SWCNT networks on nanoporous silica catalyst support : morphological and connectivity control for nanoelectronic, gas-sensing, and biosensing devices

Effective control of morphology and electrical connectivity of networks of single-walled carbon nanotubes (SWCNTs) by using rough, nanoporous silica supports of Fe catalyst nanoparticles in catalytic chemical vapor deposition is demonstrated experimentally. The very high quality of the nanotubes is evidenced by the G-to-D Raman peak ratios (>50) within the range of the highest known ratios. Transitions from separated nanotubes on smooth SiO2 surface to densely interconnected networks on the nanoporous SiO2 are accompanied by an almost two-order of magnitude increase of the nanotube density. These transitions herald the hardly detectable onset of the nanoscale connectivity and are confirmed by the microanalysis and electrical measurements. The achieved effective nanotube interconnection leads to the dramatic, almost three-orders of magnitude decrease of the SWCNT network resistivity compared to networks of similar density produced by wet chemistry-based assembly of preformed nanotubes. The growth model, supported by multiscale, multiphase modeling of SWCNT nucleation reveals multiple constructive roles of the porous catalyst support in facilitating the catalyst saturation and SWCNT nucleation, consistent with the observed higher density of longer nanotubes. The associated mechanisms are related to the unique surface conditions (roughness, wettability, and reduced catalyst coalescence) on the porous SiO2 and the increased carbon supply through the supporting porous structure. This approach is promising for the direct integration of SWCNT networks into Si-based nanodevice platforms and multiple applications ranging from nanoelectronics and energy conversion to bio- and environmental sensing.

A coupled SPH-DEM model for micro-scale structural deformations of plant cells during drying

A single plant cell was modeled with smoothed particle hydrodynamics (SPH) and a discrete element method (DEM) to study the basic micromechanics that govern the cellular structural deformations during drying. This two-dimensional particle-based model consists of two components: a cell fluid model and a cell wall model. The cell fluid was approximated to a highly viscous Newtonian fluid and modeled with SPH. The cell wall was treated as a stiff semi-permeable solid membrane with visco-elastic properties and modeled as a neo-Hookean solid material using a DEM. Compared to existing meshfree particle-based plant cell models, we have specifically introduced cell wall–fluid attraction forces and cell wall bending stiffness effects to address the critical shrinkage characteristics of the plant cells during drying. Also, a moisture domain-based novel approach was used to simulate drying mechanisms within the particle scheme. The model performance was found to be mainly influenced by the particle resolution, initial gap between the outermost fluid particles and wall particles and number of particles in the SPH influence domain. A higher order smoothing kernel was used with adaptive smoothing length to improve the stability and accuracy of the model. Cell deformations at different states of cell dryness were qualitatively and quantitatively compared with microscopic experimental findings on apple cells and a fairly good agreement was observed with some exceptions. The wall–fluid attraction forces and cell wall bending stiffness were found to be significantly improving the model predictions. A detailed sensitivity analysis was also done to further investigate the influence of wall–fluid attraction forces, cell wall bending stiffness, cell wall stiffness and the particle resolution. This novel meshfree based modeling approach is highly applicable for cellular level deformation studies of plant food materials during drying, which characterize large deformations.

Engineering the mechanical properties of graphene nanotube hybrid structures through structural modulation

The excellent multi-functional properties of carbon nanotube (CNT) and graphene have enabled them as appealing building blocks to construct 3D carbon-based nanomaterials or nanostructures. The recently reported graphene nanotube hybrid structure (GNHS) is one of the representatives of such nanostructures. This work investigated the relationships between the mechanical properties of the GNHS and its structure basing on large-scale molecular dynamics simulations. It is found that increasing the length of the constituent CNTs, the GNHS will have a higher Young’s modulus and yield strength. Whereas, no strong correlation is found between the number of graphene layers and Young’s modulus and yield strength, though more graphene layers intends to lead to a higher yield strain. In the meanwhile, the presences of multi-wall CNTs are found to greatly strengthen the hybrid structure. Generally, the hybrid structures exhibit a brittle behavior and the failure initiates from the connecting regions between CNT and graphene. More interestingly, affluent formations of monoatomic chains and rings are found at the fracture region. This study provides an in-depth understanding of the mechanical performance of the GNHSs while varying their structures, which will shed lights on the design and also the applications of the carbon-based nanostructures.

Exploitation of the menshutkin reaction for the controlled assembly of halogen bonded architectures incorporating 1,2-diiodotetrafluorobenzene and 1,3,5-Triiodotrifluorobenzene

1,4-Diazabicyclo[2.2.2]octane (DABCO) forms well-defined co-crystals with 1,2-diiodotetrafluorobenzene (1,2-DITFB), [(1,2-DITFB)2DABCO], and 1,3,5-triiodotrifluorobenzene, [(1,3,5-TITFB)2DABCO]. Both systems exhibited lower-than-expected supramolecular connectivity, which inspired a search for polymorphs in alternative crystallization solvents. In dichloromethane solution, the Menshutkin reaction was found to occur, generating chloride anions and quaternary ammonium cations through the reaction between the solvent and DABCO. The controlled in situ production of chloride ions facilitated the crystallization of new halogen bonded networks, DABCO–CH2Cl[(1,2-DITFB)Cl] (zigzag X-bonded chains) and (DABCO–CH2Cl)3[(1,3,5-TITFB)2Cl3]·CHCl3 (2D pseudo-trigonal X-bonded nets displaying Borremean entanglement), propagating with charge-assisted C–I···Cl– halogen bonds. The method was found to be versatile, and substitution of DABCO with triethylamine (TEA) gave (TEA-CH2Cl)3[(1,2-DITFB)Cl3]·4(H2O) (mixed halogen bond hydrogen bond network with 2D supramolecular connectivity) and TEA-CH2Cl[(1,3,5-TITFB)Cl] (tightly packed planar trigonal nets). The co-crystals were typically produced in high yield and purity with relatively predictable supramolecular topology, particularly with respect to the connectivity of the iodobenzene molecules. The potential to use this synthetic methodology for crystal engineering of halogen bonded architectures is demonstrated and discussed.

Structural and functional characterization of three DsbA Paralogues from Salmonella enterica Serovar Typhimurium

In prototypic Escherichia coli K-12 the introduction of disulfide bonds into folding proteins is mediated by the Dsb family of enzymes, primarily through the actions of the highly oxidizing protein EcDsbA. Homologues of the Dsb catalysts are found in most bacteria. Interestingly, pathogens have developed distinct Dsb machineries that play a pivotal role in the biogenesis of virulence factors, hence contributing to their pathogenicity. Salmonella enterica serovar (sv.) Typhimurium encodes an extended number of sulfhydryl oxidases, namely SeDsbA, SeDsbL, and SeSrgA. Here we report a comprehensive analysis of the sv. Typhimurium thiol oxidative system through the structural and functional characterization of the three Salmonella DsbA paralogues. The three proteins share low sequence identity, which results in several unique three-dimensional characteristics, principally in areas involved in substrate binding and disulfide catalysis. Furthermore, the Salmonella DsbA-like proteins also have different redox properties. Whereas functional characterization revealed some degree of redundancy, the properties of SeDsbA, SeDsbL, and SeSrgA and their expression pattern in sv. Typhimurium indicate a diverse role for these enzymes in virulence.

Impact of al passivation and cosputter on the structural property of β-FeSi2 for Al-Doped β-FeSi2/ n -Si(100) based solar cells application

The aluminum (Al) doped polycrystalline p-type β-phase iron disilicide (p-β-FeSi2) is grown by thermal diffusion of Al from Al-passivated n-type Si(100) surface into FeSi2 during crystallization of amorphous FeSi2 to form a p-type β-FeSi 2/n-Si(100) heterostructure solar cell. The structural and photovoltaic properties of p-type β-FeSi2/n-type c-Si structures is then investigated in detail by using X-ray diffraction, Raman spectroscopy, transmission electron microscopy analysis, and electrical characterization. The results are compared with Al-doped p-β-FeSi2 prepared by using cosputtering of Al and FeSi2 layers on Al-passivated n-Si(100) substrates. A significant improvement in the maximum open-circuit voltage (Voc) from 120 to 320 mV is achieved upon the introduction of Al doping through cosputtering of Al and amorphous FeSi2 layer. The improvement in Voc is attributed to better structural quality of Al-doped FeSi2 film through Al doping and to the formation of high quality crystalline interface between Al-doped β-FeSi2 and n-type c-Si. The effects of Al-out diffusion on the performance of heterostructure solar cells have been investigated and discussed in detail.

Predicting structural disruption of proteins caused by crossover

We present a machine learning model that predicts a structural disruption score from a protein s primary structure. SCHEMA was introduced by Frances Arnold and colleagues as a method for determining putative recombination sites of a protein on the basis of the full (PDB) description of its structure. The present method provides an alternative to SCHEMA that is able to determine the same score from sequence data only. Circumventing the need for resolving the full structure enables the exploration of yet unresolved and even hypothetical sequences for protein design efforts. Deriving the SCHEMA score from a primary structure is achieved using a two step approach: first predicting a secondary structure from the sequence and then predicting the SCHEMA score from the predicted secondary structure. The correlation coefficient for the prediction is 0.88 and indicates the feasibility of replacing SCHEMA with little loss of precision.

Maternal concern about her toddler undereating and becoming underweight and use of feeding practices - analysis of the NOURISH and SAIDI cohorts using structural equation modeling

The chubby baby who eats well is desirable in our culture. Perceived low weight gains and feeding concerns are common reasons mothers seek advice in the early years. In contrast, childhood obesity is a global public health concern. Use of coercive feeding practices, prompted by maternal concern about weight, may disrupt a child’s innate self regulation of energy intake, promoting overeating and overweight. This study describes predictors of maternal concern about her child undereating/becoming underweight and feeding practices. Mothers in the control group of the NOURISH and South Australian Infants Dietary Intake studies (n = 332) completed a self-administered questionnaire when the child was aged 12–16 months. Weight-for-age z-score (WAZ)was derived from weight measured by study staff. Mean age (SD) was 13.8 (1.3) months, mean WAZ (SD), 0.58 (0.86) and 49% were male. WAZ and two questions describing food refusal were combined in a structural equation model with four items from the Infant feeding Questionnaire (IFQ) to form the factor ‘Concern about undereating/weight’. Structural relationships were drawn between concern and IFQ factors ‘awareness of infant’s hunger and satiety cues’, ‘use of food to calm infant’s fussiness’ and ‘feeding infant on a schedule’, resulting in a model of acceptable fit. Lower WAZ and higher frequency of food refusal predicted higher maternal concern. Higher maternal concern was associated with lower awareness of infant cues (r = −.17, p = .01) and greater use of food to calm (r = .13, p = .03). In a cohort of healthy children, maternal concern about undereating and underweight was associated with practices that have the potential to disrupt self-regulation.

An interpretative structural modeling based network reconfiguration strategy for power systems

The network reconfiguration is an important stage of restoring a power system after a complete blackout or a local outage. Reasonable planning of the network reconfiguration procedure is essential for rapidly restoring the power system concerned. An approach for evaluating the importance of a line is first proposed based on the line contraction concept. Then, the interpretative structural modeling (ISM) is employed to analyze the relationship among the factors having impacts on the network reconfiguration. The security and speediness of restoring generating units are considered with priority, and a method is next proposed to select the generating unit to be restored by maximizing the restoration benefit with both the generation capacity of the restored generating unit and the importance of the line in the restoration path considered. Both the start-up sequence of generating units and the related restoration paths are optimized together in the proposed method, and in this way the shortcomings of separately solving these two issues in the existing methods are avoided. Finally, the New England 10-unit 39-bus power system and the Guangdong power system in South China are employed to demonstrate the basic features of the proposed method.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

A critical review of structural equation modeling applications in construction research

Structural equation modeling (SEM) is a versatile multivariate statistical technique, and applications have been increasing since its introduction in the 1980s. This paper provides a critical review of 84 articles involving the use of SEM to address construction related problems over the period 1998–2012 including, but not limited to, seven top construction research journals. After conducting a yearly publication trend analysis, it is found that SEM applications have been accelerating over time. However, there are inconsistencies in the various recorded applications and several recurring problems exist. The important issues that need to be considered are examined in research design, model development and model evaluation and are discussed in detail with reference to current applications. A particularly important issue concerns the construct validity. Relevant topics for efficient research design also include longitudinal or cross-sectional studies, mediation and moderation effects, sample size issues and software selection. A guideline framework is provided to help future researchers in construction SEM applications.

Retinal anatomy of the New Zealand kiwi: Structural traits consistent with their nocturnal behavior

Kiwi (Apteryx spp.) have a visual system unlike that of other nocturnal birds, and have specializations to their auditory, olfactory and tactile systems. Eye size, binocular visual fields and visual brain centers in kiwi are proportionally the smallest yet recorded among birds. Given the many unique features of the kiwi visual system, we examined the laminar organization of the kiwi retina to determine if they evolved increased light sensitivity with a shift to a nocturnal niche or if they retained features of their diurnal ancestor. The laminar organization of the kiwi retina was consistent with an ability to detect low light levels similar to that of other nocturnal species. In particular, the retina appeared to have a high proportion of rod photoreceptors compared to diurnal species, as evidenced by a thick outer nuclear layer, and also numerous thin photoreceptor segments intercalated among the conical shaped cone photoreceptor inner segments. Therefore, the retinal structure of kiwi was consistent with increased light sensitivity, although other features of the visual system, such as eye size, suggest a reduced reliance on vision. The unique combination of a nocturnal retina and smaller than expected eye size, binocular visual fields and brain regions make the kiwi visual system unlike that of any bird examined to date. Whether these features of their visual system are an evolutionary design that meets their specific visual needs or are a remnant of a kiwi ancestor that relied more heavily on vision is yet to be determined.

Three-dimensional geological modelling of the Galilee and central Eromanga basins, Australia: New insights into aquifer/aquitard geometry and potential influence of faults on inter-connectivity

Study region The Galilee and Eromanga basins are located in central Queensland, Australia. Both basins are components of the Great Artesian Basin which host some of the most significant groundwater resources in Australia. Study focus This study evaluates the influence of regional faults on groundwater flow in an aquifer/aquitard interbedded succession that form one of the largest Artesian Basins in the world. In order to assess the significance of regional faults as potential barriers or conduits to groundwater flow, vertical displacements of the major aquifers and aquitards were studied at each major fault and the general hydraulic relationship of units that are juxtaposed by the faults were considered. A three-dimensional (3D) geological model of the Galilee and Eromanga basins was developed based on integration of well log data, seismic surfaces, surface geology and elevation data. Geological structures were mapped in detail and major faults were characterised. New hydrological insights for the region Major faults that have been described in previous studies have been confirmed within the 3D geological model domain and a preliminary assessment of their hydraulic significance has been conducted. Previously unknown faults such as the Thomson River Fault (herein named) have also been identified in this study.