Physicochemical Characteristics of Cobalt Selenides & Their Catalytic Activities

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Magnetoresistance behavior of a ferromagnetic shape memory alloy: Ni_1.75Mn_1.25Ga

A negative-positive-negative switching behavior of magnetoresistance (MR) with temperature is observed in a ferromagnetic shape memory alloy Ni_1.75Mn_1.25Ga. In the austenitic phase between 300 and 120 K, MR is negative due to s-d scattering. Curiously, below 120K MR is positive, while at still lower temperatures in the martensitic phase, MR is negative again. The positive MR cannot be explained by Lorentz contribution and is related to a magnetic transition. Evidence for this is obtained from ab initio density functional theory, a decrease in magnetization and resistivity upturn at 120 K. Theory shows that a ferrimagnetic state with anti-ferromagnetic alignment between the local magnetic moments of the Mn atoms is the energetically favoured ground state. In the martensitic phase, there are two competing factors that govern the MR behavior: a dominant negative trend up to the saturation field due to the decrease of electron scattering at twin and domain boundaries; and a weaker positive trend due to the ferrimagnetic nature of the magnetic state. MR exhibits a hysteresis between heating and cooling that is related to the first order nature of the martensitic phase transition.Comment: 17 pages, 5 figures. Accepted in Phys. Rev.

Flows on Graphs with Random Capacities

We investigate flows on graphs whose links have random capacities. For binary trees we derive the probability distribution for the maximal flow from the root to a leaf, and show that for infinite trees it vanishes beyond a certain threshold that depends on the distribution of capacities. We then examine the maximal total flux from the root to the leaves. Our methods generalize to simple graphs with loops, e.g., to hierarchical lattices and to complete graphs.Comment: 8 pages, 6 figure

Energy balance simulation of a wheat canopy using the RZ-SHAW (RZWQM-SHAW) model

RZ-SHAW is a new hybrid model coupling the Root Zone Water Quality Model (RZWQM) and the Simultaneous Heat and Water (SHAW) model to extend RZWQM applications to conditions of frozen soil and crop residue cover. RZ-SHAW offers the comprehensive land management options of RZWQM with the additional capability to simulate diurnal changes in energy balance needed for simulating the near-surface microclimate and leaf temperature. The objective of this study was to evaluate RZ-SHAW for simulations of radiation balance and sensible and latent heat fluxes over plant canopies. Canopy energy balance data were collected at various growing stages of winter wheat in the North China Plain (36° 57'N, 116° 6'E, 28 m above sea level). RZ-SHAW and SHAW simulations using hourly meteorological data were compared with measured net radiation, latent heat flux, sensible heat flux, and soil heat flux. RZ-SHAW provided similar goodness-of-prediction statistics as the original SHAW model for all the energy balance components when using observed plant growth input data. The root mean square error (RMSE) for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 29.7, 30.7, 29.9, and 25.9 W m -2 for SHAW and 30.6, 32.9, 34.2, and 30.6 W m -2 for RZ-SHAW, respectively. Nash-Sutcliffe R 2 ranged from 0.67 for sensible heat flux to 0.98 for net radiation. Subsequently, an analysis was performed using the plant growth component of RZ-SHAW instead of inputting LAI and plant height. The model simulation results agreed with measured plant height, yield, and LAI very well. As a result, RMSE for the energy balance components were very similar to the original RZ-SHAW simulation, and latent, sensible, and soil heat fluxes were actually simulated slightly better. RMSE for simulated net radiation, latent heat, sensible heat, and soil heat fluxes was 31.5, 30.4, 30.2, and 27.6 W m -2, respectively. Overall, the results demonstrated a successful coupling of RZWQM and SHAW in terms of canopy energy balance simulation, which has important implications for prediction of crop growth, crop water stress, and irrigation scheduling

Optimal Paths in Complex Networks with Correlated Weights: The World-wide Airport Network

We study complex networks with weights, $w_{ij}$, associated with each link connecting node $i$ and $j$. The weights are chosen to be correlated with the network topology in the form found in two real world examples, (a) the world-wide airport network, and (b) the {\it E. Coli} metabolic network. Here $w_{ij} \sim x_{ij} (k_i k_j)^\alpha$, where $k_i$ and $k_j$ are the degrees of nodes $i$ and $j$, $x_{ij}$ is a random number and $\alpha$ represents the strength of the correlations. The case $\alpha > 0$ represents correlation between weights and degree, while $\alpha < 0$ represents anti-correlation and the case $\alpha = 0$ reduces to the case of no correlations. We study the scaling of the lengths of the optimal paths, $\ell_{\rm opt}$, with the system size $N$ in strong disorder for scale-free networks for different $\alpha$. We calculate the robustness of correlated scale-free networks with different $\alpha$, and find the networks with $\alpha < 0$ to be the most robust networks when compared to the other values of $\alpha$. We propose an analytical method to study percolation phenomena on networks with this kind of correlation. We compare our simulation results with the real world-wide airport network, and we find good agreement

Maximum flow and topological structure of complex networks

The problem of sending the maximum amount of flow $q$ between two arbitrary nodes $s$ and $t$ of complex networks along links with unit capacity is studied, which is equivalent to determining the number of link-disjoint paths between $s$ and $t$. The average of $q$ over all node pairs with smaller degree $k_{\rm min}$ is $_{k_{\rm min}} \simeq c k_{\rm min}$ for large $k_{\rm min}$ with $c$ a constant implying that the statistics of $q$ is related to the degree distribution of the network. The disjoint paths between hub nodes are found to be distributed among the links belonging to the same edge-biconnected component, and $q$ can be estimated by the number of pairs of edge-biconnected links incident to the start and terminal node. The relative size of the giant edge-biconnected component of a network approximates to the coefficient $c$. The applicability of our results to real world networks is tested for the Internet at the autonomous system level.Comment: 7 pages, 4 figure

Structure and function in flow networks

Peer reviewedPublisher PD