Electrochemical characteristics of ordered mesoporous carbon used as electrode material in Li-ion battery

Ordered mesoporous carbon CMK-5 was comprehensively tested for the first time as electrode materials in lithium ion battery. The surface morphology, pore structure and crystal structure were investigated by Scanning Electronic Microscopy (SEM), N-2 adsorption technique and X-ray diffraction (XRD) respectively. Electrochemical properties of CMK-5 were studied by galvanostatic cycling and cyclic voltammetry, and compared with conventional anode material graphite. Results showed that the reversible capacity of CMK-5 was 525 mAh/g at the third charge-discharge cycle and that CMK-5 was more compatible for quick charge-discharge cycling because of its special mesoporous structure. Of special interest was that the CMK-5 gave no peak on its positive sweep of the cyclic voltammetry, which was different from all the other known anode materials. Besides, X-ray photoelectron spectroscopy (XPS) and XRD were also applied to investigate the charge-discharge characteristics of CMK-5.

Synthesis of ordered nanoporous carbon and its application in Li-ion battery

Ordered nanoporous carbon (ONC) was comprehensively tested for the first time as electrode material in lithium-ion battery. Structure characterization shows the order nanoporous structure and tiny crystallite structure of as-synthesized ONC. The electrochemical properties of this carbon were studied by galvanostatic cycling and cyclic voltammetry. Of special interest is that ONC gave no peak on its positive sweep of the cyclic voltammetry, which was different from other known anode materials. Besides, X-ray photoelectron spectroscopy (XPS) and XRD were also used to investigate the electrochemical characteristics of ONC. (c) 2006 Elsevier Ltd. All rights reserved.

Effect of pore packing defects in 2-D ordered mesoporous carbons on ionic transport

Ordered mesoporous materials show great importance in energy, environmental, and chemical engineering. The diffusion of guest species in mesoporous networks plays an important role in these applications, especially for energy storage, such as supercapacitors based on ordered mesoporous carbons ( OMCs). The ion diffusion behavior in two different 2-D hexagonal OMCs was investigated by using cyclic voltametry and electrochemical impedance spectroscopy. In addition, transmission electron microscopy, small-angle X-ray diffraction, and nitrogen cryosorption methods were used to study the pore structure variations of these two OMCs. It was found that, for the OMC with defective pore channels ( termed as pore packing defects), the gravimetric capacitance was greatly decayed when the voltage scan rate was increased. The experimental results suggest that, for the ion diffusion in 2-D hexagonal OMCs with similar mesopore size distribution, the pore packing defect is a dominant dynamic factor.

Control of ordered structure and morphology of large-pore periodic mesoporous organosilicas by inorganic salt

Highly ordered rodlike periodic mesoporous organosilicas (PMO) were successfully synthesized using 1.2-bis(trimethoxysilyl)ethane as an precursor and triblock copolymer P123 as a template at low acid concentration and in the presence of inorganic salts (KCl). The role of acid and salt as well as the effects of synthesis temperature and reactant mole ratio in the control of morphology and the formation of ordered mesostructure was systematically examined. It was found that the addition of inorganic salt can dramatically expand the range of the synthesis parameters to produce highly ordered PMO structure and improve the quality of PMO materials. The morphology of PMOs was significantly dependent on the induction time for precipitation. The uniform PMO rods can only be synthesized in a narrow range of acid and salt concentrations. The results also show that the optimized salt concentration (I M) and low acidity (0.167 M) were beneficial to the formation of not only highly ordered mesostructure but also rodlike morphology. Increasing acidity resulted in fast hydrolysis reaction and short rod or plate-like particles. Highly ordered rod can also be prepared at low temperature (35 degrees C) with high salt amount (1.5 M) or high temperature (45 degrees C) with low salt amount (0.5 M). Optimum reactant molar composition at 40 degrees C is 0.035P123:8KCl:1.34HCI:444H(2)O:1.0bis(trimethoxysilyl)ethane. Lower or higher SiO2/PI23 ratio led to the formation of uniform meso-macropores or pore-blocking effect. (c) 2005 Elsevier Inc. All rights reserved.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.

Effect of sample geometry on regression rate of the melting interface for carbon steel burned in oxygen

Promoted-ignition testing on carbon steel rods of varying cross-sectional area and shape was performed in high pressure oxygen to assess the effect of sample geometry on the regression rate of the melting interface. Cylindrical and rectangular geometries and three different cross sections were tested and the regression rates of the cylinders were compared to the regression rates of the rectangular samples at test pressures around 6.9 MPa. Tests were recorded and video analysis used to determine the regression rate of the melting interface by a new method based on a drop cycle which was found to provide a good basis for statistical analysis and provide excellent agreement to the standard averaging methods used. Both geometries tested showed the typical trend of decreasing regression rate of the melting interface with increasing cross-sectional area; however, it was shown that the effect of geometry is more significant as the sample's cross sections become larger. Discussion is provided regarding the use of 3.2-mm square rods rather than 3.2-mm cylindrical rods within the standard ASTM test and any effect this may have on the observed regression rate of the melting interface.

Use of regression equation of peripheral pulse timing characteristics to predict hypertension in children

Studies have shown that an increase in arterial stiffening can indicate the presence of cardiovascular diseases like hypertension. Current gold standard in clinical practice is by measuring the blood pressure of patients using a mercury sphygmomanometer. However, the nature of this technique is not suitable for prolonged monitoring. It has been established that pulse wave velocity is a direct measure of arterial stiffening. However, its usefulness is hampered by the absence of techniques to estimate it non-invasively. Pulse transit time (PTT) is a simple and non-intrusive method derived from pulse wave velocity. It has shown its capability in childhood respiratory sleep studies. Recently, regression equations that can predict PTT values for healthy Caucasian children were formulated. However, its usefulness to identify hypertensive children based on mean PTT values has not been investigated. This was a continual study where 3 more Caucasian male children with known clinical hypertension were recruited. Results indicated that the PTT predictive equations are able to identify hypertensive children from their normal counterparts in a significant manner (p < 0.05). Hence, PTT can be a useful diagnostic tool in identifying hypertension in children and shows potential to be a non-invasive continual monitor for arterial stiffening.