Prokopovich, Polina ORCID: https://orcid.org/0000-0002-5700-9570 and Perni, S. 2011. Comparison of JKR- and DMT-based multi-asperity adhesion model: Theory and experiment. Colloids and Surfaces A: Physicochemical and Engineering Aspects 383 (1-3) , pp. 95-101. 10.1016/j.colsurfa.2011.01.011 |
Abstract
In many industrial and medical applications, some strategies to control force of adhesion between materials are necessary as surface forces can enable or hinder the functionality of the devices. All real surfaces present some level of roughness and the contact between two such surfaces is carried by the asperities on the surfaces. A multi-asperity adhesion model based on the JKR and DMT theories has been applied to the contact between silicone or glass and polybutylene terephthalate (PBT). A Monte Carlo method was used to generate a set of asperities for each of the materials. Height and radius of curvature of each asperity were based on the experimentally determined distributions. The normal distribution returned the best fit for asperity height, whilst the Weibull distribution was a better fit for the radius of curvature. The predicted adhesion forces between PBT and silicone or glass were compared with the experimental results performed using atomic force microscopy (AFM). The model predicted higher adhesion forces when the DMT theory was used than the JKR theory for both counter surfaces. The contact area calculated using the JKR model was larger than the DMT for a chosen applied load. Furthermore, the experimental values of the adhesion force were in a good agreement with the simulated data using the JKR theory in case of silicone, whilst the DMT model estimated better adhesion for glass.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering Pharmacy |
Subjects: | R Medicine > RM Therapeutics. Pharmacology |
Uncontrolled Keywords: | Adhesion; JKR; DMT; Multi-asperity contact model; AFM |
Additional Information: | Paper presented at the 14th International Conference on Surface Forces |
Publisher: | Elsevier |
ISSN: | 0927-7757 |
Last Modified: | 18 Oct 2022 13:37 |
URI: | https://orca.cardiff.ac.uk/id/eprint/14649 |
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