Thermo-physical properties of paraffin wax with iron oxide nanoparticles as phase change material for heat storage applications

Phase change materials (PCMs) are growing in importance in many thermal applications as heat storage or to smooth the energy peak demand in many technological fields in industrial as well as in civil applications. Conductive nanoparticles can be added to phase change material to improve their thermo-physical properties. In this work, Iron oxide nanoparticles (IOx-NPs) were synthesized using a simple and green synthesis method, free of toxic and harmful solvents, using the extract of a plant as a reducer and stabilizer at two different temperatures of calcination 500°C and 750°C. The metallic oxide was used as an additive with 2% wt. compositions to paraffin wax to prepare a nanocomposite. The variation in thermal properties of paraffin wax in the composite was experimentally investigated. The biosynthesized IOx-NPs were characterized by X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope (SEM) and Thermal Gravimetric Analysis (TGA) techniques. The thermal properties of the synthesized nanocomposites were characterized by a thermal conductivity analyzer and differential scanning calorimetry (DSC). The FTIR spectra showed a bond at 535 cm-1, which confirms the Fe-O vibration. The XRD powder analysis revealed the formation of the cubic phase of Fe3O4 with an average particle size of 11 nm at 500°C and the presence of the phase α-Fe2O3 with Fe3O4 at 750°C. Scanning Electron Microscopy (SEM) showed that the obtained oxide was made up of particles of nanoscale size. Experimental measurements showed that the presence of nanoparticles can improve the latent heat capacity by a maximum of 16.16 % and the thermal conductivity of the nanocomposites by a maximum of 16.99%

Oscillations in a maturation model of blood cell production.

We present a mathematical model of blood cell production which describes both the development of cells through the cell cycle, and the maturation of these cells as they differentiate to form the various mature blood cell types. The model differs from earlier similar ones by considering primitive stem cells as a separate population from the differentiating cells, and this formulation removes an apparent inconsistency in these earlier models. Three different controls are included in the model: proliferative control of stem cells, proliferative control of differentiating cells, and peripheral control of stem cell committal rate. It is shown that an increase in sensitivity of these controls can cause oscillations to occur through their interaction with time delays associated with proliferation and differentiation, respectively. We show that the characters of these oscillations are quite distinct and suggest that the model may explain an apparent superposition of fast and slow oscillations which can occur in cyclical neutropenia. © 2006 Society for Industrial and Applied Mathematics

Superconductivity in monolayer and few-layer graphene: I. Review of possible pairing symmetries and basic electronic properties

We review all symmetry-allowed spin-singlet and spin-triplet superconducting (SC) order parameters in graphene ($s$-wave, $d$-wave, $p$-wave, and $f$-wave) generated by generic onsite, nearest-neighbor (NN), and next-to-nearest-neighbor (NNN) pairing interactions in a tight-binding model. For each pairing channel, we calculate both the band structure and the dependence of the density of states on energy, chemical potential, and on the pairing strength. In particular, we distinguish between nodal superconducting states and fully gapped states and study the dependence of gap closing points on the chemical potential and the superconducting pairing strength. We further investigate the difference between mono-, bi-, and tri-layer ABC and ABA graphene, including accounting for the effects of trigonal warping

Coupling climate and economic models in a cost-benefit framework: a convex optimization approach

In this paper we present a general method, based on a convex optimisation technique, that facilitates the coupling of climate and economic models in a cost-benefit framework. As a demonstration of the method, we couple an economic growth model à la Ramsey adapted from DICE-99 with an efficient intermediate complexity climate model, C-GOLDSTEIN, which has highly simplified physics, but fully 3-D ocean dynamics. As in DICE-99 we assume that an economic cost is associated with global temperature change: this change is obtained from the climate model which is driven by the GHG concentrations computed from the economic growth path. The work extends a previous paper in which these models were coupled in cost-effectiveness mode. Here we consider the more intricate cost-benefit coupling in which the climate impact is not fixed a priori. We implement the coupled model using an oracle-based optimisation technique. Each model is contained in an oracle which supplies model output and information on its sensitivity to a master program. The algorithm Proximal-ACCPM guarantees the convergence of the procedure under sufficient convexity assumptions. Our results demonstrate the possibility of a consistent, cost-benefit, climate-damage optimisation analysis with a 3-D climate model

Resource Competition on Integral Polymatroids

We study competitive resource allocation problems in which players distribute their demands integrally on a set of resources subject to player-specific submodular capacity constraints. Each player has to pay for each unit of demand a cost that is a nondecreasing and convex function of the total allocation of that resource. This general model of resource allocation generalizes both singleton congestion games with integer-splittable demands and matroid congestion games with player-specific costs. As our main result, we show that in such general resource allocation problems a pure Nash equilibrium is guaranteed to exist by giving a pseudo-polynomial algorithm computing a pure Nash equilibrium.Comment: 17 page

Superconductivity in monolayer and few-layer graphene: II. Topological edge states and Chern numbers

We study the emergence of electronic edge states in superconducting (SC) monolayer, bilayer, and trilayer graphene for both spin-singlet and spin-triplet SC order parameters. We focus mostly on the gapped chiral $p+ip'$- and $d+id'$-wave SC states that show a non-zero Chern number and a corresponding number of edge states. For the $p+ip'$-wave state, we observe a rich Chern phase diagram when tuning the chemical potential and the SC order parameter amplitudes, which depends strongly on the number of layers and their stacking, and is also modified by trigonal warping. At small parameter values we observe a region whose Chern number is unique to rhombohedrally stacked graphene, and is independent of the number of layers. Our results can be understood in relation not only to the SC order parameter winding as expected, but also to the normal state band structure. This observation establishes the importance of the normal state characteristics for understanding the topology in SC graphene systems

One-Parameter GHG Emission Policy with R&D-based Growth

This document examines the GHG emission policy of regions which use land, labor and emitting inputs in production and enhance their productivity by devoting labor to R&D, but with different endowments and technology. The regions also have different impacts on global pollution. The problem is to organize common emission policy, if the regions cannot form a federation with a common budget and the policy parameters must be uniform for all regions. The results are the following. If a self-interested central planner allocate emission caps in fixed proportion to past emissions (i.e. grandfathering), then it establishes the Pareto optimum, decreasing emissions and promoting R&D and economic growth

Rhythmic dynamics and synchronization via dimensionality reduction : application to human gait

Reliable characterization of locomotor dynamics of human walking is vital to understanding the neuromuscular control of human locomotion and disease diagnosis. However, the inherent oscillation and ubiquity of noise in such non-strictly periodic signals pose great challenges to current methodologies. To this end, we exploit the state-of-the-art technology in pattern recognition and, specifically, dimensionality reduction techniques, and propose to reconstruct and characterize the dynamics accurately on the cycle scale of the signal. This is achieved by deriving a low-dimensional representation of the cycles through global optimization, which effectively preserves the topology of the cycles that are embedded in a high-dimensional Euclidian space. Our approach demonstrates a clear advantage in capturing the intrinsic dynamics and probing the subtle synchronization patterns from uni/bivariate oscillatory signals over traditional methods. Application to human gait data for healthy subjects and diabetics reveals a significant difference in the dynamics of ankle movements and ankle-knee coordination, but not in knee movements. These results indicate that the impaired sensory feedback from the feet due to diabetes does not influence the knee movement in general, and that normal human walking is not critically dependent on the feedback from the peripheral nervous system

Study of the effect of EAFD in polymer composites usig DoE

This study assesses the processing behaviour and mechanical properties of different polymers widely used in several industry fields formulated with Electric Arc Furnace Dust (EAFD) as filler. Design of Experiments (DoE) has been proved to be an effective tool to obtain the maximum information with the minimum number of experiments. In this experimental design mechanical properties as well as the melt flow index were chosen as dependent variables. The effect of CaCO3, BaSO4 and EAFD fillers as well as different polymer matrix has been evaluated.Peer ReviewedPostprint (published version