Publication date: Feb 12, 2019
Molecular dynamics is a versatile and powerful method to study diffusion in solid-state ionic conductors, requiring minimal prior knowledge of equilibrium or transition states of the system's free energy surface. However, the analysis of trajectories for relevant but rare events, such as a jump of the diffusing mobile ion, is still rather cumbersome, requiring prior knowledge of the diffusive process in order to get meaningful results. In this work we present a novel approach to detect the relevant events in a diffusive system without assuming prior information regarding the underlying process. We start from a projection of the atomic coordinates into a landmark basis to identify the dominant features in a mobile ion's environment. Subsequent clustering in landmark space enables a discretization of any trajectory into a sequence of distinct states. As a final step, the use of the Smooth Overlap of Atomic Positions descriptor allows distinguishing between different environments in a straightforward way. We apply this algorithm to ten Li-ionic systems and conduct in-depth analyses of cubic Li7La3Zr2O12, tetragonal Li10GeP2S12, and the β-eucryptite LiAlSiO4. We compare our results to existing methods, underscoring strong points, weaknesses, and insights into the diffusive behavior of the ionic conduction in the materials investigated.
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File name | Size | Description |
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README.txt
MD5md5:e9514c5cfe2cc1fc63631e401e86eb24
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936 Bytes | The README contains information on the notebooks and some guidance on installing the necessary packages. |
unsupervised.tar.gz
MD5md5:1bd90db05d70cf4a88752f82deb07b91
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1.2 GiB | The compressed file contains two jupyter notebooks, and a subfolder with the necessary data, namely two molecular dynamics trajectories. The trajectories are saved in a custom format, but the raw data is also available in xyz-format. |
2019.0008/v1 (version v1) [This version] | Feb 12, 2019 | DOI10.24435/materialscloud:2019.0008/v1 |