Impact of potential models on adsorption of linear molecules on carbon black

In this paper, we investigate the effects of potential models on the description of equilibria of linear molecules (ethylene and ethane) adsorption on graphitized thermal carbon black. GCMC simulation is used as a tool to give adsorption isotherms, isosteric heat of adsorption and the microscopic configurations of these molecules. At the heart of the GCMC are the potential models, describing fluid-fluid interaction and solid-fluid interaction. Here we studied the two potential models recently proposed in the literature, the UA-TraPPE and AUA4. Their impact in the description of adsorption behavior of pure components will be discussed. Mixtures of these components with nitrogen and argon are also studied. Nitrogen is modeled a two-site plus discrete charges while argon as a spherical particle. GCMC simulation is also used for generating simulation mixture isotherms. It is found that co-operation between species occurs when the surface is fractionally covered while competition is important when surface is fully loaded.

A falsification of the thermal specialization paradigm: compensation for elevated temperatures in Antarctic fishes

Specialization to a particular environment is one of the main factors used to explain species distributions. Antarctic fishes are often cited as a classic example to illustrate the specialization process and are regarded as the archetypal stenotherms. Here we show that the Antarctic fish Pagothenia borchgrevinki has retained the capacity to compensate for chronic temperature change. By displaying astounding plasticity in cardiovascular response and metabolic control, the fishes maintained locomotory performance at elevated temperatures. Our falsification of the specialization paradigm indicates that the effect of climate change on species distribution and extinction may be overestimated by current models of global warming.

Evaluation of 1-site and 5-site models of methane on its adsorption on graphite and in graphitic slit pores

In this paper, we evaluate the performance of the 1- and 5-site models of methane on the description of adsorption on graphite surfaces and in graphitic slit pores. These models have been known to perform well in the description of the fluid-phase behavior and vapor-liquid equilibria. Their performance in adsorption is evaluated in this work for nonporous graphitized thermal carbon black, and simulation results are compared with the experimental data of Avgul and Kiselev (Chemistry and Physics of Carbon; Dekker: New York, 1970; Vol. 6, p 1). On this nonporous surface, it is found that these models perform as well on isotherms at various temperatures as they do on the experimental isosteric heat for adsorption on a graphite surface. They are then tested for their performance in predicting the adsorption isotherms in graphitic slit pores, in which we would like to explore the effect of confinement on the molecule packing. Pore widths of 10 and 20 angstrom are chosen in this investigation, and we also study the effects of temperature by choosing 90.7, 113, and 273 K. The first two are for subcritical conditions, with 90.7 K being the triple point of methane and 113 K being its boiling point. The last temperature is chosen to represent the supercritical condition so that we can investigate the performance of these models at extremely high pressures. We have found that for the case of slit pores investigated in this paper, although the two models yield comparable pore densities (provided the accessible pore width is used in the calculation of pore density), the number of particles predicted by the I-site model is always greater than that predicted by the 5-site model, regardless of whether temperature is subcritical or supercritical. This is due to the packing effect in the confined space such that a methane molecule modeled as a spherical particle in the I-site model would pack better than the fused five-sphere model in the case of the 5-site model. Because the 5-site model better describes the liquid- and solid-phase behavior, we would argue that the packing density in small pores is better described with a more detailed 5-site model, and care should be exercised when using the 1-site model to study adsorption in small pores.

Effects of surface heterogeneity on the adsorption of nitrogen on graphitized thermal carbon black

In this paper, we study the surface heterogeneity and the surface mediation on the intermolecular potential energy for nitrogen adsorption on graphitized thermal carbon black (GTCB). The surface heterogeneity is modeled as the random distribution of effective carbonyl functional groups on the graphite surface. The molecular parameters and the discrete charges of this carbonyl group are taken from Jorgensen, et al. (J. Am. Chem. Soc., (1984) 106, 6638) while those for nitrogen (dispersive parameters and discrete charges) are taken from Murthy et al. (Mol. Phys., (1983) 50, 531) in our Grand Canonical Monte Carlo (GCMC) simulation. The solid surface mediation in the reduction of intermolecular potential energy between two fluid molecules was taken from a recent work by Do et al. (Langmuir, (2004) 20, 7623). Our simulation results accounting for the surface heterogeneity and surface mediation on intermolecular potential energy were compared with the experimental data of nitrogen at 77 and 90 K. The solid-fluid dispersive parameters are determined from the Lorentz-Berthelot (LB) rule. The fraction of the graphite surface covered with carbonyl functional groups was then derived from the consideration of the Henry constant, and for the data of Kruk et al. (Langmuir, (1999) 15, 1435) we have found that 1% of their GTCB surface is covered with effective carbonyl functional groups. The damping constant, due to surface mediation, was determined from the consideration of the portion of the adsorption isotherm where the first layer is being completed, and it was found to take a value of 0.0075. With these parameters, we have found that the GCMC simulation results describe the data over the complete range of pressure substantially better than any other MC models in the literature. The implication of this work is demonstrated with local adsorption isotherms of 10 and 20 A slit pores. One was obtained without allowance for surface mediation, while the other correctly accounts for these factors. The two local isotherms differ substantially, and the implication is that if we used incorrect local isotherms (i.e. without the surface mediation) the pore size distribution would be incorrectly derived.

Adsorption of argon on homogeneous graphitized thermal carbon black and heterogeneous carbon surface

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.

Adsorption of flexible n-alkane on graphitized thermal carbon black: analysis of adsorption isotherm by means of GCMC simulation

In this paper, we investigate the suitability of the grand canonical Monte Carlo in the description of adsorption equilibria of flexible n-alkane (butane, pentane and hexane) on graphitized thermal carbon black. Potential model of n-alkane of Martin and Siepmann (J. Phys. Chem. 102 (1998) 2569) is employed in the simulation, and we consider the flexibility of molecule in the simulation. By this we study two models, one is the fully flexible molecular model in which n-alkane is subject to bending and torsion, while the other is the rigid molecular model in which all carbon atoms reside on the same plane. It is found that (i) the adsorption isotherm results of these two models are close to each other, suggesting that n-alkane model behaves mostly as rigid molecules with respect to adsorption although the isotherm for longer chain n-hexane is better described by the flexible molecular model (ii) the isotherms agree very well with the experimental data at least up to two layers on the surface.

Adsorption of benzene on graphitized thermal carbon black: Reduction of the quadrupole moment in the adsorbed phase

The performance of intermolecular potential models on the adsorption of benzene on graphitized thermal carbon black at various temperatures is investigated. Two models contain only dispersive sites, whereas the other two models account explicitly for the dispersive and electrostatic sites. Using numerous data in the literature on benzene adsorption on graphitized thermal carbon black at various temperatures, we have found that the effect of surface mediation on interaction between adsorbed benzene molecules must be accounted for to describe correctly the adsorption isotherm as well as the isosteric heat. Among the two models with partial charges tested, the WSKS model of Wick et at. I that has only six dispersive sites and three discrete partial charges is better than the very expensive all-atom model of Jorgensen and Severance.(2) Adsorbed benzene molecules on graphitized thermal carbon black have a complex orientation with respect to distance from the surface and also with respect to loading. At low loadings, they adopt the parallel configuration relative to the graphene surface, whereas at higher loadings (still less than monolayer coverage) some molecules adopt a slant orientation to maximize the fluid-fluid interaction. For loadings in the multilayer region, the orientation of molecules in the first layer is influenced by the presence of molecules in the second layer. The data that are used in this article come from the work of Isirikyan and Kiselev,(3) Pierotti and Smallwood,(4) Pierce and Ewing,(5) Belyakova, Kiselev, and Kovaleva,(6) and Carrott et al.(7)

Coadaptation: A unifying principle in evolutionary thermal biology

Over the last 50 yr, thermal biology has shifted from a largely physiological science to a more integrated science of behavior, physiology, ecology, and evolution. Today, the mechanisms that underlie responses to environmental temperature are being scrutinized at levels ranging from genes to organisms. From these investigations, a theory of thermal adaptation has emerged that describes the evolution of thermoregulation, thermal sensitivity, and thermal acclimation. We review and integrate current models to form a conceptual model of coadaptation. We argue that major advances will require a quantitative theory of coadaptation that predicts which strategies should evolve in specific thermal environments. Simply combining current models, however, is insufficient to understand the responses of organisms to thermal heterogeneity; a theory of coadaptation must also consider the biotic interactions that influence the net benefits of behavioral and physiological strategies. Such a theory will be challenging to develop because each organism's perception of and response to thermal heterogeneity depends on its size, mobility, and life span. Despite the challenges facing thermal biologists, we have never been more pressed to explain the diversity of strategies that organisms use to cope with thermal heterogeneity and to predict the consequences of thermal change for the diversity of communities.

Coupled thermal, structural and vibrational analysis of a hypersonic engine for flight test

This paper describes a relatively simple and quick method for implementing aerodynamic heating models into a finite element code for non-linear transient thermal-structural and thermal-structural-vibrational analyses of a Mach 10 generic HyShot scramjet engine. The thermal-structural-vibrational response of the engine was studied for the descent trajectory from 60 to 26 km. Aerodynamic heating fluxes, as a function of spatial position and time for varying trajectory points, were implemented in the transient heat analysis. Additionally, the combined effect of varying dynamic pressure and thermal loads with altitude was considered. This aero-thermal-structural analysis capability was used to assess the temperature distribution, engine geometry distortion and yielding of the structural material due to aerodynamic heating during the descent trajectory, and for optimising the wall thickness, nose radius of leading edge, etc. of the engine intake. A structural vibration analysis was also performed following the aero-thermal-structural analysis to determine the changes in natural frequencies of the structural vibration modes that occur at the various temperatures associated with the descent trajectory. This analysis provides a unique and relatively simple design strategy for predicting and mitigating the thermal-structural-vibrational response of hypersonic engines. (C) 2006 Elsevier SAS. All rights reserved.

Short- and long-term consequences of thermal variation in the larval environment of anurans

To survive adverse or unpredictable conditions in the ontogenetic environment, many organisms retain a level of phenotypic plasticity that allows them to meet the challenges of rapidly changing conditions. Larval anurans are widely known for their ability to modify behaviour, morphology and physiological processes during development, making them an ideal model system for studies of environmental effects on phenotypic traits. Although temperature is one of the most important factors influencing the growth, development and metamorphic condition of larval anurans, many studies have failed to include ecologically relevant thermal fluctuations among their treatments. We compared the growth and age at metamorphosis of striped marsh frogs Limnodynastes peronii raised in a diurnally fluctuating thermal regime and a stable regime of the same mean temperature. We then assessed the long-term effects of the larval environment on the morphology and performance of post-metamorphic frogs. Larval L. peronii from the fluctuating treatment were significantly longer throughout development and metamorphosed about 5 days earlier. Frogs from the fluctuating group metamorphosed at a smaller mass and in poorer condition compared with the stable group, and had proportionally shorter legs. Frogs from the fluctuating group showed greater jumping performance at metamorphosis and less degradation in performance during a 10-week dormancy. Treatment differences in performance could not be explained by whole-animal morphological variation, suggesting improved contractile properties of the muscles in the fluctuating group.

Improved robust control of nonlinear stochastic systems using uncertain models

We introduce a technique for quantifying and then exploiting uncertainty in nonlinear stochastic control systems. The approach is suboptimal though robust and relies upon the approximation of the forward and inverse plant models by neural networks, which also estimate the intrinsic uncertainty. Sampling from the resulting Gaussian distributions of the inversion based neurocontroller allows us to introduce a control law which is demonstrably more robust than traditional adaptive controllers.

Examining the strategy development process through the lens of complex adaptive systems theory

The development of strategy remains a debate for academics and a concern for practitioners. Published research has focused on producing models for strategy development and on studying how strategy is developed in organisations. The Operational Research literature has highlighted the importance of considering complexity within strategic decision making; but little has been done to link strategy development with complexity theories, despite organisations and organisational environments becoming increasingly more complex. We review the dominant streams of strategy development and complexity theories. Our theoretical investigation results in the first conceptual framework which links an established Strategic Operational Research model, the Strategy Development Process model, with complexity via Complex Adaptive Systems theory. We present preliminary findings from the use of this conceptual framework applied to a longitudinal, in-depth case study, to demonstrate the advantages of using this integrated conceptual model. Our research shows that the conceptual model proposed provides rich data and allows for a more holistic examination of the strategy development process. © 2012 Operational Research Society Ltd. All rights reserved.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Evolutionary neural networks : models and applications

The scaling problems which afflict attempts to optimise neural networks (NNs) with genetic algorithms (GAs) are disclosed. A novel GA-NN hybrid is introduced, based on the bumptree, a little-used connectionist model. As well as being computationally efficient, the bumptree is shown to be more amenable to genetic coding lthan other NN models. A hierarchical genetic coding scheme is developed for the bumptree and shown to have low redundancy, as well as being complete and closed with respect to the search space. When applied to optimising bumptree architectures for classification problems the GA discovers bumptrees which significantly out-perform those constructed using a standard algorithm. The fields of artificial life, control and robotics are identified as likely application areas for the evolutionary optimisation of NNs. An artificial life case-study is presented and discussed. Experiments are reported which show that the GA-bumptree is able to learn simulated pole balancing and car parking tasks using only limited environmental feedback. A simple modification of the fitness function allows the GA-bumptree to learn mappings which are multi-modal, such as robot arm inverse kinematics. The dynamics of the 'geographic speciation' selection model used by the GA-bumptree are investigated empirically and the convergence profile is introduced as an analytical tool. The relationships between the rate of genetic convergence and the phenomena of speciation, genetic drift and punctuated equilibrium arc discussed. The importance of genetic linkage to GA design is discussed and two new recombination operators arc introduced. The first, linkage mapped crossover (LMX) is shown to be a generalisation of existing crossover operators. LMX provides a new framework for incorporating prior knowledge into GAs.Its adaptive form, ALMX, is shown to be able to infer linkage relationships automatically during genetic search.

Effects of oxidative stress and neuroprotection in apoptosis in neuronal cell models

The PC12 and SH-SY5Y cell models have been proposed as potentially realistic models to investigate neuronal cell toxicity. The effects of oxidative stress (OS) caused by both H2O2 and Aβ on both cell models were assessed by several methods. Cell toxicity was quantitated by measuring cell viability using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium (MTT) viability assay, an indicator of the integrity of the electron transfer chain (ETC), and cell morphology by fluorescence and video microscopy, both of which showed OS to cause decreased viability and changes in morphology. Levels of intracellular peroxide production, and changes in glutathione and carbonyl levels were also assessed, which showed OS to cause increases in intracellular peroxide production, glutathione and carbonyl levels. Differentiated SH-SY5y cells were also employed and observed to exhibit the greatest sensitivity to toxicity. The neurotrophic factor, nerve growth factor (NGF) was shown to cause protection against OS. Cells pre-treated with NGF showed higher viability after OS, generally less apoptotic morphology, recorded less apoptotic nucleiods, generally lower levels of intracellular peroxides and changes in gene expression. The neutrophic factor, brain derived growth factor (BDNF) and ascorbic acid (AA) were also investigated. BDNF showed no specific neuroprotection, however the preliminary data does warrant further investigation. AA showed a 'janus face' showing either anti-oxidant action and neuroprotection or pro-oxidant action depending on the situation. Results showed that the toxic effects of compounds such as Aβ and H2O2 are cell type dependent, and that OS alters glutathione metabolism in neuronal cells. Following toxic insult, glutathione levels are depleted to low levels. It is herein suggested that this lowering triggers an adaptive response causing alterations in glutathione metabolism as assessed by evaluation of glutathione mRNA biosynthetic enzyme expression and the subsequent increase in glutathione peroxidase (GPX) levels.