Statistical properties of defect-dependent detachment strength in bioinspired dry adhesives

Jamie A. Booth*, Verena Tinnemann, René Hensel, Eduard Arzt, Robert M. McMeeking, Kimberly L. Foster

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)


Dry adhesives using surface microstructures inspired by climbing animals have been recognized for their potentially novel capabilities, with relevance to a range of applications including pick-and-place handling. Past work has suggested that performance may be strongly dependent on variability in the critical defect size among fibrillar sub-contacts. However, it has not been directly verified that the resulting adhesive strength distribution is well described by the statistical theory of fracture used. Using in situ contact visualization, we characterize adhesive strength on a fibril-by-fibril basis for a synthetic fibrillar adhesive. Two distinct detachment mechanisms are observed. The fundamental, design-dependent mechanism involves defect propagation from within the contact. The secondary mechanism involves defect propagation from fabrication imperfections at the perimeter. The existence of two defect populations complicates characterization of the statistical properties. This is addressed by using the mean order ranking method to isolate the fundamental mechanism. The statistical properties obtained are subsequently used within a bimodal framework, allowing description of the secondary mechanism. Implications for performance are discussed, including the improvement of strength associated with elimination of fabrication imperfections. This statistical analysis of defect-dependent detachment represents a more complete approach to the characterization of fibrillar adhesives, offering new insight for design and fabrication.

Original languageEnglish
Article number20190239
Number of pages11
JournalJournal of the Royal Society Interface
Issue number156
Early online date31 Jul 2019
Publication statusPublished - Jul 2019

Bibliographical note

Data accessibility. The datasets supporting this article have been uploaded as part of the electronic supplementary material.
Authors’ contributions. All authors were involved in conception of the work. J.A.B. performed the theoretical modelling. V.T. performed the experiments. J.A.B. and V.T. analysed the data. J.A.B., R.H. and R.M.M. interpreted the results. All authors were involved in preparation of the manuscript.
Competing interests. We declare we have no competing interests.
Funding. The work of R.M.M. was partially supported by the MRSEC Program of the National Science Foundation under award no. DMR 1720256. R.M.M. also acknowledges support from a Humboldt Alumni Award. The work of V.T., R.H. and E.A. was funded by the European Research Council (ERC) under the European Union’s Seventh Framework Program (FP/2007–2013)/ERC Advanced grant no. 340929


  • Adhesion
  • Bioinspired
  • Gecko
  • Statistics
  • Strength
  • Weibull


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