Analyze Results

The first analysis step is to check that the run reached a diffusive regime and that the reported transport quantities are stable enough for the scientific question.

Load The Result Table

import pandas as pd

results = pd.read_csv("results_NASICON_298K.csv.gz")
print(results.tail())

Common columns are:

  • time,

  • msd,

  • jump_diffusivity,

  • tracer_diffusivity,

  • conductivity,

  • havens_ratio,

  • correlation_factor.

Check Diffusive Behavior

Plot MSD against time:

import matplotlib.pyplot as plt

plt.plot(results["time"], results["msd"])
plt.xlabel("time / s")
plt.ylabel("MSD / Angstrom^2")
plt.show()

For reliable diffusivity, the production part of the trajectory should show an approximately linear MSD-time relation. If the curve is noisy or dominated by early transients, increase equilibration, production passes, or the number of independent runs.

Compare Transport Quantities

Tracer diffusivity follows individual ion motion. Jump diffusivity follows collective charge motion and is used for conductivity. The Haven ratio compares these two diffusivities and is sensitive to correlated motion.

Use the last part of the trajectory or averages over independent seeds rather than a single early sample.

Reproducibility Checklist

Record:

  • kMCpy version,

  • structure file or structure hash,

  • site_mapping,

  • event library,

  • model file,

  • initial occupations,

  • temperature and attempt frequency,

  • equilibration and production passes,

  • random seed strategy.

The Configuration and model files are designed to make this information easy to keep with the results.

Next: Units And Interoperability.