Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.4055
Publisher DOI: 10.3389/fmech.2020.00027
Title: A simplified theory of electroadhesion for rough interfaces
Language: English
Authors: Ciavarella, Michele 
Papangelo, Antonio 
Keywords: DMT model; Electroadhesion; JKR model; Roughness models; Soft matter
Issue Date: 12-Jun-2020
Publisher: Frontiers Media
Source: Frontiers in Mechanical Engineering 6: 27 1-9 (2020)
Abstract (english): 
Electroadhesion is a very hot topic in tribology due to its implications for the science of surface haptics. Building on theories of Persson, we develop a simpler theory for electroadhesion between rough surfaces using the bearing area model of Ciavarella. The theory is derived for the cases of conducting and insulating bodies and shows that pull-off forces depend mostly on the applied voltage, the surface root mean square (RMS) height, and the longest wavelength in the surface representation. However, the real contact area and friction additionally depend on rms slopes and hence on truncation of the roughness spectrum. Two stickiness criteria are derived based on the present theory and on the energy balance proposed by Persson and Tosatti. The coefficient of friction decays with the normal pressure, tending to a plateau in a manner consistent with existing experiments.
URI: http://hdl.handle.net/11420/10846
DOI: 10.15480/882.4055
ISSN: 2297-3079
Journal: Frontiers in mechanical engineering 
Institute: Strukturdynamik M-14 
Document Type: Article
Project: Untersuchung und Anwendung komplexer, nichtlinearer, dynamischer Zustände in reiberregten mechanischen Systemen 
Funded by: Italian Ministry of Education, University and Research
Deutsche Forschungsgemeinschaft (DFG) 
More Funding information: MC and AP acknowledge support from the Italian Ministry of Education, University and Research under the Programme Department of Excellence Legge 232/2016 (grant no. CUPD94I18000260001). AP is thankful to the DFG (German Research Foundation) for funding the project PA 3303/1-1, and acknowledges support from PON Ricerca e Innovazione 2014-2020-Azione I.2 - D.D. n. 407, 27/02/2018, bando AIM(grant no. AIM1895471).
License: CC BY 4.0 (Attribution) CC BY 4.0 (Attribution)
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