2016
DOI: 10.1039/c5cp05143f
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A robust comparison of dynamical scenarios in a glass-forming liquid

Abstract: We use Bayesian inference methods to provide fresh insights into the sub-nanosecond dynamics of glycerol, a prototypical glass-forming liquid. To this end, quasielastic neutron scattering data as a function of temperature have been analyzed using a minimal set of underlying physical assumptions. On the basis of this analysis, we establish the unambiguous presence of three distinct dynamical processes in glycerol, namely, translational diffusion of the molecular centre of mass and two additional localized and t… Show more

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Cited by 11 publications
(16 citation statements)
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“…3 indicates a small activation energy, as expected for a highly local motion. 31,42 The time scales we obtain for the various modes are also consistent with previous work. We 19 and others 30 have previously assigned the intermediate process at τ h ≈ 1 ps to spatially heterogeneous dynamics in the form of collective molecular rearrangements.…”
Section: Model Veracitysupporting
confidence: 90%
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“…3 indicates a small activation energy, as expected for a highly local motion. 31,42 The time scales we obtain for the various modes are also consistent with previous work. We 19 and others 30 have previously assigned the intermediate process at τ h ≈ 1 ps to spatially heterogeneous dynamics in the form of collective molecular rearrangements.…”
Section: Model Veracitysupporting
confidence: 90%
“…We account for distinct types of motion expected in amorphous systems: over-damped vibration (in which we include IS transitions), motion associated with MB transitions, and homogeneous diffusive motion. Based on ultrafast optical experiments performed by us and on recent work by Vispa et al, 31 we choose Lorentzians to represent each of the three types of motion considered here. Vispa et al, 31 recently found that a triple Lorentzian function provided significantly better fits for S(q, E) of a molecular liquid than common models of similar complexity containing functional forms such as KWW and Gaussian, and much better fits than 2-component models.…”
Section: The Modelmentioning
confidence: 99%
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“…In a second step, the software generates a complete Markov chain containing all the parameters that can describe the data, and their associated χ 2 merit function. The adaptive algorithm and the Bayesian methodology have been described in detail in previous publications [13,[46][47][48][49][50][51][52][53], and the reader is referred to these works for further details.…”
Section: B Data Analysismentioning
confidence: 99%