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Invariance principles in the theory and computation of transport coefficients

Federico Grasselli1*, Stefano Baroni2,3*

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

2 SISSA - Scuola Internazionale Superiore di Studi Avanzati, via Bonomea 265, 34136 Trieste, Italy

3 CNR - Istituto Officina dei Materiali @ SISSA, Trieste 34136, Italy

* Corresponding authors emails: federico.grasselli@epfl.ch, baroni@sissa.it
DOI10.24435/materialscloud:rp-cd [version v1]

Publication date: Jul 19, 2021

How to cite this record

Federico Grasselli, Stefano Baroni, Invariance principles in the theory and computation of transport coefficients, Materials Cloud Archive 2021.112 (2021), https://doi.org/10.24435/materialscloud:rp-cd

Description

In this work we elaborate on recently discovered invariance principles, according to which transport coefficients are, to a large extent, independent of the microscopic definition of the densities and currents of the conserved quantities being transported (energy, momentum, mass, charge). These invariance principles can be combined with new spectral analysis methods for the current time series to be fed into the Green-Kubo formula to obtain accurate estimates of transport coefficients from relatively short molecular dynamics simulations. In this record we collect the time series of the ab initio charge flux for a simulation of molten potassium chloride, together with the Jupyter Notebooks we employed to analyse the data and produce the figures in the related article.

Materials Cloud sections using this data

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Files

File name Size Description
Cepstral.ipynb
MD5md5:0e701d8fa74345e857f9c137e1110ab3
49.7 KiB Jupyter Notebook where the behaviour of cepstral analysis vs the number of retained cepstral coefficients is studied.
AnalysisPlot.ipynb
MD5md5:e1ce1cbdd6f5f59ef892be4cb4f1330b
187.6 KiB Jupyter Notebook where the Green-Kubo and Helfand-Einstein formulas are analysed to produce the plots displayed in the reference article.
GKHE_quant_40B.dat
MD5md5:d1939faec46e1e5d2cfada808cdfd42c
16.9 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux obtained from Born effective charge tensors. 40-block analysis.
GKHE_quant_120B.dat
MD5md5:be2ede71d59762d1753bfb64cbad400c
5.8 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux obtained from Born effective charge tensors. 120-block analysis.
GKHE_class_40B.dat
MD5md5:b06e48cd2eb1a1d287abd53ab41fcf37
16.9 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux obtained from oxidation numbers. 40-block analysis.
GKHE_class_120B.dat
MD5md5:46b5c192782f91f331851687af2003d1
5.7 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux obtained from oxidation numbers. 120-block analysis.
GKHE_diff_40B.dat
MD5md5:2135a1e077b4ceef41754c5ea73ec0db
17.5 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux difference. 40-block analysis.
GKHE_diff_120B.dat
MD5md5:90ecd240986d55ed4010cd617f310195
5.9 KiB Data file of Green-Kubo and Helfand-Einstein integrals of the autocorrelation function of the charge flux difference. 120-block analysis.
elclass.dat
MD5md5:abbb76a8bf1f8e6f859f80517454fb57
448.0 KiB Data file of the time series of the charge flux obtained from oxidation numbers.
elquant.dat
MD5md5:1b9e5c986bd05532329763f023db09e8
448.0 KiB Data file of the time series of the charge flux obtained from Born effective charge tensors.
diff.dat
MD5md5:244a62a3ef0d42e0588a69a94090dc99
448.2 KiB Data file of the time series of the difference between the mentioned charge fluxes.
README.txt
MD5md5:485a9d35d96cb4d53ccd61f593bcddcf
1.7 KiB Readme containing a more extensive description of the data as well as references to the code employed to perform the analysis.

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

Preprint (Preprint where the data is discussed)
Journal reference (Regular article where the data is discussed)
F. Grasselli, S. Baroni, The European Physical Journal B, in press (2021) doi:10.1140/epjb/s10051-021-00152-5

Keywords

transport molecular dynamics Green-Kubo MaX SNSF Marie Curie Fellowship

Version history:

2021.112 (version v1) [This version] Jul 19, 2021 DOI10.24435/materialscloud:rp-cd