Diffusion coefficients were computed from simulation trajectories using the Python package kinisi-1.0.0. This package implements a Bayesian regression scheme that obtains a statistically efficient estimate of the diffusion coefficient and predicts associated uncertainties. This approach parameterises a multivariate normal distribution that describes the ensemble of MSDs represented by the data. Markov-chain Monte Carlo sampling is then used to sample the posterior distribution of the self-diffusion coefficient, D * from the Einstein relation: