Modeling in tribology: Recent advances, applications, and open questions

Lars Pastewka, Antonis I. Vakis, Ramin Aghababaei, Andreas Almqvist, Giuseppe Carbone, Michael Chandross, Daniele Dini, Stefan J. Eder, Hendrik J. Ehrich, James P. Ewen, Nicola Menga, Jean-François Molinari, Gianpietro Moras, Lucia Nicola, Marco Paggi, Carmine Putignano, Michele Scaraggi, Vladislav A. Yastrebov, Martin H. Müser

Research output: Contribution to journalReview articlepeer-review

Abstract

Recent advances in modeling have enhanced our ability to make quantitative predictions for tribological phenomena, thereby unraveling relevant mechanisms. Algorithmic innovations, including those based on multiscale methods and machine learning, have been especially impactful, for example in overcoming long-standing bottlenecks that hinder simulations of systems with strong coupling across disparate scales. However, traditional modeling approaches, such as boundary-element techniques, have also progressed and continue to yield new insights. This article reviews developments from the past decade, examining how both new and established methods have deepened our understanding of experimental results and have furthered theoretical approaches in key tribological areas, including contact mechanics, lubrication, metal friction, and tribo-chemistry. Selected applications, such as tunable interfaces and energy harvesting, illustrate the broad influence of recent developments on the field.
Original languageEnglish
Article number111326
JournalTribology International
Early online date30 Oct 2025
DOIs
Publication statusE-pub ahead of print - 30 Oct 2025

Data Availability Statement

No data was used for the research described in the article.

Acknowledgements

Any subjective views or opinions that might be expressed in the paper do not necessarily represent the views of the US Department of Energy or the USA Government. Open access funding was provided by TU Wien.

Funding

S.J.E. and H.J.E. acknowledge Project K2 InTribology2, no. 906860 of theAustrian Research Promotion Agency (FFG). D.D. acknowledges the support received from the Engineering and Physical Sciences Research Council, United Kingdom (EPSRC) via EP/V038044/1 and EP/N025954/1, as well as the support provided from the Royal Academy of Engineering (RAEng) Research Chair in Complex Engineering Interfaces (RCSRF2122-14-143). J.P.E. thanks the RAEng for support via their Research Fellowships scheme. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the US Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Keywords

  • Modeling
  • Tribology

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