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  5. Multi-scale model predicting friction of crystalline materials
 
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Multi-scale model predicting friction of crystalline materials

Publication date
2021-12-13
Document type
Research article
Author
Torche, Paola C.
Silva, Andrea
Kramer, Denis 
Polcar, Tomas
Hovorka, Ondrej
Organisational unit
Computational Material Design 
DOI
10.1002/admi.202100914
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/14288
ISSN
2196-7350
Series or journal
Advanced Materials Interfaces
Periodical volume
9
Periodical issue
4
Peer-reviewed
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Part of the university bibliography
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  • Additional Information
Keyword
2D materials
density functional theory calculations
stochastic thermodynamics
tribology
Abstract
A multi-scale computational framework suitable for designing solid lubricant interfaces fully in silico is presented. The approach is based on stochastic thermodynamics founded on the classical thermally activated 2D Prandtl–Tomlinson model, linked with first principles methods to accurately capture the properties of real materials. It allows investigating the energy dissipation due to friction in materials as it arises directly from their electronic structure, and naturally accessing the time-scale range of a typical friction force microscopy. This opens new possibilities for designing a broad class of material surfaces with atomically tailored properties. The multi-scale framework is applied to a class of 2D layered materials and reveals a delicate interplay between the topology of the energy landscape and dissipation that known static approaches based solely on the energy barriers fail to capture.
Description
Funding Information: This project has received funding from the European Union's Horizon2020 research and innovation programme under grant agreement No. 721642: SOLUTION. The authors acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. Publisher Copyright: {\textcopyright} 2021 Wiley-VCH GmbH Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
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