Multiple Time Scale Behaviors and Network Dynamics in Liquid Methanol

Abstract

Canonical ensemble molecular dynamics simulations of liquid methanol, modeled using a rigidbody, pair-additive potential, are used to compute static distributions and temporal correlations of tagged molecule potential energies as a means of characterising the liquid state dynamics. The static distribution of tagged molecule potential energies shows a clear multimodal structure with three distinct peaks, similar to those observed previously in water and liquid silica. The multimodality is shown to originate from electrostatic effects, but not from local, hydrogen-bond interactions. An interesting outcome of this study is the remarkable similarity in the tagged potential energy power spectra of methanol, water and silica, despite the differences in the underlying interactions and the dimensionality of the network. All three liquids show a distinct multiple time scale (MTS) regime with a 1/f α dependence with a clear positive correlation between the scaling exponent α and the diffusivity. The low-frequency limit of the MTS regime is determined by the frequency of crossover to white noise behaviour which occurs at approximately 0.1 cm −1 in the case of methanol under standard temperature and pressure conditions. The power spectral regime above 200 cm −1 in all three systems is dominated by resonances due to localised vibrations, such as librations. The correlation between α and the diffusivity in all three liquids appears to be related to the strength of the coupling between the localised motions and the larger length/time-scale network reorganizations. Thus the time scales associated with network reorganization dynamics appear to be qualitatively similar in these systems, despite the fact that water and silica both display diffusional anomalies but methanol does not.

2D IR photon echo spectroscopy reveals hydrogen bond dynamics of aromatic nitriles

“…These simulations of H-bond breaking and making in methanol give times in the range of 2–5 ps [45–47] which agree with measurements on neat methanol clusters in CCl 4 [30]. Recent simulations indicate that these times are widely distributed [48]. The exchange times (4.5 and 5.3 ps) we report here and also those for acetonitrile [10] are somewhat longer than the methanol H-bond breaking times, suggesting that there are barriers to forming H-bonds to the nitrile in the range of ca 2K B T.…”

Comparative Study of the Collective Dynamics of Proteins and Inorganic Nanoparticles

“…This change in dynamics parallels the reduction in the scale of collective motion with the addition of water to the glycerol solution described above. Many previous works have emphasized the occurrence of power law fluctuations in the potential energy of folded proteins 76 77 78 and in water, methanol and silica 79 80 so there is no need to dwell on this phenomenon further here 76 77 78 . Associated long-range temporal fluctuations in fluorescence intensity, reactivity, etc., of both nanoparticles and proteins have also been observed experimentally 81 82 83 84 85 86 .…”

Local Order, Energy, and Mobility of Water Molecules in the Hydration Shell of Small Peptides

“…As a consequence of a multiplicity of time scales, water as well as other network forming liquids show a 1/f R behavior in the S u (f) spectra. [21][22][23][24][25]63 Figure 6 shows that the key features of the S u (f) spectra of TIP3P and SPC/E water are S u (f) ) lim…”

“…19,20 In recent studies on water, methanol, as well as liquids with water-like anomalies, we have found it useful to focus on the tagged molecule potential energy (TPE), u, which corresponds to the interaction energy of an individual water molecule with all other molecules in the system. [21][22][23][24][25] This is equivalent to the binding energy of an individual water molecule at a particular location at a given instant of time. Temporal correlations in the TPE are sensitive to local librational modes as well as network reorganizations involving two or more molecules.…”