Literature DB >> 30965008

Effect of Relative Humidity on the Viscoelasticity of Thin Organic Films Studied by Contact Thermal Noise AFM.

Juan F Gonzalez-Martinez1, Erum Kakar1,2, Stefan Erkselius3, Nicola Rehnberg3, Javier Sotres1.   

Abstract

Material scientists are in need of experimental techniques that facilitate a quantitative mechanical characterization of mesoscale materials and, therefore, their rational design. An example is that of thin organic films, as their performance often relates to their ability to withstand use without damage. The mechanical characterization of thin films has benefited from the emergence of the atomic force microscope (AFM). In this regard, it is of relevance that most soft materials are not elastic but viscoelastic instead. While most AFM operation modes and analysis procedures are suitable for elasticity studies, the use of AFM for quantitative viscoelastic characterizations is still a challenge. This is now an emerging topic due to recent developments in contact resonance AFM. The aim of this work was to further explore the potential of this technique by investigating its sensitivity to viscoelastic changes induced by environmental parameters, specifically humidity. Here, we show that by means of this experimental approach, it was possible to quantitatively monitor the influence of humidity on the viscoelasticity of two different thin and hydrophobic polyurethane coatings representative of those typically used to protect materials from processes like weathering and wear. The technique was sensitive even to the transition between the antiplasticizing and plasticizing effects of ambient humidity. Moreover, we showed that this was possible without the need of externally exciting the AFM cantilever or the sample, i.e., just by monitoring the Brownian motion of cantilevers, which significantly facilitates the implementation of this technique in any AFM setup.

Entities:  

Year:  2019        PMID: 30965008     DOI: 10.1021/acs.langmuir.8b04222

Source DB:  PubMed          Journal:  Langmuir        ISSN: 0743-7463            Impact factor:   3.882


  1 in total

1.  Locating critical events in AFM force measurements by means of one-dimensional convolutional neural networks.

Authors:  Javier Sotres; Hannah Boyd; Juan F Gonzalez-Martinez
Journal:  Sci Rep       Date:  2022-07-29       Impact factor: 4.996

  1 in total

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