Effects of boundary conditions on magnetization switching in kinetic Ising models of nanoscale ferromagnets

Magnetization switching in highly anisotropic single-domain ferromagnets has been previously shown to be qualitatively described by the droplet theory of metastable decay and simulations of two-dimensional kinetic Ising systems with periodic boundary conditions. In this article we consider the effects of boundary conditions on the switching phenomena. A rich range of behaviors is predicted by droplet theory: the specific mechanism by which switching occurs depends on the structure of the boundary, the particle size, the temperature, and the strength of the applied field. The theory predicts the existence of a peak in the switching field as a function of system size in both systems with periodic boundary conditions and in systems with boundaries. The size of the peak is strongly dependent on the boundary effects. It is generally reduced by open boundary conditions, and in some cases it disappears if the boundaries are too favorable towards nucleation. However, we also demonstrate conditions under which the peak remains discernible. This peak arises as a purely dynamic effect and is not related to the possible existence of multiple domains. We illustrate the predictions of droplet theory by Monte Carlo simulations of two-dimensional Ising systems with various system shapes and boundary conditions.Comment: RevTex, 48 pages, 13 figure

Effect of working fluids on the performance of phase change material storage based direct vapor generation solar organic Rankine cycle system

Working fluids can play a critical role in the working of an organic Rankine cycle system. A direct vapor generation solar organic Rankine cycle embedded with phase change material storage is analyzed in this study. The system comprised of an array of evacuated flat plate collectors, phase change material based thermal storage, expander, condenser, and organic working fluid pump. The storage tank model is modeled using a finite difference method in MATLAB programming environment while the 1D model of ORC system is used to evaluate the system performance. After a careful screen, 12 dry and isentropic working fluids were selected and their impact on the performance of the heat storage tank and the overall system is evaluated. The results show that the system efficiencies increase and decrease with the increment and decrement in the critical temperature of the working fluid. Moreover, the rise and fall of working fluid temperature, phase change material temperature, and the quantity of energy stored and released generally increase with an increase in the critical temperature of the working fluid. At the evaporation temperature of 10 °C higher and lower than the melting point temperature of the phase change material, Benzene has achieved the highest system efficiencies of 10.7% & 10.4% during charging and discharging mode, respectively. However, the maximum the rise and fall of working fluid temperature, phase change material temperature, and the quantity of energy stored and released during charging and discharging mode is attained by Heptane which is found to be 5.35 °C & 7.34 °C, 0.48 °C & 0.44 °C and 13.81 MJ & 23.04 MJ, respectively. Heptane has shown overall best performance among the selected working fluids and found to be feasible for phase change material storage based direct vapor generation solar ORC system

Where Taxonomy Based on Subtle Morphological Differences Is Perfectly Mirrored by Huge Genetic Distances: DNA Barcoding in Protura (Hexapoda)

<div><p>Background</p><p>Protura is a group of tiny, primarily wingless hexapods living in soil habitats. Presently about 800 valid species are known. Diagnostic characters are very inconspicuous and difficult to recognize. Therefore taxonomic work constitutes an extraordinary challenge which requires special skills and experience. Aim of the present pilot project was to examine if DNA barcoding can be a useful additional approach for delimiting and determining proturan species.</p><p>Methodology and Principal Findings</p><p>The study was performed on 103 proturan specimens, collected primarily in Austria, with additional samples from China and Japan. The animals were examined with two markers, the DNA barcoding region of the mitochondrial COI gene and a fragment of the nuclear 28S rDNA (Divergent Domain 2 and 3). Due to the minuteness of Protura a modified non-destructive DNA-extraction method was used which enables subsequent species determination. Both markers separated the examined proturans into highly congruent well supported clusters. Species determination was performed without knowledge of the results of the molecular analyses. The investigated specimens comprise a total of 16 species belonging to 8 genera. Remarkably, morphological determination in all species exactly mirrors molecular clusters. The investigation revealed unusually huge genetic COI distances among the investigated proturans, both maximal intraspecific distances (0–21.3%), as well as maximal congeneric interspecifical distances (up to 44.7%).</p><p>Conclusions</p><p>The study clearly demonstrates that the tricky morphological taxonomy in Protura has a solid biological background and that accurate species delimitation is possible using both markers, COI and 28S rDNA. The fact that both molecular and morphological analyses can be performed on the same individual will be of great importance for the description of new species and offers a valuable new tool for biological and ecological studies, in which proturans have generally remained undetermined at species level.</p></div

Comparison of COI and 28S rDNA in species discrimination of the genera <i>Acerentomon</i> (<i>Aco</i>), <i>Acerentulus</i> (<i>Acu</i>) and <i>Acerella</i> (<i>Ace</i>).

<p>Mirrored NJ tree based on K2P distances of COI (left) and 28S (right). Bootstrap support (maximal support marked with full circles) derived from 5000 replicates. Color code for genera: <i>Acerentomon</i> = violet, <i>Ionescuellum</i> = green, <i>Acerentulus</i> = orange, <i>Acerella</i> = red, <i>Eosentomon</i> = blue; Austrian sample sites are coded with different icons: Leopoldsberg = square, Eichkogel = triangle, and Twimberger Graben = circle.</p

List of primer pairs and starting positions within the selected markers used in the present study.

<p>Reference sequence <i>Sinentomon erythranum</i> (NCBI accession number: NC015982), * indicates internal primers additionally used in some specimens.</p

K2P distances in COI among species of Protura collected in Austria.

<p>Species described by their maximal intraspecific (Max intra), and the range of the best intraspecific matches (Best intra), as well as the maximal congeneric interspecific distances (Max congen), the name of the best matching species (Best match), along with the range of their best interspecific distances (Best inter). In species, covered by a single representative, missing distances are marked by a short line. Species abbreviations as used in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090653#pone-0090653-t003" target="_blank">Tab. 3</a>.</p

List of morphologically determined species of Protura investigated in this study.

<p>Genus abbreviation: <i>Ace</i> = <i>Acerella</i>, <i>Aco</i> = <i>Acerentomon</i>, <i>Acu</i> = <i>Acerentulus, Eos</i> = <i>Eosentomon</i>, <i>Ion</i> = <i>Ionescuellum</i>; Locality abbreviation: LB = Leopoldsberg, TG = Twimberger Graben, EK = Eichkogel.</p

Comparison of COI and 28S rDNA in species discrimination of the genera <i>Ionescuellum</i> (<i>Ion</i>) and <i>Eosentomon</i> (<i>Eos</i>).

<p>NJ tree based on K2P distances of COI (left) and the mirrored 28S rDNA results (right). Bootstrap support (maximal support marked with full circles) derived from 5000 replicates is maximal for all species and polpulations. Color code for genera: <i>Acerentomon</i> = violet, <i>Ionescuellum</i> = green, <i>Acerentulus</i> = orange, <i>Acerella</i> = red, <i>Eosentomon</i> = blue; Austrian sample sites are coded with different icons: Leopoldsberg = square, Eichkogel = triangle, and Twimberger Graben = circle.</p

NJ tree based on K2P distances from 91 COI sequences of Protura.

<p>Newly sequenced specimens labeled with lab code number (HP), abbreviation for genus, and species name. Color code for genera: <i>Acerentomon</i> = violet, <i>Ionescuellum = </i>green, <i>Acerentulus</i> = orange, <i>Acerella</i> = red, <i>Eosentomon</i> = blue; Austrian sample sites are coded with different icons: Leopoldsberg = square, Eichkogel = triangle, and Twimberger Graben = circle. Bootstrap support (given below nodes) derived from 5000 replicates. Maximally supported clusters and subclusters are indicated by black dots. Genus abbreviations: <i>Aco</i> = <i>Acerentomon</i>, <i>Ion</i> = <i>Ionescuellum</i>, <i>Acu</i> = <i>Acerentulus</i>, <i>Ace</i> = <i>Acerella</i>, and <i>Eos</i> = <i>Eosentomon</i>.</p