sarkas.tools.transport.InterDiffusion#

class sarkas.tools.transport.InterDiffusion[source]#

The interdiffusion coefficient is calculated from the Green-Kubo formula

\[D_{\alpha} = \frac{1}{3Nx_1x_2} \int_0^\tau dt \langle \mathbf {J}_{\alpha}(0) \cdot \mathbf {J}_{\alpha}(t) \rangle,\]

where \(x_{1,2}\) are the concentration of the two species and \(\mathbf {J}_{\alpha}(t)\) is the diffusion current calculated by the sarkas.tools.observables.DiffusionFlux class.

Data is retrievable at dataframe and dataframe_slices.

Methods

InterDiffusion.__init__()

InterDiffusion.calculate_average_temperature(params)

Calculate the average temperature from the sarkas.tools.observables.Thermodynamics data.

InterDiffusion.compute(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula

InterDiffusion.copy_params(params)

InterDiffusion.create_df_filenames()

Create paths of the filenames of the dataframes.

InterDiffusion.diffusion(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula.

InterDiffusion.electrical_conductivity(...)

Calculate the transport coefficient from the Green-Kubo formula.

InterDiffusion.get_observable_data(observable)

Grab the autocorrelation function datasets by calling the observable's parse() method.

InterDiffusion.initialize_dataframes(observable)

Grab observables autocorrelation data and initialize the dataframes where to store the data.

InterDiffusion.interdiffusion(observable[, ...])

Calculate the transport coefficient from the Green-Kubo formula

InterDiffusion.make_directories()

Create directories where to save the transport coefficients.

InterDiffusion.parse(observable)

Read the HDF files containing the transport coefficients.

InterDiffusion.plot(observable[, display_plot])

Make a dual plot comparing the ACF and the Transport Coefficient by using the plot_tc() method.

InterDiffusion.plot_tc(time, acf_data, ...)

Make dual plots with ACF and transport coefficient.

InterDiffusion.pretty_print()

InterDiffusion.pretty_print_msg()

Print to screen the location where data is stored and other relevant information.

InterDiffusion.save_hdf()

Save the HDF dataframes to disk in the TransportCoefficient folder.

InterDiffusion.setup(params, observable)

Parameters

InterDiffusion.time_stamp(message, timing)

Print out to screen elapsed times.

InterDiffusion.viscosity(observable[, plot, ...])

Calculate the transport coefficient from the Green-Kubo formula