Effects of quenching rate on amorphous structures of Cu46Zr54 metallic glass

Metallic glass shows some superior properties different from crystalline, but the nature of amorphous structure and structural change during glass transition have not been completely understood yet. Molecular dynamics simulation provides intuitive insight into the microstructure and properties at atomistic level. Before probing into the microstructures of metallic glass with molecular dynamics (MD) simulation, it is important to obtain amorphous state first. In the current work, we reproduce the process of manufacturing metallic glass in laboratory including the melting, equilibrating and quenching procedure with molecular dynamics simulations. The structure changing at melting point and glass transition temperature are investigated with the different cooling processing. The partial radial distribution function (PRDF) is applied as a criterion to judge the final amorphous state obtained considering the quenching at different cooling rates and the effects of cooling rate on the formation of amorphous structures are further discussed.

Effects of quenching rate on amorphous structures of Cu46Zr54 metallic glass

Metallic glass shows some superior properties different from crystalline, but the nature of amorphous structure and structural change during glass transition have not been completely understood yet. Molecular dynamics simulation provides intuitive insight into the microstructure and properties at atomistic level. Before probing into the microstructures of metallic glass with molecular dynamics (MD) simulation, it is important to obtain amorphous state first. In the current work, we reproduce the process of manufacturing metallic glass in laboratory including the melting, equilibrating and quenching procedure with molecular dynamics simulations. The structure changing at melting point and glass transition temperature are investigated with the different cooling processing. The partial radial distribution function (PRDF) is applied as a criterion to judge the final amorphous state obtained considering the quenching at different cooling rates and the effects of cooling rate on the formation of amorphous structures are further discussed.

Nature of crystalline particle assembly in ring shaped colloidal stains from concentrated dispersions

The drying of colloidal droplet suspensions is important in many realms of practical application and has sustained the interest of researchers over two decades. The arrangements of polystyrene and silica beads, both of diameter 1 μm, 10% by volume of solid deposited on normal glass (hydrophilic), and silicone (hydrophobic) surfaces evaporated from a suspension volume of 3 μL, were investigated. Doughnut shape depositions were found, imputing the influence of strong central circulation flows that resulted in three general regions. In the central region which had strong particle build-up, the top most layers of particle arrangement was confirmed to be disordered using power spectrum and radial distribution function analysis. On closer examination, this appeared more like frustrated attempts to crystallize into larger grains rather than beads arranging in a disordered fashion throughout the piling process. With an adapted micro-bulldozing operation to progressively remove layers of particles from the heap, we found that the later efforts to crystallize through lateral capillary inter-particle forces were liable to be undone once the particles contacted the disorganized particles underneath, which were formed out of the jamming of fast particles arriving at the surface. © 2014 Elsevier B.V.

Simulation of oleuropein structural conformation in vacuum, water and triolein-water systems using molecular dynamics

Oleuropein, the main phenolic compound of olive leaves, exhibits a unique blend of biological activities and has been shown to locate itself at the oil-water (O/W) interface. This behavior could influence the physico-chemical properties of dispersed systems such as emulsions. In this work, we study the effect of the microenvironment (vacuum, water, and triolein-water) on the conformational preferences of oleuropein using molecular dynamics (MD) simulations at 300K for at least 30ns. The seven torsions that describe the flexible skeleton of oleuropein were monitored together with the distance between the glucose (Glu) and hydroxytyrosol (Hyd) moieties (dglu-hyd) of the molecule. The obtained trajectories demonstrated that oleuropein adopts different conformations that depend on the environment. The preferential conformers in each system were analyzed for their molecular geometry and internal energy. In vacuum, the oleuropein preferential conformation is tight with the glucose moiety in close proximity with the hydroxytyrosol moiety. In water, oleuropein preferential conformers presented large differences in their structural properties, varying from a close like U form, and a semi-opened form, to an opened form characterized by high fluctuations in dglu-hyd values. In a triolein-water system, oleuropein tends to adopt a more open form where the glucose moiety could be approximately aligned with the hydroxytyrosol and elenolic acid moieties. Based on a calculation at the HF/6-31G* level, these flexibilities of oleuropein required energy of 19.14kcal/mol in order to adopt the conformation between water and triolein-water system. A radial distribution function (RDF) analysis showed that specific hydroxyl groups of Hyd and Glu interact with water molecules, enabling us to understand the amphiphilic character of oleuropein at the triolein-water interface. MD calculations together with interfacial tension measurements revealed that the oleuropein binding at O/W interface is an enthalpy driven mechanism.

Exercise loading and cortical bone distribution at the tibial shaft

Cortical bone is not a uniform tissue, and its apparent density [cortical volumetric density (vBMD)] varies around the bone cross-section as well as along the axial length of the bone. It is not yet known, whether the varying vBMD distribution is attributable to modulation in the predominant loads affecting bone. The aim of the present study was to compare the cortical bone mass distribution through the bone cortex (radial distribution) and around the center of mass (polar distribution) among 221 premenopausal women aged 17–40 years representing athletes involved in high impact, odd impact, high magnitude, repetitive low impact, repetitive non-impact sports and leisure time physical activity (referent controls). Bone cross-sections at the tibial mid-diaphysis were assessed with pQCT. Radial and polar vBMD distributions were analyzed in three concentric cortical divisions within the cortical envelope and in four cortical sectors originating from the center of the bone cross-section. MANCOVA, including age as a covariate, revealed no significant group by division/sector interaction in either radial or polar distribution, but the mean vBMD values differed between groups (P < 0.001). The high and odd-impact groups had 1.2 to 2.6% (P < 0.05) lower cortical vBMD than referents, in all analyzed sectors/divisions. The repetitive, low-impact group had 0.4 to 1.0% lower (P < 0.05) vBMD at the mid and outer cortical regions and at the anterior sector of the tibia. The high magnitude group had 1.2% lower BMD at the lateral sector (P < 0.05). The present results generate a hypothesis that the radial and polar cortical bone vBMD distributions within the tibial mid-shaft are not modulated by exercise loading but the mean vBMD level is slightly affected.

Effects of lifetime loading history on cortical bone density and its distribution in middle-aged and older men

We have reported previously that long-term participation of weight-bearing exercise is associated with increased QCT-derived cortical bone size and strength in middle-aged and older men, but not whole bone cortical volumetric BMD. However, since bone remodeling and the distribution of loading-induced strains within cortical bone are non-uniform, the aim of this study was to examine the effects of lifetime loading history on cortical bone mass distribution and bone shape in healthy community dwelling middle-aged and older men. We used QCT to assess mid-femur and mid-tibia angular bone mass distribution around its center (polar distribution), the bone density distribution through the cortex (radial distribution), and the ratio between the maximum and minimum moments of inertia (I_max/I_min ratio) in 281 men aged 50 to 79 years. Current (> 50 years) and past (13–50 years) sport and leisure time activity was assessed by questionnaire to calculate an osteogenic index (OI) during adolescence and adulthood. All men were then categorized into a high (H) or low/non impact (L) group according to their OI scores in each period. Three contrasting groups were then formed to reflect weight-bearing impact categories during adolescence and then adulthood: H–H, H–L and L–L. For polar bone mass distribution, bone deposition in the anterolateral, medial and posterior cortices were 6–10% greater at the mid-femur and 9–24% greater at mid-tibia in men in the highest compared to lowest tertile of lifetime loading (p < 0.01– < 0.001). When comparing the influence of contrasting loading history during adolescence and adulthood, there was a graded response between the groups in the distribution of bone mass at the anterior-lateral and posterior regions of the mid-tibia (H–H > H–L > L–L). For radial bone density distribution, there were no statistically significant effects of loading at the mid-femur, but a greater lifetime OI was associated with a non-significant 10–15% greater bone density near the endocortical region of the mid-tibia. In conclusion, a greater lifetime loading history was associated with region-specific adaptations in cortical bone density.

A hybrid ART-GRNN online learning neural network with a ε-insensitive loss function

In this brief, a new neural network model called generalized adaptive resonance theory (GART) is introduced. GART is a hybrid model that comprises a modified Gaussian adaptive resonance theory (MGA) and the generalized regression neural network (GRNN). It is an enhanced version of the GRNN, which preserves the online learning properties of adaptive resonance theory (ART). A series of empirical studies to assess the effectiveness of GART in classification, regression, and time series prediction tasks is conducted. The results demonstrate that GART is able to produce good performances as compared with those of other methods, including the online sequential extreme learning machine (OSELM) and sequential learning radial basis function (RBF) neural network models.

Sequence-dependent structure/function relationships of catalytic peptide-enabled gold nanoparticles generated under ambient synthetic conditions

Peptide-enabled nanoparticle (NP) synthesis routes can create and/or assemble functional nanomaterials under environmentally friendly conditions, with properties dictated by complex interactions at the biotic/abiotic interface. Manipulation of this interface through sequence modification can provide the capability for material properties to be tailored to create enhanced materials for energy, catalysis, and sensing applications. Fully realizing the potential of these materials requires a comprehensive understanding of sequence-dependent structure/function relationships that is presently lacking. In this work, the atomic-scale structures of a series of peptide-capped Au NPs are determined using a combination of atomic pair distribution function analysis of high-energy X-ray diffraction data and advanced molecular dynamics (MD) simulations. The Au NPs produced with different peptide sequences exhibit varying degrees of catalytic activity for the exemplar reaction 4-nitrophenol reduction. The experimentally derived atomic-scale NP configurations reveal sequence-dependent differences in structural order at the NP surface. Replica exchange with solute-tempering MD simulations are then used to predict the morphology of the peptide overlayer on these Au NPs and identify factors determining the structure/catalytic properties relationship. We show that the amount of exposed Au surface, the underlying surface structural disorder, and the interaction strength of the peptide with the Au surface all influence catalytic performance. A simplified computational prediction of catalytic performance is developed that can potentially serve as a screening tool for future studies. Our approach provides a platform for broadening the analysis of catalytic peptide-enabled metallic NP systems, potentially allowing for the development of rational design rules for property enhancement.

Effects of habitual physical activity and fitness on tibial cortical bone mass structure and mass distribution in pre-pubertal boys and girl: the look study

Targeted weight-bearing activities during the pre-pubertal years can improve cortical bone mass, structure and distribution, but less is known about the influence of habitual physical activity (PA) and fitness. This study examined the effects of contrasting habitual PA and fitness levels on cortical bone density, geometry and mass distribution in pre-pubertal children. Boys (n = 241) and girls (n = 245) aged 7–9 years had a pQCT scan to measure tibial mid-shaft total, cortical and medullary area, cortical thickness, density, polar strength strain index (SSIpolar) and the mass/density distribution through the bone cortex (radial distribution divided into endo-, mid- and pericortical regions) and around the centre of mass (polar distribution). Four contrasting PA and fitness groups (inactive–unfit, inactive–fit, active–unfit, active–fit) were generated based on daily step counts (pedometer, 7-days) and fitness levels (20-m shuttle test and vertical jump) for boys and girls separately. Active-fit boys had 7.3–7.7 % greater cortical area and thickness compared to inactive–unfit boys (P < 0.05), which was largely due to a 6.4–7.8 % (P < 0.05) greater cortical mass in the posterior–lateral, medial and posterior–medial 66 % tibial regions. Cortical area was not significantly different across PA-fitness categories in girls, but active-fit girls had 6.1 % (P < 0.05) greater SSIpolar compared to inactive–fit girls, which was likely due to their 6.7 % (P < 0.05) greater total bone area. There was also a small region-specific cortical mass benefit in the posterior–medial 66 % tibia cortex in active-fit girls. Higher levels of habitual PA-fitness were associated with small regional-specific gains in 66 % tibial cortical bone mass in pre-pubertal children, particularly boys.

Effect of data length and bin numbers on distribution entropy (DistEn) measurement in analyzing healthy aging

Complexity analysis of a given time series is executed using various measures of irregularity, the most commonly used being Approximate entropy (ApEn), Sample entropy (SampEn) and Fuzzy entropy (FuzzyEn). However, the dependence of these measures on the critical parameter of tolerance `r' leads to precarious results, owing to random selections of r. Attempts to eliminate the use of r in entropy calculations introduced a new measure of entropy namely distribution entropy (DistEn) based on the empirical probability distribution function (ePDF). DistEn completely avoids the use of a variance dependent parameter like r and replaces it by a parameter M, which corresponds to the number of bins used in the histogram to calculate it. When tested for synthetic data, M has been observed to produce a minimal effect on DistEn as compared to the effect of r on other entropy measures. Also, DistEn is said to be relatively stable with data length (N) variations, as far as synthetic data is concerned. However, these claims have not been analyzed for physiological data. Our study evaluates the effect of data length N and bin number M on the performance of DistEn using both synthetic and physiologic time series data. Synthetic logistic data of `Periodic' and `Chaotic' levels of complexity and 40 RR interval time series belonging to two groups of healthy aging population (young and elderly) have been used for the analysis. The stability and consistency of DistEn as a complexity measure as well as a classifier have been studied. Experiments prove that the parameters N and M are more influential in deciding the efficacy of DistEn performance in the case of physiologic data than synthetic data. Therefore, a generalized random selection of M for a given data length N may not always be an appropriate combination to yield good performance of DistEn for physiologic data.

Evaluation of selective growth in a Fe-2.8% Si single crystal using Rodrigues-Frank space

A Fe-2.8%Si single crystal was scratched in order to randomise the texture in the neighbourhood of the notch. Annealing resulted in recrystallization and grain growth starting from the deformed zone. Misorientations between the single crystal matrix and the grown grains were gathered and were studied in order to investigate the possibility for selective growth based on a specific misorientation. However, instead of studying the misorientation angle or axis profiles separately in a 1D or 2D projection a full misorientation analysis was carried out in the 3-dimensional Rodrigues-Frank misorientation space, which offers an unambiguous interpretation of the data because no features are hidden or masked by a projection. It is concluded that the selective growth phenomenon following the <110>26.5deg misorientation relationship is strongly supported by the gathered orientation data, after appropriately normalizing these data with respect to a random misorientation distribution.

Prediction of wool knitwear pilling propensity using support vector machines

The propensity of wool knitwear to form entangled fiber balls, known as pills, on the surface is affected by a large number of factors. This study examines, for the first time, the application of the support vector machine (SVM) data mining tool to the pilling propensity prediction of wool knitwear. The results indicate that by using the binary classification method and the radial basis function (RBF) kernel function, the SVM is able to give high pilling propensity prediction accuracy for wool knitwear without data over-fitting. The study also found that the number of records available for each pill rating greatly affects the learning and prediction capability of SVM models.

Robust ODF smoothing for accurate estimation of fiber orientation

Q-ball imaging was presented as a model free, linear and multimodal diffusion sensitive approach to reconstruct diffusion orientation distribution function (ODF) using diffusion weighted MRI data. The ODFs are widely used to estimate the fiber orientations. However, the smoothness constraint was proposed to achieve a balance between the angular resolution and noise stability for ODF constructs. Different regularization methods were proposed for this purpose. However, these methods are not robust and quite sensitive to the global regularization parameter. Although, numerical methods such as L-curve test are used to define a globally appropriate regularization parameter, it cannot serve as a universal value suitable for all regions of interest. This may result in over smoothing and potentially end up in neglecting an existing fiber population. In this paper, we propose to include an interpolation step prior to the spherical harmonic decomposition. This interpolation based approach is based on Delaunay triangulation provides a reliable, robust and accurate smoothing approach. This method is easy to implement and does not require other numerical methods to define the required parameters. Also, the fiber orientations estimated using this approach are more accurate compared to other common approaches.