114 resultados para boron nitride (BN) nanodisks


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Electrocatalytic reduction of water to molecular hydrogen via the hydrogen evolution reaction may provide a sustainable energy supply for the future, but its commercial application is hampered by the use of precious platinum catalysts. All alternatives to platinum thus far are based on nonprecious metals, and, to our knowledge, there is no report about a catalyst for electrocatalytic hydrogen evolution beyond metals. Here we couple graphitic-carbon nitride with nitrogen-doped graphene to produce a metal-free hybrid catalyst, which shows an unexpected hydrogen evolution reaction activity with comparable overpotential and Tafel slope to some of well-developed metallic catalysts. Experimental observations in combination with density functional theory calculations reveal that its unusual electrocatalytic properties originate from an intrinsic chemical and electronic coupling that synergistically promotes the proton adsorption and reduction kinetics.

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Theory suggests that CCBCC (1) will rearrange to planar cyclo-C4B (19) if the excess energy of 1 is greater than or equal to16.1 kcal mol(-1) [calculations at the CCSD(T)/aug-cc-pVTZ//B3LYP/6-31G(d) level of theory]. Cyclo-C4B lies only 1.1 kcal mol(-1) above CCBCC. The planar nature of symmetrical cyclo-C4B is attributed to multicentered bonding involving boron. If cyclo-C4B (19) has an excess energy of greater than or equal to24.4 kcal mol-1, it may ring open to form CCCCB (3).

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The extraction of coal seam gas (CSG) produces large volumes of potentially contaminated water. It has raised concerns about the environmental health impacts of the co-produced CSG water. In this paper, we review CSG water contaminants and their potential health effects in the context of exposure pathways in Queensland’s CSG basins. The hazardous substances associated with CSG water in Queensland include fluoride, boron, lead and benzene. The exposure pathways for CSG water are: (1) water used for municipal purposes, (2) recreational water activities in rivers, (3) occupational exposures, (4) water extracted from contaminated aquifers, and; (5) indirect exposure through the food chain. We recommend mapping of exposure pathways into communities in CSG regions to determine the potentially exposed populations in Queensland. Future efforts to monitor chemicals of concern and consolidate them into a central database will build the necessary capability to undertake a much needed environmental health impact assessment.

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We have studied the mineral takedaite Ca3(BO3)2, a borate mineral of calcium using SEM with EDX and vibrational spectroscopy. Chemical analysis shows a homogeneous phase, composed of Ca. Boron was not detected. A very intense Raman band at 1087 cm−1 is assigned to the BO stretching vibration of BO3 units. Additional Raman bands may be due to isotopic splitting. In the infrared spectrum, bands at 1218 cm−1 and at 1163, 1262 and 1295 cm−1 are assigned to the trigonal borate stretching modes. Raman bands at 712 and 715 cm−1 are assigned to the in-plane bending modes of the BO3 units. Vibrational spectroscopy enables aspects of the molecular structure of takedaite to be assessed.

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There has been a recent rapid expansion of the range of applications of low-temperature plasma processing in Si-based photovoltaic (PV) technologies. The desire to produce Si-based PV materials at an acceptable cost with consistent performance and reproducibility has stimulated a large number of major research and research infrastructure programs, and a rapidly increasing number of publications in the field of low-temperature plasma processing for Si photovoltaics. In this article, we introduce the low-temperature plasma sources for Si photovoltaic applications and discuss the effects of low-temperature plasma dissociation and deposition on the synthesis of Si-based thin films. We also examine the relevant growth mechanisms and plasma diagnostics, Si thin-film solar cells, Si heterojunction solar cells and silicon nitride materials for antireflection and surface passivation. Special attention is paid to the low-temperature plasma interactions with Si materials including hydrogen interaction, wafer cleaning, masked or mask-free surface texturization, the direct formation of p-n junction, and removal of phosphorus silicate glass or parasitic emitters. The chemical and physical interactions in such plasmas with Si surfaces are analyzed. Several examples of the plasma processes and techniques are selected to represent a variety of applications aimed at the improvement of Si-based solar cell performance. © 2014 Elsevier B.V.

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Attention has recently focussed on MgB2 superconductors (Tc~39K) which can be formed into wires with high material density and viable critical current densities (Jc)1. However, broader utilisation of this diboride and many others is likely to occur when facile synthesis for bulk applications is developed. To date, common synthesis methods include high temperature sintering of mixed elemental powders2, combustion synthesis3, mechano-chemical mixing with high temperature sintering4 and high pressure (~GPa region) with high temperature. In this work, we report on a lower temperature, moderate (<4MPa) pressure method to synthesise metal diborides.

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The metal borides, in particular the diborides and hexaborides, contain stoichiometric forms that include insulators, semiconductors and superconductors. In addition, their end-member structures have high symmetry and two atoms although, in general, substitution(s) of multi-valent ions into the metal site occurs consistent with Vegard’s law. These characteristics allow for fundamental comparison of important physical properties such as superconductivity and insulation within a relatively simple structure type. Our early work1,2 has demonstrated this for the hexaborides and this work compares similar attributes across a broader suite of boride structures. In all cases, theoretical calculations are referenced to structures determined via high resolution neutron or X-ray diffraction experiments.

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Synthesis of metal borides is typically undertaken at high temperature using direct combinations of elemental starting materials[1]. Techniques include carbothermal reduction using elemental carbon, metals, metal oxides and B2O3[2] or reaction between metal chlorides and boron sources[3]. These reactions generally require temperatures greater than 1200oC and are not readily suitable for an industrial setting nor scalable to bulk production.

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Bayesian networks (BNs) are graphical probabilistic models used for reasoning under uncertainty. These models are becoming increasing popular in a range of fields including ecology, computational biology, medical diagnosis, and forensics. In most of these cases, the BNs are quantified using information from experts, or from user opinions. An interest therefore lies in the way in which multiple opinions can be represented and used in a BN. This paper proposes the use of a measurement error model to combine opinions for use in the quantification of a BN. The multiple opinions are treated as a realisation of measurement error and the model uses the posterior probabilities ascribed to each node in the BN which are computed from the prior information given by each expert. The proposed model addresses the issues associated with current methods of combining opinions such as the absence of a coherent probability model, the lack of the conditional independence structure of the BN being maintained, and the provision of only a point estimate for the consensus. The proposed model is applied an existing Bayesian Network and performed well when compared to existing methods of combining opinions.

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This paper presents a novel framework for the modelling of passenger facilitation in a complex environment. The research is motivated by the challenges in the airport complex system, where there are multiple stakeholders, differing operational objectives and complex interactions and interdependencies between different parts of the airport system. Traditional methods for airport terminal modelling do not explicitly address the need for understanding causal relationships in a dynamic environment. Additionally, existing Bayesian Network (BN) models, which provide a means for capturing causal relationships, only present a static snapshot of a system. A method to integrate a BN complex systems model with stochastic queuing theory is developed based on the properties of the Poisson and exponential distributions. The resultant Hybrid Queue-based Bayesian Network (HQBN) framework enables the simulation of arbitrary factors, their relationships, and their effects on passenger flow and vice versa. A case study implementation of the framework is demonstrated on the inbound passenger facilitation process at Brisbane International Airport. The predicted outputs of the model, in terms of cumulative passenger flow at intermediary and end points in the inbound process, are found to have an R2 goodness of fit of 0.9994 and 0.9982 respectively over a 10 h test period. The utility of the framework is demonstrated on a number of usage scenarios including causal analysis and ‘what-if’ analysis. This framework provides the ability to analyse and simulate a dynamic complex system, and can be applied to other socio-technical systems such as hospitals.

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We have studied the boron containing mineral ezcurrite Na4B10O17·7H2O using electron microscopy and vibrational spectroscopy. Both tetrahedral and trigonal boron units are observed. The nominal resolution of the Raman spectrometer is of the order of 2 cm−1 and as such is sufficient enough to identify separate bands for the stretching bands of the two boron isotopes. The Raman band at 1037 cm−1 is assigned to BO stretching vibration. Raman bands at 1129, 1163, 1193 cm−1 are attributed to BO stretching vibration of the tetrahedral units. The Raman band at 947 cm−1 is attributed to the antisymmetric stretching modes of tetrahedral boron. The sharp Raman peak at 1037 cm−1 is from the 11-B component such a mode, then it should have a smaller 10-B satellite near (1.03) × (1037) = 1048 cm−1, and indeed a small peak at 1048 is observed. The broad Raman bands at 3186, 3329, 3431, 3509, 3547 and 3576 cm−1 are assigned to water stretching vibrations. Broad infrared bands at 3170, 3322, 3419, 3450, 3493, 3542, 3577 and 3597 cm−1 are also assigned to water stretching vibrations. Infrared bands at 1330, 1352, 1389, 1407, 1421 and 1457 cm−1 are assigned to the antisymmetric stretching vibrations of trigonal boron. The observation of so many bands suggests that there is considerable variation in the structure of ezcurrite. Infrared bands at 1634, 1646 and 1681 cm−1 are assigned to water bending modes. The number of water bending modes is in harmony with the number of water stretching vibrations.

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We have studied the mineral kornerupine, a borosilicate mineral, by using a combination of scanning electron microscopy with energy-dispersive analysis and Raman and infrared spectroscopy. Qualitative chemical analysis of kornerupine shows a magnesium–aluminum silicate. Strong Raman bands at 925, 995, and 1051 cm−1 with bands of lesser intensity at 1035 and 1084 cm−1 are assigned to the silicon–oxygen stretching vibrations of the siloxane units. Raman bands at 923 and 947 cm−1 are attributed to the symmetrical stretching vibrations of trigonal boron. Infrared spectra show greater complexity and the infrared bands are more difficult to assign. Two intense Raman bands at 3547 and 3612 cm−1 are assigned to the stretching vibrations of hydroxyl units. The infrared bands are observed at 3544 and 3610 cm−1. Water is also identified in the spectra of kornerupine.

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We have studied the mineral Ca(H4B3O7)(OH)⋅4(H2O) or CaB3O3(OH)5⋅4(H2O) using electron microscopy and vibrational spectroscopy. The mineral has been characterized by a range of techniques including X-ray diffraction, thermal analysis, electron microscopy with EDX and vibrational spectroscopy. Electron microscopy shows a pure phase and the chemical analysis shows the presence of calcium only. The nominal resolution of the Raman spectrometer is of the order of 2 cm−1 and as such is sufficient enough to identify separate bands for the stretching bands of the two boron isotopes. Raman and infrared bands are assigned to the stretching and bending modes of trigonal and tetrahedral boron and the stretching modes of the hydroxyl and water units. By using a combination of techniques we have characterized the borate mineral inyoite.

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We have studied the borate mineral szaibelyite MgBO2(OH) using electron microscopy and vibrational spectroscopy. EDS spectra show a phase composed of Mg with minor amounts of Fe. Both tetrahedral and trigonal boron units are observed. The nominal resolution of the Raman spectrometer is of the order of 2 cm−1 and as such is sufficient enough to identify separate bands for the stretching bands of the two boron isotopes. The Raman band at 1099 cm−1 with a shoulder band at 1093 cm−1 is assigned to BO stretching vibration. Raman bands at 1144, 1157, 1229, 1318 cm−1 are attributed to the BOH in-plane bending modes. Raman bands at 836 and 988 cm−1 are attributed to the antisymmetric stretching modes of tetrahedral boron. The infrared bands at 3559 and 3547 cm−1 are assigned to hydroxyl stretching vibrations. Broad infrared bands at 3269 and 3398 cm−1 are assigned to water stretching vibrations. Infrared bands at 1306, 1352, 1391, 1437 cm−1 are assigned to the antisymmetric stretching vibrations of trigonal boron. Vibrational spectroscopy enables aspects of the molecular structure of the borate mineral szaibelyite to be assessed.

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The use of expert knowledge to quantify a Bayesian Network (BN) is necessary when data is not available. This however raises questions regarding how opinions from multiple experts can be used in a BN. Linear pooling is a popular method for combining probability assessments from multiple experts. In particular, Prior Linear Pooling (PrLP), which pools opinions then places them into the BN is a common method. This paper firstly proposes an alternative pooling method, Posterior Linear Pooling (PoLP). This method constructs a BN for each expert, then pools the resulting probabilities at the nodes of interest. Secondly, it investigates the advantages and disadvantages of using these pooling methods to combine the opinions of multiple experts. Finally, the methods are applied to an existing BN, the Wayfinding Bayesian Network Model, to investigate the behaviour of different groups of people and how these different methods may be able to capture such differences. The paper focusses on 6 nodes Human Factors, Environmental Factors, Wayfinding, Communication, Visual Elements of Communication and Navigation Pathway, and three subgroups Gender (female, male),Travel Experience (experienced, inexperienced), and Travel Purpose (business, personal) and finds that different behaviors can indeed be captured by the different methods.