43 resultados para Molecules - Models - Computer simulation


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Proceedings of the 44th Rocky Mountain conference on analytical chemistry

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In this paper, we investigate the effects of various potential models in the description of vapor–liquid equilibria (VLE) and adsorption of simple gases on highly graphitized thermal carbon black. It is found that some potential models proposed in the literature are not suitable for the description of VLE (saturated gas and liquid densities and the vapor pressure with temperature). Simple gases, such as neon, argon, krypton, xenon, nitrogen, and methane are studied in this paper. To describe the isotherms on graphitized thermal carbon black correctly, the surface mediation damping factor introduced in our recent publication should be used to calculate correctly the fluid–fluid interaction energy between particles close to the surface. It is found that the damping constant for the noble gases family is linearly dependent on the polarizability, suggesting that the electric field of the graphite surface has a direct induction effect on the induced dipole of these molecules. As a result of this polarization by the graphite surface, the fluid–fluid interaction energy is reduced whenever two particles are near the surface. In the case of methane, we found that the damping constant is less than that of a noble gas having the similar polarizability, while in the case of nitrogen the damping factor is much greater and this could most likely be due to the quadrupolar nature of nitrogen.

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Quantifying mass and energy exchanges within tropical forests is essential for understanding their role in the global carbon budget and how they will respond to perturbations in climate. This study reviews ecosystem process models designed to predict the growth and productivity of temperate and tropical forest ecosystems. Temperate forest models were included because of the minimal number of tropical forest models. The review provides a multiscale assessment enabling potential users to select a model suited to the scale and type of information they require in tropical forests. Process models are reviewed in relation to their input and output parameters, minimum spatial and temporal units of operation, maximum spatial extent and time period of application for each organization level of modelling. Organizational levels included leaf-tree, plot-stand, regional and ecosystem levels, with model complexity decreasing as the time-step and spatial extent of model operation increases. All ecosystem models are simplified versions of reality and are typically aspatial. Remotely sensed data sets and derived products may be used to initialize, drive and validate ecosystem process models. At the simplest level, remotely sensed data are used to delimit location, extent and changes over time of vegetation communities. At a more advanced level, remotely sensed data products have been used to estimate key structural and biophysical properties associated with ecosystem processes in tropical and temperate forests. Combining ecological models and image data enables the development of carbon accounting systems that will contribute to understanding greenhouse gas budgets at biome and global scales.

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Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

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Genetic research on risk of alcohol, tobacco or drug dependence must make allowance for the partial overlap of risk-factors for initiation of use, and risk-factors for dependence or other outcomes in users. Except in the extreme cases where genetic and environmental risk-factors for initiation and dependence overlap completely or are uncorrelated, there is no consensus about how best to estimate the magnitude of genetic or environmental correlations between Initiation and Dependence in twin and family data. We explore by computer simulation the biases to estimates of genetic and environmental parameters caused by model misspecification when Initiation can only be defined as a binary variable. For plausible simulated parameter values, the two-stage genetic models that we consider yield estimates of genetic and environmental variances for Dependence that, although biased, are not very discrepant from the true values. However, estimates of genetic (or environmental) correlations between Initiation and Dependence may be seriously biased, and may differ markedly under different two-stage models. Such estimates may have little credibility unless external data favor selection of one particular model. These problems can be avoided if Initiation can be assessed as a multiple-category variable (e.g. never versus early-onset versus later onset user), with at least two categories measurable in users at risk for dependence. Under these conditions, under certain distributional assumptions., recovery of simulated genetic and environmental correlations becomes possible, Illustrative application of the model to Australian twin data on smoking confirmed substantial heritability of smoking persistence (42%) with minimal overlap with genetic influences on initiation.

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Adsorption of ethylene and ethane on graphitized thermal carbon black and in slit pores whose walls are composed of graphene layers is studied in detail to investigate the packing efficiency, the two-dimensional critical temperature, and the variation of the isosteric heat of adsorption with loading and temperature. Here we used a Monte Carlo simulation method with a grand canonical Monte Carlo ensemble. A number of two-center Lennard-Jones (LJ) potential models are investigated to study the impact of the choice of potential models in the description of adsorption behavior. We chose two 2C-LJ potential models in our investigation of the (i) UA-TraPPE-LJ model of Martin and Siepmann (J. Phys. Chem. B 1998,102, 25692577) for ethane and Wick et al. (J. Phys. Chem. B 2000,104, 8008-8016) for ethylene and (ii) AUA4-LJ model of Ungerer et al. (J. Chem. Phys. 2000,112, 5499-5510) for ethane and Bourasseau et al. (J. Chem. Phys. 2003, 118, 3020-3034) for ethylene. These models are used to study the adsorption of ethane and ethylene on graphitized thermal carbon black. It is found that the solid-fluid binary interaction parameter is a function of adsorbate and temperature, and the adsorption isotherms and heat of adsorption are well described by both the UA-TraPPE and AUA models, although the UA-TraPPE model performs slightly better. However, the local distributions predicted by these two models are slightly different. These two models are used to explore the two-dimensional condensation for the graphitized thermal carbon black, and these values are 110 K for ethylene and 120 K for ethane.

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In this paper we consider the adsorption of argon on the surface of graphitized thermal carbon black and in slit pores at temperatures ranging from subcritical to supercritical conditions by the method of grand canonical Monte Carlo simulation. Attention is paid to the variation of the adsorbed density when the temperature crosses the critical point. The behavior of the adsorbed density versus pressure (bulk density) shows interesting behavior at temperatures in the vicinity of and those above the critical point and also at extremely high pressures. Isotherms at temperatures greater than the critical temperature exhibit a clear maximum, and near the critical temperature this maximum is a very sharp spike. Under the supercritical conditions and very high pressure the excess of adsorbed density decreases towards zero value for a graphite surface, while for slit pores negative excess density is possible at extremely high pressures. For imperfect pores (defined as pores that cannot accommodate an integral number of parallel layers under moderate conditions) the pressure at which the excess pore density becomes negative is less than that for perfect pores, and this is due to the packing effect in those imperfect pores. However, at extremely high pressure molecules can be packed in parallel layers once chemical potential is great enough to overcome the repulsions among adsorbed molecules. (c) 2005 American Institute of Physics.

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In this paper we investigate the effects of surface mediation on the adsorption behavior of argon at different temperatures on homogeneous graphitized thermal carbon black and on heterogeneous nongraphitized carbon black surface. The grand canonical Monte Carlo (GCMC) simulation is used to study the adsorption, and its performance is tested against a number of experimental data on graphitized thermal carbon black (which is known to be highly homogeneous) that are available in the literature. The surface-mediation effect is shown to be essential in the correct description of the adsorption isotherm because without accounting for that effect the GCMC simulation results are always greater than the experimental data in the region where the monolayer is being completed. This is due to the overestimation of the fluid–fluid interaction between particles in the first layer close to the solid surface. It is the surface mediation that reduces this fluid–fluid interaction in the adsorbed layers, and therefore the GCMC simulation results accounting for this surface mediation that are presented in this paper result in a better description of the data. This surface mediation having been determined, the surface excess of argon on heterogeneous carbon surfaces having solid–fluid interaction energies different from the graphite can be readily obtained. Since the real heterogeneous carbon surface is not the same as the homogeneous graphite surface, it can be described by an area distribution in terms of the well depth of the solid–fluid energy. Assuming a patchwise topology of the surface with patches of uniform well depth of solid–fluid interaction, the adsorption on a real carbon surface can be determined as an integral of the local surface excess of each patch with respect to the differential area. When this is matched against the experimental data of a carbon surface, we can derive the area distribution versus energy and hence the geometrical surface area. This new approach will be illustrated with the adsorption of argon on a nongraphitized carbon at 87.3 and 77 K, and it is found that the GCMC surface area is different from the BET surface area by about 7%. Furthermore, the description of the isotherm in the region of BET validity of 0.06 to 0.2 is much better with our method than with the BET equation.

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Brugada syndrome (BS) is a genetic disease identified by an abnormal electrocardiogram ( ECG) ( mainly abnormal ECGs associated with right bundle branch block and ST-elevation in right precordial leads). BS can lead to increased risk of sudden cardiac death. Experimental studies on human ventricular myocardium with BS have been limited due to difficulties in obtaining data. Thus, the use of computer simulation is an important alternative. Most previous BS simulations were based on animal heart cell models. However, due to species differences, the use of human heart cell models, especially a model with three-dimensional whole-heart anatomical structure, is needed. In this study, we developed a model of the human ventricular action potential (AP) based on refining the ten Tusscher et al (2004 Am. J. Physiol. Heart Circ. Physiol. 286 H1573 - 89) model to incorporate newly available experimental data of some major ionic currents of human ventricular myocytes. These modified channels include the L-type calcium current (ICaL), fast sodium current (I-Na), transient outward potassium current (I-to), rapidly and slowly delayed rectifier potassium currents (I-Kr and I-Ks) and inward rectifier potassium current (I-Ki). Transmural heterogeneity of APs for epicardial, endocardial and mid-myocardial (M) cells was simulated by varying the maximum conductance of IKs and Ito. The modified AP models were then used to simulate the effects of BS on cellular AP and body surface potentials using a three-dimensional dynamic heart - torso model. Our main findings are as follows. (1) BS has little effect on the AP of endocardial or mid-myocardial cells, but has a large impact on the AP of epicardial cells. (2) A likely region of BS with abnormal cell AP is near the right ventricular outflow track, and the resulting ST-segment elevation is located in the median precordium area. These simulation results are consistent with experimental findings reported in the literature. The model can reproduce a variety of electrophysiological behaviors and provides a good basis for understanding the genesis of abnormal ECG under the condition of BS disease.

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The finite element method is used to simulate coupled problems, which describe the related physical and chemical processes of ore body formation and mineralization, in geological and geochemical systems. The main purpose of this paper is to illustrate some simulation results for different types of modelling problems in pore-fluid saturated rock masses. The aims of the simulation results presented in this paper are: (1) getting a better understanding of the processes and mechanisms of ore body formation and mineralization in the upper crust of the Earth; (2) demonstrating the usefulness and applicability of the finite element method in dealing with a wide range of coupled problems in geological and geochemical systems; (3) qualitatively establishing a set of showcase problems, against which any numerical method and computer package can be reasonably validated. (C) 2002 Published by Elsevier Science B.V.