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Strain Rate Effects on Axial Tensile Behavior of Crystalline Polyethylene: Insights from Molecular Dynamics Simulations

Submitted by Nuwan Dewapriya on

Our recent paper is accessible freely for 50 days from this link: https://authors.elsevier.com/a/1iaz87NHxQgzz

 


Key findings of this paper include a 7-fold strength increase in crystals with chain ends at higher strain rates, a shift in failure mode from chain end sliding to chain scission, and the influence of molecular weight on the failure mode.

Viscoelastic amplification of the pull-off stress in the detachment of a rigid flat punch from an adhesive soft viscoelastic layer

Submitted by Antonio Papangelo on

The problem of the detachment of a flat indenter from a plane adhesive viscoelastic strip of thickness “b” is studied. For any given retraction speed, three different detachment regimes are found: (i) for very small “b” the detachment stress is constant and equal to the theoretical strength of the interface, (ii) for intermediate values of “b” the detachment stress decays approximately as b^{-1/2}1/2, (iii) for thick layers a constant detachment stress is obtained corresponding to case the punch is detaching from a halfplane.

Journal Club for February 2024: Mechanics in Solid-State Batteries: Mechanical Properties, Interfacial Failure, and Multiphysics Modeling

Submitted by Juner Zhu on

Journal Club for February 2024: Mechanics in Solid-State Batteries: Mechanical Properties, Interfacial Failure, and Multiphysics Modeling

Wei Li=, Ruqing Fang=, Junning Jiao, Juner Zhu*

Department of Mechanical and Industrial Engineering, Northeastern University

* Corresponding author: j.zhu [at] northeastern.edu
= Authors with equal contributions to this article

Constitutive theory for highly entangled hydrogels by considering the molecular friction

Submitted by bin.chen on

By considering the frictional sliding of randomly distributed entanglements within the polymer network upon mechanical stretches, we develop a constitutive theory to describe the large stretch behaviors of highly entangled hydrogels. 

doi: https://doi.org/10.1007/s10483-024-3076-8

 

Atomistic simulation assisted error-inclusive Bayesian machine learning for probabilistically unraveling the mechanical properties of solidified metals

Submitted by mohsenzaeem on

Solidification phenomenon has been an integral part of the manufacturing processes of metals, where the quantification ofstochastic variations and manufacturing uncertainties is critically important. Accurate molecular dynamics (MD) simulations ofmetal solidification and the resulting properties require excessive computational expenses for probabilistic stochastic analyseswhere thousands of random realizations are necessary.