612 research outputs found

    The structural and functional integrity of peripheral nerves depends on the glial-derived signal desert hedgehog

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    We show that desert hedgehog ( dhh), a signaling molecule expressed by Schwann cells, is essential for the structural and functional integrity of the peripheral nerve. Dhh-null nerves display multiple abnormalities that affect myelinating and nonmyelinating Schwann cells, axons, and vasculature and immune cells. Myelinated fibers of these mice have a significantly increased ( more than two times) number of Schmidt-Lanterman incisures ( SLIs), and connexin 29, a molecular component of SLIs, is strongly upregulated. Crossing dhh-null mice with myelin basic protein ( MBP)-deficient shiverer mice, which also have increased SLI numbers, results in further increased SLIs, suggesting that Dhh and MBP control SLIs by different mechanisms. Unmyelinated fibers are also affected, containing many fewer axons per Schwann cell in transverse profiles, whereas the total number of unmyelinated axons is reduced by approximately one-third. In dhh-null mice, the blood-nerve barrier is permeable and neutrophils and macrophage numbers are elevated, even in uninjured nerves. Dhh-null nerves also lack the largest-diameter myelinated fibers, have elevated numbers of degenerating myelinated axons, and contain regenerating fibers. Transected dhh nerves degenerate faster than wild-type controls. This demonstrates that a single identified glial signal, Dhh, plays a critical role in controlling the integrity of peripheral nervous tissue, in line with its critical role in nerve sheath development ( Parmantier et al., 1999). The complexity of the defects raises a number of important questions about the Dhh-dependent cell-cell signaling network in peripheral nerves

    Combinatorial synthesis of oxysulfides in the lanthanum-bismuth-copper system

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    Establishing synthesis methods for a target material constitutes a grand challenge in materials research, which is compounded with use-inspired specifications on the format of the material. Solar photochemistry using thin film materials is a promising technology for which many complex materials are being proposed, and the present work describes application of combinatorial methods to explore the synthesis of predicted La–Bi–Cu oxysulfide photocathodes, in particular alloys of LaCuOS and BiCuOS. The variation in concentration of three cations and two anions in thin film materials, and crystallization thereof, is achieved by a combination of reactive sputtering and thermal processes including reactive annealing and rapid thermal processing. Composition and structural characterization establish composition-processing-structure relationships that highlight the breadth of processing conditions required for synthesis of LaCuOS and BiCuOS. The relative irreducibility of La oxides and limited diffusion indicate the need for high temperature processing, which conflicts with the temperature limits for mitigating evaporation of Bi and S. Collectively the results indicate that alloys of these phases will require reactive annealing protocols that are uniquely tailored to each composition, motivating advancement of dynamic processing capabilities to further automate discovery of synthesis routes

    Sharp lines in the absorption edge of EuTe and Pb0.1_{0.1}Eu0.9_{0.9}Te in high magnetic fields

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    The optical absorption spectra in the region of the \fd transition energies of epitaxial layers of of EuTe and \PbEuTe, grown by molecular beam epitaxy, were studied using circularly polarized light, in the Faraday configuration. Under \sigmam polarization a sharp symmetric absorption line (full width at half-maximum 0.041 eV) emerges at the low energy side of the band-edge absorption, for magnetic fields intensities greater than 6 T. The absorption line shows a huge red shift (35 meV/T) with increasing magnetic fields. The peak position of the absorption line as a function of magnetic field is dominated by the {\em d-f} exchange interaction of the excited electron and the \Euion spins in the lattice. The {\em d-f} exchange interaction energy was estimated to be JdfS=0.15±0.01J_{df}S=0.15\pm 0.01 eV. In \PbEuTe the same absorption line is detected, but it is broader, due to alloy disorder, indicating that the excitation is localized within a finite radius. From a comparison of the absorption spectra in EuTe and \PbEuTe the characteristic radius of the excitation is estimated to be 10\sim 10\AA.Comment: Journal of Physics: Condensed Matter (2004, at press

    Analyzing machine learning models to accelerate generation of fundamental materials insights

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    Machine learning for materials science envisions the acceleration of basic science research through automated identification of key data relationships to augment human interpretation and gain scientific understanding. A primary role of scientists is extraction of fundamental knowledge from data, and we demonstrate that this extraction can be accelerated using neural networks via analysis of the trained data model itself rather than its application as a prediction tool. Convolutional neural networks excel at modeling complex data relationships in multi-dimensional parameter spaces, such as that mapped by a combinatorial materials science experiment. Measuring a performance metric in a given materials space provides direct information about (locally) optimal materials but not the underlying materials science that gives rise to the variation in performance. By building a model that predicts performance (in this case photoelectrochemical power generation of a solar fuels photoanode) from materials parameters (in this case composition and Raman signal), subsequent analysis of gradients in the trained model reveals key data relationships that are not readily identified by human inspection or traditional statistical analyses. Human interpretation of these key relationships produces the desired fundamental understanding, demonstrating a framework in which machine learning accelerates data interpretation by leveraging the expertize of the human scientist. We also demonstrate the use of neural network gradient analysis to automate prediction of the directions in parameter space, such as the addition of specific alloying elements, that may increase performance by moving beyond the confines of existing data

    Bi Alloying into Rare Earth Double Perovskites Enhances Synthesizability and Visible Light Absorption

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    A high throughput combinatorial synthesis utilizing inkjet printing of precursor inks was used to rapidly evaluate Bi-alloying into double perovskite oxides for enhanced visible light absorption. The fast visual screening of photo image scans of the library plates identifies 4-metal oxide compositions displaying an increase in light absorption, which subsequent UV–vis spectroscopy indicates is due to bandgap reduction. Structural characterization by X-ray diffraction (XRD) and Raman spectroscopy demonstrates that the visually darker composition range contains Bi-alloyed Sm₂MnNiO₆ (double perovskite structure), of the form (Bi,Sm)₂MnNiO₆. Bi alloying not only increases the visible absorption but also facilitates crystallization of this structure at the relatively low annealing temperature of 615 °C. Investigation of additional seven combinations of a rare earth (RE) and a transition metal (TM) with Bi and Mn indicates that Bi-alloying on the RE site occurs with similar effect in the family of rare earth oxide double perovskites

    Enhanced Bulk Transport in Copper Vanadate Photoanodes Identified by Combinatorial Alloying

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    The impact of alloying on the performance of β-Cu₂V₂O₇ photoanodes was investigated using inkjet printing of composition libraries containing 1,809 Cu₂V₂O₇-based photoanodes. Six elements (Zr, Ca, Hf, Gd, La, and Lu) were alloyed and pairwise co-alloyed at concentrations up to 7 at % into Cu-rich, stoichiometric, and Cu-deficient host Cu₂V₂O₇. A 1.7-fold increase in oxygen evolution photocurrent in pH 9.2 electrolyte was obtained by alloying Ca into β-Cu₂V₂O₇. Experiments employing a hole scavenger to better characterize bulk charge separation and transport revealed a 2.2-fold increase in photoactivity via alloying with Hf, Zr, and La, which increased to 2.7-fold upon co-alloying these elements with Ca. Concurrent with increased photoactivity is substantially decreased photon absorption between 1.5 and 2 eV, a range reported to coincide with high exciton absorption in β-Cu₂V₂O₇, motivating further exploration of whether these co-alloy compositions may destabilize the excitonic state that appears to have limited performance to date

    Enhanced Bulk Transport in Copper Vanadate Photoanodes Identified by Combinatorial Alloying

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    The impact of alloying on the performance of β-Cu₂V₂O₇ photoanodes was investigated using inkjet printing of composition libraries containing 1,809 Cu₂V₂O₇-based photoanodes. Six elements (Zr, Ca, Hf, Gd, La, and Lu) were alloyed and pairwise co-alloyed at concentrations up to 7 at % into Cu-rich, stoichiometric, and Cu-deficient host Cu₂V₂O₇. A 1.7-fold increase in oxygen evolution photocurrent in pH 9.2 electrolyte was obtained by alloying Ca into β-Cu₂V₂O₇. Experiments employing a hole scavenger to better characterize bulk charge separation and transport revealed a 2.2-fold increase in photoactivity via alloying with Hf, Zr, and La, which increased to 2.7-fold upon co-alloying these elements with Ca. Concurrent with increased photoactivity is substantially decreased photon absorption between 1.5 and 2 eV, a range reported to coincide with high exciton absorption in β-Cu₂V₂O₇, motivating further exploration of whether these co-alloy compositions may destabilize the excitonic state that appears to have limited performance to date

    Suppression of carrier induced ferromagnetism by composition and spin fluctuations in diluted magnetic semiconductors

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    We suggest an approach to account for spatial (composition) and thermal fluctuations in "disordered" magnetic models (e.g. Heisenberg, Ising) with given spatial dependence of magnetic spin-spin interaction. Our approach is based on introduction of fluctuating molecular field (rather than mean field) acting between the spins. The distribution function of the above field is derived self-consistently. In general case this function is not Gaussian, latter asymptotics occurs only at sufficiently large spins (magnetic ions) concentrations nin_i. Our approach permits to derive the equation for a critical temperature TcT_c of ferromagnetic phase transition with respect to the above fluctuations. We apply our theory to the analysis of influence of composition fluctuations on TcT_c in diluted magnetic semiconductors (DMS) with RKKY indirect spin-spin interaction.Comment: 6 pages, 2 figure

    Neutrinoless double beta decay in seesaw models

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    We study the general phenomenology of neutrinoless double beta decay in seesaw models. In particular, we focus on the dependence of the neutrinoless double beta decay rate on the mass of the extra states introduced to account for the Majorana masses of light neutrinos. For this purpose, we compute the nuclear matrix elements as functions of the mass of the mediating fermions and estimate the associated uncertainties. We then discuss what can be inferred on the seesaw model parameters in the different mass regimes and clarify how the contribution of the light neutrinos should always be taken into account when deriving bounds on the extra parameters. Conversely, the extra states can also have a significant impact, cancelling the Standard Model neutrino contribution for masses lighter than the nuclear scale and leading to vanishing neutrinoless double beta decay amplitudes even if neutrinos are Majorana particles. We also discuss how seesaw models could reconcile large rates of neutrinoless double beta decay with more stringent cosmological bounds on neutrino masses.Comment: 34 pages, 5 eps figures and 1 axodraw figure. Final version published in JHEP. NME results available in Appendi
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