Fatigue and failure of a polymer chain under tension

Abstract

The rupture of a polymer chain maintained at temperature $T$ under fixed tension is prototypical to a wide array of systems failing under constant external strain and random perturbations. Past research focused on analytic and numerical studies of the mean rate of collapse of such a chain. Surprisingly, an analytic calculation of the probability distribution function (PDF) of collapse rates appears to be lacking. Since rare events of rapid collapse can be important and even catastrophic, we present here a theory of this distribution, with a stress on its tail of fast rates. We show that the tail of the PDF is a power law with a {\em universal} exponent that is theoretically determined. Extensive numerics validate the offered theory. Lessons pertaining to other problems of the same type are drawn.

References in corpus (4)

• Powerlaw: a Python package for analysis of heavy-tailed distributions
• Rupture of multiple parallel molecular bonds under dynamic loading
• Rank-Ordering Statistics of Extreme Events: Application to the Distribution of Large Earthquakes
• Creep and Fracture of a Protein Gel under Stress

Cited by in corpus (1)

• Crack Localization and the Interplay between Stress Enhancement and Thermal Noise