Correlations from ion-pairing and the Nernst-Einstein equation

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

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

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

Lithium isotopes in large rivers reveal the cannibalistic nature of modern continental weathering and erosion

The erosion of major mountain ranges is thought to be largely cannibalistic, recycling sediments that were deposited in the ocean or on the continents prior to mountain uplift. Despite this recognition, it has not yet been possible to quantify the amount of recycled material that is presently transported by rivers to the ocean. Here, we have analyzed the Li content and isotope composition (View the MathML source) of suspended sediments sampled along river depth profiles and bed sands in three of the largest Earth's river systems (Amazon, Mackenzie and Ganga–Brahmaputra rivers). The View the MathML source values of river-sediments transported by these rivers range from +5.3 to −3.6‰ and decrease with sediment grain size. We interpret these variations as reflecting a mixture of unweathered rock fragments (preferentially transported at depth in the coarse fraction) and present-day weathering products (preferentially transported at the surface in the finest fraction). Only the finest surface sediments contain the complementary reservoir of Li solubilized by water–rock interactions within the watersheds. Li isotopes also show that river bed sands can be interpreted as a mixture between unweathered fragments of igneous and sedimentary rocks. A mass budget approach, based on Li isotopes, Li/Al and Na/Al ratios, solved by an inverse method allows us to estimate that, for the large rivers analyzed here, the part of solid weathering products formed by present-day weathering reactions and transported to the ocean do not exceed 35%. Li isotopes also show that the sediments transported by the Amazon, Mackenzie and Ganga–Brahmaputra river systems are mostly sourced from sedimentary rocks (>60%) rather than igneous rocks. This study shows that Li isotopes in the river particulate load are a good proxy for quantifying both the erosional rock sources and the fingerprint of present-day weathering processes. Overall, Li isotopes in river sediments confirm the cannibalistic nature of erosion and weathering

Efficient organic carbon burial in the Bengal fan sustained by the Himalayan erosional system

Author Posting. © Nature Publishing Group, 2007. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 450 (2007): 407-410, doi:10.1038/nature06273.Continental erosion controls atmospheric carbon dioxide levels on geological timescales through silicate weathering, riverine transport and subsequent burial of organic carbon in oceanic sediments. The efficiency of organic carbon deposition in sedimentary basins is however limited by the organic carbon load capacity of the sediments and organic carbon oxidation in continental margins. At the global scale, previous studies have suggested that about 70 per cent of riverine organic carbon is returned to the atmosphere, such as in the Amazon basin. Here we present a comprehensive organic carbon budget for the Himalayan erosional system, including source rocks, river sediments and marine sediments buried in the Bengal fan. We show that organic carbon export is controlled by sediment properties, and that oxidative loss is negligible during transport and deposition to the ocean. Our results indicate that 70 to 85 per cent of the organic carbon is recent organic matter captured during transport, which serves as a net sink for atmospheric carbon dioxide. The amount of organic carbon deposited in the Bengal basin represents about 10 to 20 per cent of the total terrestrial organic carbon buried in oceanic sediments. High erosion rates in the Himalayas generate high sedimentation rates and low oxygen availability in the Bay of Bengal that sustain the observed extreme organic carbon burial efficiency. Active orogenic systems generate enhanced physical erosion and the resulting organic carbon burial buffers atmospheric carbon dioxide levels, thereby exerting a negative feedback on climate over geological timescales

A cloud platform for automating and sharing analysis of raw simulation data from high throughput polymer molecular dynamics simulations

Open material databases storing hundreds of thousands of material structures and their corresponding properties have become the cornerstone of modern computational materials science. Yet, the raw outputs of the simulations, such as the trajectories from molecular dynamics simulations and charge densities from density functional theory calculations, are generally not shared due to their huge size. In this work, we describe a cloud-based platform to facilitate the sharing of raw data and enable the fast post-processing in the cloud to extract new properties defined by the user. As an initial demonstration, our database currently includes 6286 molecular dynamics trajectories for amorphous polymer electrolytes and 5.7 terabytes of data. We create a public analysis library at https://github.com/TRI-AMDD/htp_md to extract multiple properties from the raw data, using both expert designed functions and machine learning models. The analysis is run automatically with computation in the cloud, and results then populate a database that can be accessed publicly. Our platform encourages users to contribute both new trajectory data and analysis functions via public interfaces. Newly analyzed properties will be incorporated into the database. Finally, we create a front-end user interface at https://www.htpmd.matr.io for browsing and visualization of our data. We envision the platform to be a new way of sharing raw data and new insights for the computational materials science community.Comment: 21 pages, 7 figure

Stable isotopic composition of upper oceanic crust formed at a fast spreading ridge, ODP Site 801

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94808/1/ggge303.pd

Heat and charge transport in H2O at ice-giant conditions from ab initio molecular dynamics simulations

The impact of the inner structure and thermal history of planets on their observable features, such as luminosity or magnetic field, crucially depends on the poorly known heat and charge transport properties of their internal layers. The thermal and electric conductivities of different phases of water (liquid, solid, and super-ionic) occurring in the interior of ice giant planets, such as Uranus or Neptune, are evaluated from equilibrium ab initio molecular dynamics, leveraging recent progresses in the theory and data analysis of transport in extended systems. The implications of our findings on the evolution models of the ice giants are briefly discussed

Spatial correlation bias in late-Cenozoic erosion histories derived from thermochronology

International audienceThe potential link between erosion rates at the Earth's surface and changes in global climate has intrigued geoscientists for decades1,2 because such a coupling has implications for the influence of silicate weathering3,4 and organic-carbon burial5 on climate and for the role of Quaternary glaciations in landscape evolution1,6. A global increase in late-Cenozoic erosion rates in response to a cooling, more variable climate has been proposed on the basis of worldwide sedimentation rates7. Other studies have indicated, however, that global erosion rates may have remained steady, suggesting that the reported increases in sediment-accumulation rates are due to preservation biases, depositional hiatuses and varying measurement intervals8-10. More recently, a global compilation of thermochronology data has been used to infer a nearly twofold increase in the erosion rate in mountainous landscapes over late-Cenozoic times6. It has been contended that this result is free of the biases that affect sedimentary records11, although others have argued that it contains biases related to how thermochronological data are averaged12 and to erosion hiatuses in glaciated landscapes13. Here we investigate the 30 locations with reported accelerated erosion during the late Cenozoic6. Our analysis shows that in 23 of these locations, the reported increases are a result of a spatial correlation bias—that is, combining data with disparate exhumation histories, thereby converting spatial erosion-rate variations into temporal increases. In four locations, the increases can be explained by changes in tectonic boundary conditions. In three cases, climatically induced accelerations are recorded, driven by localized glacial valley incision. Our findings suggest that thermochronology data currently have insufficient resolution to assess whether late-Cenozoic climate change affected erosion rates on a global scale. We suggest that a synthesis of local findings that include location-specific information may help to further investigate drivers of global erosion rates