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The Prandtl-Tomlinson model of friction, first introduced in 1928 as a "conceptual model" for a single-atom contact, consists of a point mass that is dragged over a sinusoidal potential by a spring. After decades of virtual oblivion, it has recently found impressive validation for contacts comprising tens or even hundreds of atoms. To date, the Prandtl-Tomlinson model enjoys widespread popularity as depicting arguably the most insightful mechanical analogue to atomic-scale effects occurring at sliding interfaces. In this issue of ACS Nano, Pawlak et al. demonstrate the model's applicability to a true single-atom contact, thereby illustrating that simple mechanical representations can indeed go a long way toward explaining interactions at atomically defined interfaces.
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http://dx.doi.org/10.1021/acsnano.5b08251 | DOI Listing |
ACS Appl Mater Interfaces
July 2025
International School for Advanced Studies (SISSA), Via Bonomea 265, 34136 Trieste, Italy.
Nanofriction experiments typically produce force traces exhibiting atomic stick-slip oscillations, which researchers have traditionally analyzed with ad hoc algorithms. This study successfully unravels the potential of machine learning (ML) to interpret nanofriction force traces and automatically extract Prandtl-Tomlinson (PT) model parameters. A prototypical neural network (NN) perceptron was trained on synthetic force traces generated by simulations across a wide parameter range.
View Article and Find Full Text PDFAdv Sci (Weinh)
June 2025
School of Materials Science and Engineering, Nankai University, Tianjin, 300350, P. R. China.
Precise control of friction at the nanoscale is crucial for developing efficient micro/nano-electromechanical systems. This study presents a novel approach to manipulate friction in two-dimensional materials using coupled direct current (DC) and alternating current (AC) electric fields. By applying a low-amplitude AC bias atop a DC field, friction on monolayer graphene is continuously reduced without compensating the DC bias, while preserving the integrity of the graphitic interface.
View Article and Find Full Text PDFNanoscale Adv
July 2024
State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology 100029 Beijing China
Phys Rev Lett
February 2024
Jiangsu Key Laboratory for Design and Manufacture of Micro-Nano Biomedical Instruments, School of Mechanical Engineering, Southeast University, Nanjing 211189, China.
Friction is responsible for about one-third of the primary energy consumption in the world. So far, a thorough atomistic understanding of the frictional energy dissipation mechanisms is still lacking. The Amontons' law states that kinetic friction is independent of the sliding velocity while the Prandtl-Tomlinson model suggests that damping is proportional to the relative sliding velocity between two contacting objects.
View Article and Find Full Text PDFLangmuir
August 2023
National United Engineering Laboratory for Advanced Bearing Tribology, Henan University of Science and Technology, Luoyang 471023, China.
Graphene has enormous potential as a solid lubricant at sliding electrical contact interfaces of micro-/nanoelectromechanical systems that suffer severe wear. Understanding the velocity-dependent friction of graphene under different applied voltages contributes to the application of graphene in sliding electrical contact scenarios. The friction of graphene, measured by conductive atomic force microscopy, under low applied voltage increases logarithmically with sliding velocity─the same as when no voltage is applied but at a faster rate of increase.
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