, MLT is the approach that explores the connection between educational theory and practice through the lens of an empirical study of multilingual children acquiring multiple writing systems simultaneously. The introduction explicates discourse, text, resonance, sensation and becoming. The second section introduces certain Deleuzian concepts that plug into MLT. The third section serves as an introduction to MLT. The fourth section is devoted to the study by way of a rhizoanalysis. Finally, drawing on the concept of the rhizome, this article exits with potential lines of flight opened by MLT. These are becomings which highlight the significance of this work in terms of transforming not only how literacies are conceptualized, especially in minority language contexts, but also how one might live.

A tensor encoding model of word meaning : theory and application to information retrieval

This project was a step forward in developing and evaluating a novel, mathematical model that can deduce the meaning of words based on their use in language. This model can be applied to a wide range of natural language applications, including the information seeking process most of us undertake on a daily basis.

Integrating agency and resource dependence theory : firm profitability, industry regulation, and board task performance

Boards of directors are key governancemechanisms in organizations and fulfill twomain tasks:monitoringmanagers and firm performance, and providing advice and access to resources. In spite of a wealth of researchmuch remains unknown about how boards attend to the two tasks. This study investigates whether organizational (firm profitability) and environmental factors (industry regulation) affect board task performance. The data combine CEOs' responses to a questionnaire, and archival data from a sample of large Italian firms. Findings show that past firm performance is negatively associatedwith board monitoring and advice tasks; greater industry regulation enhances perceived board task performance; board monitoring and advice tasks tend to reinforce each other, despite their theoretical and practical distinction.

A Design Theory for Context-Aware Information Systems

This research studies information systems that adapt to the context in which they are used and provides recommendations on how the design of such systems can be improved. This thesis covers the problem of context-awareness via two case studies in the insurance and transportation industries. The study highlights shortcomings in the understanding of the relationship between information systems and context. Furthermore, it presents a new, theory-informed approach to design, and provides guidance for system developers seeking to implement context-aware information systems.

Implementing the self-management threshold learning outcome in Australian legal curricula : insights from self-determination theory

In 2010, six Threshold Learning Outcomes (TLOs) for law were developed by the Australian Learning and Teaching Council's Discipline Scholars: Law. The final of these outcomes, TLO 6, concerns self-management. This thesis examines strategies for implementing self-management in Australian legal education by first contextualising the development of TLO 6 in light of other relevant national and international developments in higher education, and secondly, analysing this learning outcome through the lens of Self-Determination Theory (SDT), an influential branch of educational psychology. It is argued that the central concept of autonomous self-regulation in SDT provides insights into factors that are relevant to law students’ capacities for long-term self-management, which is reinforced by analysis of the literature on law students’ distress. Accordingly, curriculum design that supports students’ autonomy may simultaneously promote students’ self-management capacities. The discussion of theoretical and practical perspectives on autonomy supportive curriculum design in this thesis thus illuminates potential pedagogical approaches for the implementation of TLO 6 in Australian legal curricula.

Adsorption and dissociation of ammonia borane outside and inside single-walled carbon nanotubes : A density functional theory study

Amonia borane (AB) has been identified as a potential candidate highcapacity hydrogen storage material. This work probes the adsorption and dissociation of AB inside and outside single-walled carbon nanotubes (SWCNTs) within the framework of density functional theory. The dissociation barriers of AB have been calculated and compared with that of the isolated AB molecule. On the basis of the present calculations, no notable improvement results from SWCNT confinement; on the contrary, the dissociation barrier slightly increases with respect to isolated AB.

A density functional theory study on CO2 capture and activation by graphene-like boron nitride with boron vacancy

First principle calculations for a hexagonal (graphene-like) boron nitride (g-BN) monolayer sheet in the presence of a boron-atom vacancy show promising properties for capture and activation of carbon dioxide. CO2 is found to decompose to produce an oxygen molecule via an intermediate chemisorption state on the defect g-BN sheet. The three stationary states and two transition states in the reaction pathway are confirmed by minimum energy pathway search and frequency analysis. The values computed for the two energy barriers involved in this catalytic reaction after enthalpy correction indicate that the catalytic reaction should proceed readily at room temperature.

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.

Career-path analysis using optimal matching and self-organizing maps

This paper is devoted to the analysis of career paths and employability. The state-of-the-art on this topic is rather poor in methodologies. Some authors propose distances well adapted to the data, but are limiting their analysis to hierarchical clustering. Other authors apply sophisticated methods, but only after paying the price of transforming the categorical data into continuous, via a factorial analysis. The latter approach has an important drawback since it makes a linear assumption on the data. We propose a new methodology, inspired from biology and adapted to career paths, combining optimal matching and self-organizing maps. A complete study on real-life data will illustrate our proposal.