Literature DB >> 22159043

Quantifying dissipative contributions in nanoscale interactions.

Sergio Santos1, Karim R Gadelrab, Tewfik Souier, Marco Stefancich, Matteo Chiesa.   

Abstract

Imaging with nanoscale resolution has become routine practice with the use of scanning probe techniques. Nevertheless, quantification of material properties and processes has been hampered by the complexity of the tip-surface interaction and the dependency of the dynamics on operational parameters. Here, we propose a framework for the quantification of the coefficients of viscoelasticity, surface energy, surface energy hysteresis and elastic modulus. Quantification of these parameters at the nanoscale will provide a firm ground to the understanding and modelling of tribology and nanoscale sciences with true nanoscale resolution. This journal is © The Royal Society of Chemistry 2012

Year:  2011        PMID: 22159043     DOI: 10.1039/c1nr10954e

Source DB:  PubMed          Journal:  Nanoscale        ISSN: 2040-3364            Impact factor:   7.790


  4 in total

1.  Moiré Modulation of Van Der Waals Potential in Twisted Hexagonal Boron Nitride.

Authors:  Stefano Chiodini; James Kerfoot; Giacomo Venturi; Sandro Mignuzzi; Evgeny M Alexeev; Bárbara Teixeira Rosa; Sefaattin Tongay; Takashi Taniguchi; Kenji Watanabe; Andrea C Ferrari; Antonio Ambrosio
Journal:  ACS Nano       Date:  2022-04-29       Impact factor: 18.027

2.  Capillary and van der Waals interactions on CaF2 crystals from amplitude modulation AFM force reconstruction profiles under ambient conditions.

Authors:  Annalisa Calò; Oriol Vidal Robles; Sergio Santos; Albert Verdaguer
Journal:  Beilstein J Nanotechnol       Date:  2015-03-25       Impact factor: 3.649

3.  Dynamic force microscopy simulator (dForce): A tool for planning and understanding tapping and bimodal AFM experiments.

Authors:  Horacio V Guzman; Pablo D Garcia; Ricardo Garcia
Journal:  Beilstein J Nanotechnol       Date:  2015-02-04       Impact factor: 3.649

4.  Quantifying nanoscale forces using machine learning in dynamic atomic force microscopy.

Authors:  Abhilash Chandrashekar; Pierpaolo Belardinelli; Miguel A Bessa; Urs Staufer; Farbod Alijani
Journal:  Nanoscale Adv       Date:  2022-04-05
  4 in total

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