Paolo Pegolo^1*, Enrico Drigo^2*, Federico Grasselli^3,4*, Stefano Baroni^2*

1 COSMO—Laboratory of Computational Science and Modelling, IMX, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland

2 SISSA—Scuola Internazionale Superiore di Studi Avanzati, 34136 Trieste, Italy

3 Department of Physics, Informatics and Mathematics, Università degli Studi di Modena e Reggio Emilia, 41125 Modena, Italy

4 CNR-Nano S3—Istituto Nanoscienze, 41125 Modena, Italy

* Corresponding authors emails: paolo.pegolo@epfl.ch, endrigo@sissa.it, federico.grasselli@unimore.it, baroni@sissa.it

DOI10.24435/materialscloud:hf-ar [version v1]

Publication date: Jan 23, 2025

How to cite this record

Paolo Pegolo, Enrico Drigo, Federico Grasselli, Stefano Baroni, Transport coefficients from equilibrium molecular dynamics, Materials Cloud Archive 2025.18 (2025), https://doi.org/10.24435/materialscloud:hf-ar

Description

The determination of transport coefficients through the time-honoured Green-Kubo theory of linear response and equilibrium molecular dynamics requires significantly longer simulation times than those of equilibrium properties, while being further hindered by the lack of well-established data-analysis techniques to evaluate the statistical accuracy of the results. Leveraging recent advances in the spectral analysis of the current time series associated to molecular trajectories, we introduce a new method to estimate the full (diagonal as well as off-diagonal) Onsager matrix of transport coefficients from a single statistical model. This approach, based on the knowledge of the statistical distribution of the Onsager-matrix samples in the frequency domain, unifies the evaluation of diagonal (conductivities and viscosities) and off-diagonal (e.g., thermoelectric) transport coefficients within a comprehensive framework, significantly improving the reliability of transport coefficient estimation for materials ranging from molten salts to solid-state electrolytes. We validate the accuracy of this method against existing approaches using benchmark data on molten cesium fluoride and liquid water, and conclude our presentation with the computation of various transport coefficients of the Li₃PS₄ solid-state electrolyte.

Materials Cloud sections using this data

Files

File name	Size	Description
README.md MD5md5:bc7e84c614b4334e0f6b480ad524e6f7	3.4 KiB	Explanation of the structure of the archive and its content
environment.yaml MD5md5:82bfa8a603d9fe586d50a9c9761ad2d9	343 Bytes	Conda environment file to set up a python environment to reproduce the calculations.
scripts.zip MD5md5:57abb5afba3f5995f26cb9ded689ecbe	8.7 KiB	Folder with python scripts to perform data analysis (it contains a dedicated README)
NEP.zip MD5md5:e2cd7273b19f383788a52ef7f7210b8a	127.1 MiB	Input files to train the NEP model for Li3PS4 (it contains a dedicated README)
EMD.zip MD5md5:b46639efbb0fc08cab67a8aa2c58ed38	1.6 MiB	GPUMD input files to run MD simulations of Li3PS4 with the NEP model (it contains a dedicated README)
validation.zip MD5md5:0b84c469df29cf9f143492897ca00168	275.0 MiB	Data used to benchmark the methodology developed in the manuscript (it contains a dedicated README)
postprocess.zip MD5md5:1a73c8dbb538e03919d3479a04427833	7.4 KiB	Folder with the data obtained after postprocessing MD simulations with the python scripts contained in `scripts` (it contains a dedicated README)
transportwithdensities.zip MD5md5:50e803f60f78fdd440bccd7eee7fa3d5	48.5 KiB	Python package to compute partial enthalpies
reproduce_figures.zip MD5md5:79004101334e942eec0551ad6966fd12	13.0 KiB	Python scripts to reproduce the figures in the manuscript
figures.zip MD5md5:66ab73f02db7f98648ebc9320aef58be	1.3 MiB	Folder with the figures.

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.

External references

Keywords

transport molecular dynamics solid-state electrolytes thermoelectricity