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The use of inorganic solid-ionic conductors with a metal electrode, has been proposed as a way to increase energy density, decrease capacity loss and prevent failure from metal propagation. Current observations of Li-metal electrodes causing cell shorting in solid-state systems have been identified as main obstacles limiting the development of this technology. However, many aspects of the involved phenomenon have not been fully addressed theoretically. In this work, we derive a mathematical model of electrodeposition-induced plastic flow in metal/inorganic solid-conductor systems. We use a semi-analytical solution to derive pressure increase expressions at metal protrusions and assess the possibility of fracture. The results give flow solutions analogous to laminar channel flow. The solutions also show how taking into account a boundary traction potential from built up pressure, leads to ionic redistribution and effectively screens isolated flaws, making local current focusing an incomplete explanation for observed electrolyte fracture. We show that the boundary traction potential sets a maximum value for the pressure increase that can occur from deposition at an isolated flaw. We derive conditions under which fracture can occur, and quantify the role of ionic conductivity and electrolyte fracture toughness in extending safe operating regimes of solid-state electrolytes with metal electrodes.

Xi-cam is an extensible platform for data management, analysis and visualization. Xi-cam aims to provide a flexible and extensible approach to synchrotron data treatment as a solution to rising demands for high-volume/high-throughput processing pipelines. The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms. Plugins are available for SAXS/WAXS/GISAXS/GIWAXS, tomography and NEXAFS data. With Xi-cam's `advanced' mode, data processing steps are designed as a graph-based workflow, which can be executed live, locally or remotely. Remote execution utilizes high-performance computing or de-localized resources, allowing for the effective reduction of high-throughput data. Xi-cam's plugin-based architecture targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis. Xi-cam is open-source and cross-platform, and available for download on GitHub.

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