Resolving distribution of relaxation times in Poly(propylene glycol) on the crossover region
Enis Tuncer, Marizio Furlani, Bengt-Erik Mellander

TL;DR
This paper applies a novel numerical method combining constrained least squares and Monte Carlo techniques to analyze dielectric relaxation data of poly(propylene glycol), revealing detailed relaxation spectra and behavior in the crossover region.
Contribution
The study introduces a new approach to extract relaxation time distributions without prior assumptions, providing deeper insights into molecular relaxations in poly(propylene glycol).
Findings
Resolved alpha and beta relaxations in PPG.
Identified Arrhenius behavior post-crossover.
Showed beta relaxation continuity with different activation energy.
Abstract
In this paper, a recently developed numerical technique [{\em Tuncer E and Guba{\'n}ski S M, IEEE Trans Diel El Insul {\bf 8}(3)(2001) 310-320}] is applied to poly(propylene glycol) complex dielectric data to extract more information about the molecular relaxation processes. The method is based on a constrained-least-squares (\clsq) data fitting procedure together with the Monte Carlo (\mc) method. We preselect the number of relaxation times with no {\em a-priori} physical assumption, and use the Debye single relaxation as ``kernel'', then the obtained weighting factors at each \mc step from the \clsq method builds up a relaxation time spectrum. When the analysis is repeated for data at different temperatures a {\em relaxation-image} is created. The obtained relaxation are analyzed using the Lorentz (Cauchy) distribution, which is a special form of the L{\'e}vy statistics. In the…
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