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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
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Statistical aspects of interface adhesion and detachment of hierarchically patterned structures: dataset

Authors: Esfandiary, Nosaibeh; Zaiser, Michael; Moretti, Paolo;

Statistical aspects of interface adhesion and detachment of hierarchically patterned structures: dataset

Abstract

Data from: N. Esfandiary, M. Zaiser, P. Moretti: Statistical aspects of interface adhesion and detachment of hierarchically patterned structures (2022) Journal of Statistical Mechanics: Theory and Experiment 023301, https://doi.org/10.1088/1742-5468/ac52a4 Abstract: We introduce a three dimensional model for interface failure of hierarchical materials adhering to heterogeneous substrates. We find that the hierarchical structure induces scale invariant detachment patterns, which in the limit of low interface disorder prevent interface failure by crack propagation ('detachment fronts'). In the opposite limit of high interface disorder, hierarchical patterns ensure enhanced work of failure as compared to reference non-hierarchical structures. While the study of hierarchical adhesion is motivated by examples of fibrous materials of biological interest, our results indicate that hierarchical patterns can be useful in engineering scenarios in view of tuning and optimizing adhesion properties. Contact: Paolo Moretti Institute of Materials Simulation Friedrich-Alexander-Universität Erlangen-Nürnberg Dr.-Mack-Str. 77 90762 Fürth Germany File naming scheme: hfn: hierarchical fuse network rrn: random reference network uni: uniform threshold distribution wei15: Weibull threshold distribution (shape factor 1.5) wei4: Weibull threshold distribution (shape factor 4) wei9: Weibull threshold distribution (shape factor 9) s1: largest connected components s2: 2nd largest connected components iv: sample iv curve envelope: envelope of iv (displacement control)

Funded by DFG - 377472739 (Research Training Group GRK 2423 'Fracture across Scales - FRASCAL').

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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