795 research outputs found

    Correlations from ion-pairing and the Nernst-Einstein equation

    Full text link
    We present a new approximation to ionic conductivity well suited to dynamical atomic-scale simulations, based on the Nernst-Einstein equation. In our approximation, ionic aggregates constitute the elementary charge carriers, and are considered as non-interacting species. This approach conveniently captures the dominant effect of ion-ion correlations on conductivity, short range interactions in the form of clustering. In addition to providing better estimates to the conductivity at a lower computational cost than exact approaches, this new method allows to understand the physical mechanisms driving ion conduction in concentrated electrolytes. As an example, we consider Li+^+ conduction in poly(ethylene oxide), a standard solid-state polymer electrolyte. Using our newly developed approach, we are able to reproduce recent experimental results reporting negative cation transference numbers at high salt concentrations, and to confirm that this effect can be caused by a large population of negatively charged clusters involving cations

    Tho\u27 I\u27m Not The First To Call You Sweetheart (Please Let Me Be The Last)

    Get PDF
    https://digitalcommons.library.umaine.edu/mmb-vp/6591/thumbnail.jp

    Tho\u27 I\u27m Not The First To Call You Sweetheart (Please Let Me Be The Last)

    Get PDF
    https://digitalcommons.library.umaine.edu/mmb-vp/6590/thumbnail.jp

    We\u27re Going Over

    Get PDF
    https://digitalcommons.library.umaine.edu/mmb-vp/4087/thumbnail.jp

    We\u27re Going Over The Top.

    Get PDF
    https://digitalcommons.library.umaine.edu/mmb-vp/3400/thumbnail.jp

    Graph Dynamical Networks for Unsupervised Learning of Atomic Scale Dynamics in Materials

    Full text link
    Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in membranes, molten atoms at interfaces, etc., which are difficult to understand due to the complexity of local environments. In this work, we develop graph dynamical networks, an unsupervised learning approach for understanding atomic scale dynamics in arbitrary phases and environments from molecular dynamics simulations. We show that important dynamical information can be learned for various multi-component amorphous material systems, which is difficult to obtain otherwise. With the large amounts of molecular dynamics data generated everyday in nearly every aspect of materials design, this approach provides a broadly useful, automated tool to understand atomic scale dynamics in material systems.Comment: 25 + 7 pages, 5 + 3 figure

    It\u27s A Long Way Back To Mother\u27s Knee

    Get PDF
    https://digitalcommons.library.umaine.edu/mmb-vp/1928/thumbnail.jp

    Since They\u27re Playin\u27 Hawaiian Tunes In Dixie

    Get PDF
    Two men playing guitar under the tree and woman dancing with group of people watching in background; Photograph of Edah Delbridgehttps://scholarsjunction.msstate.edu/cht-sheet-music/11319/thumbnail.jp

    Differences in hearing acuity among “normal-hearing” young adults modulate the neural basis for speech comprehension

    Get PDF
    AbstractIn this paper, we investigate how subtle differences in hearing acuity affect the neural systems supporting speech processing in young adults. Auditory sentence comprehension requires perceiving a complex acoustic signal and performing linguistic operations to extract the correct meaning. We used functional MRI to monitor human brain activity while adults aged 18–41 years listened to spoken sentences. The sentences varied in their level of syntactic processing demands, containing either a subject-relative or object-relative center-embedded clause. All participants self-reported normal hearing, confirmed by audiometric testing, with some variation within a clinically normal range. We found that participants showed activity related to sentence processing in a left-lateralized frontotemporal network. Although accuracy was generally high, participants still made some errors, which were associated with increased activity in bilateral cingulo-opercular and frontoparietal attention networks. A whole-brain regression analysis revealed that activity in a right anterior middle frontal gyrus (aMFG) component of the frontoparietal attention network was related to individual differences in hearing acuity, such that listeners with poorer hearing showed greater recruitment of this region when successfully understanding a sentence. The activity in right aMFGs for listeners with poor hearing did not differ as a function of sentence type, suggesting a general mechanism that is independent of linguistic processing demands. Our results suggest that even modest variations in hearing ability impact the systems supporting auditory speech comprehension, and that auditory sentence comprehension entails the coordination of a left perisylvian network that is sensitive to linguistic variation with an executive attention network that responds to acoustic challenge.</jats:p
    • …
    corecore