Testing multiple mapping conditioning mixing for Monte Carlo probability density function simulations

Mitarai [Phys. Fluids 17, 047101 (2005)] compared turbulent combustion models against homogeneous direct numerical simulations with extinction/recognition phenomena. The recently suggested multiple mapping conditioning (MMC) was not considered and is simulated here for the same case with favorable results. Implementation issues crucial for successful MMC simulations are also discussed.

Modeling of adsorption on nongraphitized carbon surface: GCMC simulation studies and comparison with experimental data

We model nongraphitized carbon black surfaces and investigate adsorption of argon on these surfaces by using the grand canonical Monte Carlo simulation. In this model, the nongraphitized surface is modeled as a stack of graphene layers with some carbon atoms of the top graphene layer being randomly removed. The percentage of the surface carbon atoms being removed and the effective size of the defect ( created by the removal) are the key parameters to characterize the nongraphitized surface. The patterns of adsorption isotherm and isosteric heat are particularly studied, as a function of these surface parameters as well as pressure and temperature. It is shown that the adsorption isotherm shows a steplike behavior on a perfect graphite surface and becomes smoother on nongraphitized surfaces. Regarding the isosteric heat versus loading, we observe for the case of graphitized thermal carbon black the increase of heat in the submonolayer coverage and then a sharp decline in the heat when the second layer is starting to form, beyond which it increases slightly. On the other hand, the isosteric heat versus loading for a highly nongraphitized surface shows a general decline with respect to loading, which is due to the energetic heterogeneity of the surface. It is only when the fluid-fluid interaction is greater than the surface energetic factor that we see a minimum-maximum in the isosteric heat versus loading. These simulation results of isosteric heat agree well with the experimental results of graphitization of Spheron 6 (Polley, M. H.; Schaeffer, W. D.; Smith, W. R. J. Phys. Chem. 1953, 57, 469; Beebe, R. A.; Young, D. M. J. Phys. Chem. 1954, 58, 93). Adsorption isotherms and isosteric heat in pores whose walls have defects are also studied from the simulation, and the pattern of isotherm and isosteric heat could be used to identify the fingerprint of the surface.

Searching for convergence in phylogenetic Markov chain Monte Carlo

Markov chain Monte Carlo (MCMC) is a methodology that is gaining widespread use in the phylogenetics community and is central to phylogenetic software packages such as MrBayes. An important issue for users of MCMC methods is how to select appropriate values for adjustable parameters such as the length of the Markov chain or chains, the sampling density, the proposal mechanism, and, if Metropolis-coupled MCMC is being used, the number of heated chains and their temperatures. Although some parameter settings have been examined in detail in the literature, others are frequently chosen with more regard to computational time or personal experience with other data sets. Such choices may lead to inadequate sampling of tree space or an inefficient use of computational resources. We performed a detailed study of convergence and mixing for 70 randomly selected, putatively orthologous protein sets with different sizes and taxonomic compositions. Replicated runs from multiple random starting points permit a more rigorous assessment of convergence, and we developed two novel statistics, delta and epsilon, for this purpose. Although likelihood values invariably stabilized quickly, adequate sampling of the posterior distribution of tree topologies took considerably longer. Our results suggest that multimodality is common for data sets with 30 or more taxa and that this results in slow convergence and mixing. However, we also found that the pragmatic approach of combining data from several short, replicated runs into a metachain to estimate bipartition posterior probabilities provided good approximations, and that such estimates were no worse in approximating a reference posterior distribution than those obtained using a single long run of the same length as the metachain. Precision appears to be best when heated Markov chains have low temperatures, whereas chains with high temperatures appear to sample trees with high posterior probabilities only rarely. [Bayesian phylogenetic inference; heating parameter; Markov chain Monte Carlo; replicated chains.]

Simulation study of methanol and ethanol adsorption on graphitized carbon black

GCMC simulations are applied to the adsorption of sub-critical methanol and ethanol on graphitized carbon black at 300 K. The carbon black was modelled both with and without carbonyl functional groups. Large differences are seen between the amounts adsorbed for different carbonyl configurations at low pressure prior to monolayer coverage. Once a monolayer has been formed on the carbon black, the adsorption behaviour is similar between the model surfaces with and without functional groups. Simulation isotherms for the case of low carbonyl concentrations or no carbonyls are qualitatively similar to the few experimental isotherms available in the literature for methanol and ethanol adsorption on highly graphitized carbon black. Isosteric heats and adsorbed phase heat capacities are shown to be very sensitive to carbonyl configurations. A maximum is observed in the adsorbed phase heat capacity of the alcohols for all simulations but is unrealistically high for the case of a plain graphite surface. The addition of carbonyls to the surface greatly reduces this maximum and approaches experimental data with carbonyl concentration as low as 0.09 carbonyls/nm(2).

Effects of graphene layer size on the adsorption of fluids on graphitized thermal carbon black. A computer simulation study

The adsorption of Lennard-Jones fluids (argon and nitrogen) onto a graphitized thermal carbon black surface was studied with a Grand Canonical Monte Carlo Simulation (GCMC). The surface was assumed to be finite in length and composed of three graphene layers. When the GCMC simulation was used to describe adsorption on a graphite surface, an over-prediction of the isotherm was consistently observed in the pressure regions where the first and second layers are formed. To remove this over-prediction, surface mediation was accounted for to reduce the fluid-fluid interaction. Do and co-workers have introduced the so-called surface-mediation damping factor to correct the over-prediction for the case of a graphite surface of infinite extent, and this approach has yielded a good description of the adsorption isotherm. In this paper, the effects of the finite size of the graphene layer on the adsorption isotherm and how these would affect the extent of the surface mediation were studied. It was found that this finite-surface model provides a better description of the experimental data for graphitized thermal carbon black of high surface area (i.e. small crystallite size) while the infinite- surface model describes data for carbon black of very low surface area (i.e. large crystallite size).

Correct procedures for the calculation of heats of adsorption for heterogeneous adsorbents from molecular simulation

Several procedures for calculating the heat of adsorption from Monte Carlo simulations for a heterogeneous adsorbent are presented. Simulations have been performed to generate isotherms for nitrogen at 77 K and methane at 273.15 K in graphitic slit pores of various widths. The procedures were then applied to calculate the heat of adsorption of an activated carbon with an arbitrary pore size distribution. The consistency of the different procedures shows them to be correct in calculating interaction energy contributions to the heat of adsorption. The currently favored procedure for this type of calculation, from the literature, is shown to be incorrect and in serious error when calculating the heat of adsorption of activated carbon.

Optimization of slitlike carbon nanopores for storage of hythane fuel at ambient temperatures

Carbons with slitlike pores can serve as effective host materials for storage of hythane fuel, a bridge between the petrol combustion and hydrogen fuel cells. We have used grand canonical Monte Carlo simulation for the modeling of the hydrogen and methane mixture storage at 293 K and pressure of methane and hydrogen mixture up to 2 MPa. We have found that these pores serve as efficient vessels for the storage of hythane fuel near ambient temperatures and low pressures. We find that, for carbons having optimized slitlike pores of size H congruent to 7 angstrom ( pore width that can accommodate one adsorbed methane layer), and bulk hydrogen mole fraction >= 0.9, the volumetric stored energy exceeds the 2010 target of 5.4 MJ dm(-3) established by the U. S. FreedomCAR Partnership. At the same condition, the content of hydrogen in slitlike carbon pores is congruent to 7% by energy. Thus, we have obtained the composition corresponding to hythane fuel in carbon nanospaces with greatly enhanced volumetric energy in comparison to the traditional compression method. We proposed the simple system with added extra container filled with pure free/adsorbed methane for adjusting the composition of the desorbed mixture as needed during delivery. Our simulation results indicate that light slit pore carbon nanomaterials with optimized parameters are suitable filling vessels for storage of hythane fuel. The proposed simple system consisting of main vessel with physisorbed hythane fuel, and an extra container filled with pure free/adsorbed methane will be particularly suitable for combustion of hythane fuel in buses and passenger cars near ambient temperatures and low pressures.

Application of Monte Carlo simulations to identify an appropriate dosage strategy for patients receiving a continuous intravenous infusion of enoxaparin

Aim: To identify an appropriate dosage strategy for patients receiving enoxaparin by continuous intravenous infusion (CII). Methods: Monte Carlo simulations were performed in NONMEM, (200 replicates of 1000 patients) to predict steady state anti-Xa concentrations (Css) for patients receiving a CII of enoxaparin. The covariate distribution model was simulated based on covariate demographics in the CII study population. The impact of patient weight, renal function (creatinine clearance (CrCL)) and patient location (intensive care unit (ICU)) were evaluated. A population pharmacokinetic model was used as the input-output model (1-compartment first order output model with mixed residual error structure). Success of a dosing regimen was based on the percent of Css that is between the therapeutic range of 0.5 IU/ml to 1.2 IU/ml. Results: The best dose for patients in the ICU was 4.2IU/kg/h (success mean 64.8% and 90% prediction interval (PI): 60.1–69.8%) if CrCL60ml/min, the best dose was 8.3IU/kg/h (success mean 65.4%, 90% PI: 58.5–73.2%). Simulations suggest that there was a 50% improvement in the success of the CII if the dose rate for ICU patients with CrCL

Quantum chaos in atom optics

I shall discuss the quantum and classical dynamics of a class of nonlinear Hamiltonian systems. The discussion will be restricted to systems with one degree of freedom. Such systems cannot exhibit chaos, unless the Hamiltonians are time dependent. Thus we shall consider systems with a potential function that has a higher than quadratic dependence on the position and, furthermore, we shall allow the potential function to be a periodic function of time. This is the simplest class of Hamiltonian system that can exhibit chaotic dynamics. I shall show how such systems can be realized in atom optics, where very cord atoms interact with optical dipole potentials of a far-off resonance laser. Such systems are ideal for quantum chaos studies as (i) the energy of the atom is small and action scales are of the order of Planck's constant, (ii) the systems are almost perfectly isolated from the decohering effects of the environment and (iii) optical methods enable exquisite time dependent control of the mechanical potentials seen by the atoms.

Electron beam current loss at the high-vacuum-high-pressure boundary in the environmental scanning electron microscope

A significant loss in electron probe current can occur before the electron beam enters the specimen chamber of an environmental scanning electron microscope (ESEM). This loss results from electron scattering in a gaseous jet formed inside and downstream (above) the pressure-limiting aperture (PLA), which separates the high-pressure and high-vacuum regions of the microscope. The electron beam loss above the PLA has been calculated for three different ESEMs, each with a different PLA geometry: an ElectroScan E3, a Philips XL30 ESEM, and a prototype instrument. The mass thickness of gas above the PLA in each case has been determined by Monte Carlo simulation of the gas density variation in the gas jet. It has been found that the PLA configurations used in the commercial instruments produce considerable loss in the electron probe current that dramatically degrades their performance at high chamber pressure and low accelerating voltage. These detrimental effects are minimized in the prototype instrument, which has an optimized thin-foil PLA design.

Close packed transitions in slit-shaped pores: Density functional theory study of methane adsorption capacity in carbon

An important feature of improving lattice gas models and classical isotherms is the incorporation of a pore size dependent capacity, which has hitherto been overlooked. In this paper, we develop a model for predicting the temperature dependent variation in capacity with pore size. The model is based on the analysis of a lattice gas model using a density functional theory approach at the close packed limit. Fluid-fluid and solid-fluid interactions are modeled by the Lennard-Jones 12-6 potential and Steele's 10-4-3, potential respectively. The capacity of methane in a slit-shaped carbon pore is calculated from the characteristic parameters of the unit cell, which are extracted by minimizing the grand potential of the unit cell. The capacities predicted by the proposed model are in good agreement with those obtained from grand canonical Monte Carlo simulation, for pores that can accommodate up to three adsorbed layers. Single particle and pair distributions exhibit characteristic features that correspond to the sequence of buckling and rhombic transitions that occur as the slit pore width is increased. The model provides a useful tool to model continuous variation in the microstructure of an adsorbed phase, namely buckling and rhombic transitions, with increasing pore width. (C) 2002 American Institute of Physics.