Mechanism for the Enhancement of the Oxygen Diffusivity by Cation Substitution in La_2–<i>x</i>Sr_<i>x</i>CuO₄

Ruddlesden–Popper oxides Ln2MO4 (Ln = La, Pr, Nd, Sm; M = Ni, Cu, Fe, Co, Mn) are one of the promising cathode materials for the intermediate temperature (500–750 °C) solid oxide fuel cell. The key property making them operate at relatively low temperatures is their higher oxygen diffusivity, but in general, it is a difficult task to balance it with the durability of the material. To establish guiding principles for systematic improvement, it is indispensable to understand the oxygen diffusion process at the atomic scale. For La2–xSrxCuO4, we used density functional theory calculations to identify major diffusion paths and the crucial factors affecting the diffusion of oxygen vacancies. We found that out-of-plane equatorial-to-apical oxygen site hopping is the bottleneck of oxygen diffusion. Sr substitutional doping not only facilitates the formation of oxygen vacancies, i.e., the number of diffusion carriers, but also affects the diffusivity by locally lowering the formation energy. Two competing effects of Sr, weakly trapping the oxygen vacancies and alleviating the bottleneck of the above hopping, are quantified using our realistic random walk simulation, and the resulting diffusion coefficients reveal that the latter dominates at all doping concentrations, but the effect is saturated at x ∼ 0.3

Composite information transfer.

<p>(A) The 18 countries are positioned according to their incoming and outgoing composite TE values. (B) The economic interactions among the European countries. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone-0051986-g007" target="_blank">Figure 7C–E</a> shows the composite TE values for seven countries (Germany, Indonesia, Italy, Japan, South Korea, the UK, and the USA) over three periods – (C) January 1994-December 1998 (60 months), (D) January 1999-December 2004 (72 months), and (E) January 2005-September 2009 (60 months).</p

Variable weights.

<p>This figure shows the calculated weights for all the variables of the 18 studied countries. Each 5×1 column shows the color-coded weights for each country’s variables. This plot was drawn with the base entropy set to zero.</p

Overview of proposed approach.

<p>The proposed approach consists of three major steps – (1) cross-variable network construction within each country, (2) international network construction, and (3) integration by building a composite network based on the international and cross-variable networks.</p

Domestic cross-variable networks.

<p>(A) Cross-variable networks for Brazil, and China, which are based on an 88-month time-series of the five variables and reveal the information transfer among the variables. (B) Cross-variable networks for all 18 countries in our study, superimposed in a single graph (the label of an edge indicates on which country’s cross-variable network the edge appears).</p

International networks.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone-0051986-g004" target="_blank">Figure 4A–C</a> shows the international networks for three continents – (A) Europe, (B) North and South America, and (C) Asia. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone-0051986-g004" target="_blank">Figure 4D-F</a> shows the outgoing TE values among the continents in terms of the five variables – (D) Asia and Europe, (E) the Americas and Europe, and (F) the Americas and Asia. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone-0051986-g004" target="_blank">Figure 4G</a> shows the influence that the G7 countries (Canada, France, Germany, Italy, Japan, the UK, and the USA) and China have on the other countries in our study.</p

Analysis of composite transfer entropy calculation.

<p>(A) To examine the effect of adjusting the base entropy (BE) on the resulting composite TE value, this plot depicts how the composite value varies as we change <i>ρ</i> with respect to four different BE levels (0.1, 1, 10, and 100). (B) Comparison between our approach and the integrative method proposed by Lee <i>et al</i>. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone.0051986-Lee1" target="_blank">[16]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051986#pone.0051986-Lee2" target="_blank">[17]</a> in computational biology. This plot demonstrates how the composite TE value is affected by its component TE value.</p

Transition Metal-Free Half-Metallicity in Two-Dimensional Gallium Nitride with a Quasi-Flat Band

Two-dimensional half-metallicity without a transition metal is an attractive attribute for spintronics applications. On the basis of first-principles calculation, we revealed that a two-dimensional gallium nitride (2D-GaN), which was recently synthesized between graphene and SiC or wurtzite GaN substrate, exhibits half-metallicity due to its half-filled quasi-flat band. We found that graphene plays a crucial role in stabilizing a local octahedral structure, whose unusually high density of states due to a flat band leads to a spontaneous phase transition to its half-metallic phase from normal metal. It was also found that its half-metallicity is strongly correlated to the in-plane lattice constants and thus subjected to substrate modification. To investigate the magnetic property, we simplified its magnetic structure with a two-dimensional Heisenberg model and performed Monte Carlo simulation. Our simulation estimated its Curie temperature (TC) to be ∼165 K under a weak external magnetic field, suggesting that transition metal-free 2D-GaN exhibiting p orbital-based half-metallicity can be utilized in future spintronics

International network between Germany and Italy.

<p>This figure shows an international influence network between Germany and Italy (the cross-variable networks of the two countries are overlaid). A node represents a macro-economic variable, and a directed edge connects two nodes representing the same variable for two countries, if there is a statistically significant information transfer between the two nodes.</p

Information transfer among three continent-areas.

<p>Information transfer among three continent-areas.</p