Figures and show that the trends in the experimental data can be reproduced from the MD simulation, but this does not, in itself, provide insight into the nature of the motion. This can be most obviously obtained by analysis of the MD trajectories themselves (as discussed below), but it is also useful to parameterise the correlation functions derived from the MD trajectories in terms of simple restricted rotational diffusion, involving an effective correlation time, 𝜏 c,eff , and a generalised order parameter S 2 . Given the complexity of the potential surfaces, the correlation functions are not expected to be simple exponentials (ex-amples are shown in Figure of the Supplementary Information), but the general trends in 𝜏 c and S 2 , shown in the lower panels of Figure (and tabulated in Table of the Supplementary Information), are expected to be robust. Notably, both parameters vary with temperature. This clearly shows that simple jump-type models, which involve a fixed geometry (amplitude) motion, will not correctly describe the dynamics, even if plausible fits to the experimental data can be obtained (cf. Figure ). Moreover, the assumption that the correlation time is associated, via an Arrhenius-type relationship, to a thermally activated jump process is clearly incorrect for the acetone dynamics; the 𝜏 c,eff values are essentially independent of temperature over the range 200-300 K, rather it is the amplitude of motion (parameterised by S 2 ) that changes with temperature. This implies that the acetone dynamics has a strong librational character (only the amplitude and not the frequency of motion changes with temperature for barrierless motions).