13 research outputs found

    Magnon Heat Transport in (Sr,La)_14Cu_24O_41

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    We have measured the thermal heat conductivity kappa of the compounds Sr_14Cu_24O_41 and Ca_9La_5Cu_24O_41 containing doped and undoped spin ladders, respectively. We find a huge anisotropy of both, the size and the temperature dependence of kappa which we interpret in terms of a very large heat conductivity due to the magnetic excitations of the one-dimensional spin ladders. This magnon heat conductivity decreases with increasing hole doping of the ladders. The magnon heat transport is analyzed theoretically using a simple kinetic model. From this analysis we determine the spin gap and the temperature dependent mean free path of the magnons which ranges by several thousand angstroms at low temperature. The relevance of several scattering channels for the magnon transport is discussed.Comment: 6 pages, 5 figures, submitted to Phys. Rev.

    From thermal rectifiers to thermoelectric devices

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    We discuss thermal rectification and thermoelectric energy conversion from the perspective of nonequilibrium statistical mechanics and dynamical systems theory. After preliminary considerations on the dynamical foundations of the phenomenological Fourier law in classical and quantum mechanics, we illustrate ways to control the phononic heat flow and design thermal diodes. Finally, we consider the coupled transport of heat and charge and discuss several general mechanisms for optimizing the figure of merit of thermoelectric efficiency.Comment: 42 pages, 22 figures, review paper, to appear in the Springer Lecture Notes in Physics volume "Thermal transport in low dimensions: from statistical physics to nanoscale heat transfer" (S. Lepri ed.

    Utility of extrapolating human S1500+ genes to the whole transcriptome: tunicamycin case study

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    The TempO-Seq S1500+ platform(s), now available for human, mouse, rat, and zebrafish, measures a discrete number of genes that are representative of biological and pathway co-regulation across the entire genome in a given species. While measurement of these genes alone provides a direct assessment of gene expression activity, extrapolating expression values to the whole transcriptome (~26 000 genes in humans) can estimate measurements of non-measured genes of interest and increases the power of pathway analysis algorithms by using a larger background gene expression space. Here, we use data from primary hepatocytes of 54 donors that were treated with the endoplasmic reticulum (ER) stress inducer tunicamycin and then measured on the human S1500+ platform containing ~3000 representative genes. Measurements for the S1500+ genes were then used to extrapolate expression values for the remaining human transcriptome. As a case study of the improved downstream analysis achieved by extrapolation, the "measured only" and "whole transcriptome" (measured + extrapolated) gene sets were compared. Extrapolation increased the number of significant genes by 49%, bringing to the forefront many that are known to be associated with tunicamycin exposure. The extrapolation procedure also correctly identified established tunicamycin-related functional pathways reflected by coordinated changes in interrelated genes while maintaining the sample variability observed from the "measured only" genes. Extrapolation improved the gene- and pathway-level biological interpretations for a variety of downstream applications, including differential expression analysis, gene set enrichment pathway analysis, DAVID keyword analysis, Ingenuity Pathway Analysis, and NextBio correlated compound analysis. The extrapolated data highlight the role of metabolism/metabolic pathways, the ER, immune response, and the unfolded protein response, each of which are key activities associated with tunicamycin exposure that were unrepresented or underrepresented in one or more of the analyses of the original "measured only" dataset. Furthermore, the inclusion of the extrapolated genes raised "tunicamycin" from third to first upstream regulator in Ingenuity Pathway Analysis and from sixth to second most correlated compound in NextBio analysis. Therefore, our case study suggests an approach to extend and enhance data from the S1500+ platform for improved insight into biological mechanisms and functional outcomes of diseases, drugs, and other perturbations.Toxicolog
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