CO2-C4H10 Mixtures Simulated in Silica Slit Pores: Relation between Structure and Dynamics

Equilibrium molecular dynamics simulations were conducted for pure n-butane and for mixtures containing n-butane and carbon dioxide confined in 2 nm wide slit-shaped pores carved out of cristobalite silica. A range of thermodynamic conditions was explored, including temperatures ranging from subcritical to supercritical, and various densities. Preferential adsorption of carbon dioxide near the -OH groups on the surface was observed, where the adsorbed CO2 molecules tend to interact simultaneously with more than one -OH group. Analysis of the simulation results suggests that the preferential CO2 adsorption to the pore walls weakens the adsorption of n-butane, lowers the activation energy for n-butane diffusivity, and consequently enhances n-butane mobility. The diffusion results obtained for pure CO2 are consistent with strong adsorption on the pore walls, as the CO2 self-diffusion coefficient is low at low densities, increases with loading, and exhibits a maximum as the density is increased further because of hindrance effects. As the temperature increases, the maximum in self-diffusion coefficient is narrower, steeper, and shifted to lower loading. The simulation results are also quantified in terms of molecular density profiles for both butane and CO2 and in terms of residence time of the various molecules near the solid substrate. Our results could be useful for designing separation devices and also for better understanding the behavior of fluids in subsurface environments

N-octane diffusivity enhancement via carbon dioxide in silica slit-shaped nanopores – a molecular dynamics simulation

Equilibrium molecular dynamics simulations were conducted to study the competitive adsorption and diffusion of mixtures containing n-octane and carbon dioxide confined in slit-shaped silica pores of width 1.9 nm. Atomic density profiles substantiate strong interactions between CO2 molecules and the protonated pore walls. Non-monotonic change in n-octane self-diffusion coefficients as a function of CO2 loading was observed. CO2 preferential adsorption to the pore surface is likely to attenuate the surface adsorption of n-octane, lower the activation energy for n-octane diffusivity, and consequently enhance n-octane mobility at low CO2 loading. This observation was confirmed by conducting test simulations for pure n-octane confined in narrower pores. At high CO2 loading, n-octane diffusivity is hindered by molecular crowding. Thus, n-octane diffusivity displays a maximum. In contrast, within the concentration range considered here, the self-diffusion coefficient predicted for CO2 exhibits a monotonic increase with loading, which is attributed to a combination of effects including the saturation of the adsorption capacity of the silica surface. Test simulations suggest that the results are strongly dependent on the pore morphology, and in particular on the presence of edges that can preferentially adsorb CO2 molecules and therefore affect the distribution of these molecules equally on the pore surface, which appears to be required to provide the effective enhancement of n-octane diffusivity

On the free volume in nuclear multifragmentation

In many statistical multifragmentation models the volume available to the $N$ nonoverlapping fragments forming a given partition is a basic ingredient serving to the simplification of the density of states formula. One therefore needs accurate techniques for calculating this quantity. While the direct Monte-Carlo procedure consisting of randomly generating the fragments into the freeze-out volume and counting the events with no overlapped fragments is numerically affordable only for partitions with small $N$, the present paper proposes a Metropolis - type simulation which allows accurate evaluations of the free volume even for cases with large $N$. This procedure is used for calculating the available volume for various situations. Though globally this quantity has an exponential dependence on $N$, variations of orders of magnitude for partitions with the same $N$ may be identified. A parametrization based on the virial approximation adjusted with a calibration function, describing very well the variations of the free volume for different partitions having the same $N$ is proposed. This parametrization was successfully tested within the microcanonical multifragmentation model from [Al. H. Raduta and Ad. R. Raduta, Phys. Rev. C {\bf 55}, 1344 (1997); {\it ibid.}, {\bf 56}, 2059 (1997)]. Finally, it is proven that parametrizations of the free volume solely dependent on $N$ are rather inadequate for multifragmentation studies producing important deviations from the exact results.Comment: 20 pages, 9 figures, Nucl. Phys. A (in press

Confinement Effects on Carbon Dioxide Methanation: A Novel Mechanism for Abiotic Methane Formation

An important scientific debate focuses on the possibility of abiotic synthesis of hydrocarbons during oceanic crust-seawater interactions. While on-site measurements near hydrothermal vents support this possibility, laboratory studies have provided data that are in some cases contradictory. At conditions relevant for sub-surface environments it has been shown that classic thermodynamics favour the production of CO2 from CH4, while abiotic methane synthesis would require the opposite. However, confinement effects are known to alter reaction equilibria. This report shows that indeed thermodynamic equilibrium can be shifted towards methane production, suggesting that thermal hydrocarbon synthesis near hydrothermal vents and deeper in the magma-hydrothermal system is possible. We report reactive ensemble Monte Carlo simulations for the CO2 methanation reaction. We compare the predicted equilibrium composition in the bulk gaseous phase to that expected in the presence of confinement. In the bulk phase we obtain excellent agreement with classic thermodynamic expectations. When the reactants can exchange between bulk and a confined phase our results show strong dependency of the reaction equilibrium conversions, [Formula: see text], on nanopore size, nanopore chemistry, and nanopore morphology. Some physical conditions that could shift significantly the equilibrium composition of the reactive system with respect to bulk observations are discussed

A scalable parallel finite element framework for growing geometries. Application to metal additive manufacturing

This work introduces an innovative parallel, fully-distributed finite element framework for growing geometries and its application to metal additive manufacturing. It is well-known that virtual part design and qualification in additive manufacturing requires highly-accurate multiscale and multiphysics analyses. Only high performance computing tools are able to handle such complexity in time frames compatible with time-to-market. However, efficiency, without loss of accuracy, has rarely held the centre stage in the numerical community. Here, in contrast, the framework is designed to adequately exploit the resources of high-end distributed-memory machines. It is grounded on three building blocks: (1) Hierarchical adaptive mesh refinement with octree-based meshes; (2) a parallel strategy to model the growth of the geometry; (3) state-of-the-art parallel iterative linear solvers. Computational experiments consider the heat transfer analysis at the part scale of the printing process by powder-bed technologies. After verification against a 3D benchmark, a strong-scaling analysis assesses performance and identifies major sources of parallel overhead. A third numerical example examines the efficiency and robustness of (2) in a curved 3D shape. Unprecedented parallelism and scalability were achieved in this work. Hence, this framework contributes to take on higher complexity and/or accuracy, not only of part-scale simulations of metal or polymer additive manufacturing, but also in welding, sedimentation, atherosclerosis, or any other physical problem where the physical domain of interest grows in time

Cardiovascular risk profile and frailty in a population-based study of older British men.

BACKGROUND: Frailty in older age is known to be associated with cardiovascular disease (CVD) risk. However, the extent to which frailty is associated with the CVD risk profile has been little studied. Our aim was to examine the associations of a range of cardiovascular risk factors with frailty and to assess whether these are independent of established CVD. METHODS: Cross-sectional study of a socially representative sample of 1622 surviving men aged 71-92 examined in 2010-2012 across 24 British towns, from a prospective study initiated in 1978-1980. Frailty was defined using the Fried phenotype, including weight loss, grip strength, exhaustion, slowness and low physical activity. RESULTS: Among 1622 men, 303 (19%) were frail and 876 (54%) were pre-frail. Compared with non-frail, those with frailty had a higher odds of obesity (OR 2.03, 95% CI 1.38 to 2.99), high waist circumference (OR 2.30, 95% CI 1.67 to 3.17), low high-density lipoprotein-cholesterol (HDL-C) (OR 2.28, 95% CI 1.47 to 3.54) and hypertension (OR 1.79, 95% CI 1.27 to 2.54). Prevalence of these factors was also higher in those with frailty (prevalence in frail vs non-frail groups was 46% vs 31% for high waist circumference, 20% vs 11% for low HDL and 78% vs 65% for hypertension). Frail individuals had a worse cardiovascular risk profile with an increased risk of high heart rate, poor lung function (forced expiratory volume in 1 s (FEV1)), raised white cell count (WCC), poor renal function (low estimated glomerular filtration rate), low alanine transaminase and low serum sodium. Some risk factors (HDL-C, hypertension, WCC, FEV1, renal function and albumin) were also associated with being pre-frail. These associations remained when men with prevalent CVD were excluded. CONCLUSIONS: Frailty was associated with increased risk of a range of cardiovascular factors (including obesity, HDL-C, hypertension, heart rate, lung function, renal function) in older people; these associations were independent of established CVD

The Star Formation Rate Density and Dust Attenuation Evolution over 12 Gyr with the VVDS Surveys

[Abridged] We investigate the global galaxy evolution over 12 Gyr (0.05<z<4.5), from the star formation rate density (SFRD), combining the VVDS Deep (17.5<=I<=24.0) and Ultra-Deep (23.00<=i<=24.75) surveys. We obtain a single homogeneous spectroscopic redshift sample, totalizing about 11000 galaxies. We estimate the rest-frame FUV luminosity function (LF) and luminosity density (LD), extract the dust attenuation of the FUV radiation using SED fitting, and derive the dust-corrected SFRD. We find a constant and flat faint-end slope alpha in the FUV LF at z1.7, we set alpha steepening with (1+z). The absolute magnitude M*_FUV brightens in the entire range 02 it is on average brighter than in the literature, while phi* is smaller. Our total LD shows a peak at z=2, present also when considering all sources of uncertainty. The SFRD history peaks as well at z=2. It rises by a factor of 6 during 2 Gyr (from z=4.5 to z=2), and then decreases by a factor of 12 during 10 Gyr down to z=0.05. This peak is mainly produced by a similar peak within the population of galaxies with -21.5<=M_FUV<=-19.5 mag. As times goes by, the total SFRD is dominated by fainter and fainter galaxies. The presence of a clear peak at z=2 and a fast rise at z>2 of the SFRD is compelling for models of galaxy formation. The mean dust attenuation A_FUV of the global galaxy population rises by 1 mag during 2 Gyr from z=4.5 to z=2, reaches its maximum at z=1 (A_FUV=2.2 mag), and then decreases by 1.1 mag during 7 Gyr down to z=0. The dust attenuation maximum is reached 2 Gyr after the SFRD peak, implying a contribution from the intermediate-mass stars to the dust production at z<2.Comment: 23 pages, 15 figures, accepted for publication in A&

Lyman Alpha Emitters in the Hierarchically Clustering Galaxy Formation

We present a new theoretical model for the luminosity functions (LFs) of Lyman alpha (Lya) emitting galaxies in the framework of hierarchical galaxy formation. We extend a semi-analytic model of galaxy formation that reproduces a number of observations for local and high-z galaxies, without changing the original model parameters but introducing a physically-motivated modelling to describe the escape fraction of Lya photons from host galaxies (f_esc). Though a previous study using a hierarchical clustering model simply assumed a constant and universal value of f_esc, we incorporate two new effects on f_esc: extinction by interstellar dust and galaxy-scale outflow induced as a star formation feedback. It is found that the new model nicely reproduces all the observed Lya LFs of the Lya emitters (LAEs) at different redshifts in z ~ 3-6. Especially, the rather surprisingly small evolution of the observed LAE Lya LFs compared with the dark halo mass function is naturally reproduced. Our model predicts that galaxies with strong outflows and f_esc ~ 1 are dominant in the observed LFs. This is also consistent with available observations, while the simple universal f_esc model requires f_esc << 1 not to overproduce the brightest LAEs. On the other hand, we found that our model significantly overpredicts LAEs at z > 6, and absorption of Lya photons by neutral hydrogen in intergalactic medium (IGM) is a reasonable interpretation for the discrepancy. This indicates that the IGM neutral fraction x_HI rapidly evolves from x_HI << 1 at z < 6 to a value of order unity at z ~ 6-7, which is broadly consistent with other observational constraints on the reionization history.Comment: 14 pages, 7 figures, 1 table; accepted to ApJ; the html abstract is replaced to match the accepted version, the .ps and .pdf files are strictly identical between the 2nd and the 3rd version

A robust morphological classification of high-redshift galaxies using support vector machines on seeing limited images. I Method description

We present a new non-parametric method to quantify morphologies of galaxies based on a particular family of learning machines called support vector machines. The method, that can be seen as a generalization of the classical CAS classification but with an unlimited number of dimensions and non-linear boundaries between decision regions, is fully automated and thus particularly well adapted to large cosmological surveys. The source code is available for download at http://www.lesia.obspm.fr/~huertas/galsvm.html To test the method, we use a seeing limited near-infrared ($K_s$ band, $2,16\mu m$) sample observed with WIRCam at CFHT at a median redshift of $z\sim0.8$. The machine is trained with a simulated sample built from a local visually classified sample from the SDSS chosen in the high-redshift sample's rest-frame (i band, $0.77\mu m$) and artificially redshifted to match the observing conditions. We use a 12-dimensional volume, including 5 morphological parameters and other caracteristics of galaxies such as luminosity and redshift. We show that a qualitative separation in two main morphological types (late type and early type) can be obtained with an error lower than 20% up to the completeness limit of the sample ($KAB\sim 22$) which is more than 2 times better that what would be obtained with a classical C/A classification on the same sample and indeed comparable to space data. The method is optimized to solve a specific problem, offering an objective and automated estimate of errors that enables a straightforward comparison with other surveys.Comment: 11 pages, 7 figures, 3 tables. Submitted to A&A. High resolution images are available on reques