2011
DOI: 10.1039/c0an00498g
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Analytical method for parameterizing the random profile components of nanosurfaces imaged by atomic force microscopy

Abstract: The functional properties of many technological surfaces in biotechnology, electronics, and mechanical engineering depend to a large degree on the individual features of their nanoscale surface texture, which in turn is a function of the surface manufacturing process. Among these features, the surface irregularities and self-similarity structures at different spatial scales, especially in the range of 1 to 100 nm, are of high importance because they greatly affect the surface interaction forces acting at a nan… Show more

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Cited by 12 publications
(21 citation statements)
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“…In this work, the method of atomic force microscopy was used to analyze the surface relief of metals formed under different regimes of laser ablation in an aqueous medium. It has been shown that NUCLEAR PHYSICS SERGE F. TIMASHEV nuclear transformations occur only under intensive impacts of plasma ions and molecules on the surface, when the "roughness" greatly increases and the texture "spikiness factor" as one of the key 3D parameters of the surface relief in the nanometer range [42,43] determining the measure of the most abrupt changes of the surface profile becomes significant.…”
Section: Discussionmentioning
confidence: 99%
“…In this work, the method of atomic force microscopy was used to analyze the surface relief of metals formed under different regimes of laser ablation in an aqueous medium. It has been shown that NUCLEAR PHYSICS SERGE F. TIMASHEV nuclear transformations occur only under intensive impacts of plasma ions and molecules on the surface, when the "roughness" greatly increases and the texture "spikiness factor" as one of the key 3D parameters of the surface relief in the nanometer range [42,43] determining the measure of the most abrupt changes of the surface profile becomes significant.…”
Section: Discussionmentioning
confidence: 99%
“…( )) with those derived from experimental data provides information on spatial intervals in which correlations between irregularities of different types are retained (correlation areas or correlation lengths) and makes it possible to determine parameters characterizing the chaoticity of the surface relief [7][8][9]11]. (1) shows AFM surface images of films prepared from native R-phycoerythrin at concentrations of 50 and 5 g/ml and from R-phycoerythrin with incorporated CdS nanoparticles.…”
Section: Calculationsmentioning
confidence: 99%
“…The averaged values of FNS parameters for R-phycoerythrin with and without incorporated quantum dots are shown in Table 1. Figure (4) illustrates the structural functions (2) ( ) calculated for experimental data and the structural functions constructed from FNS parameters: the structural functions (2) ( ) directly calculated for the given profiles (1); the sum (2) of the resonant components r (2) ( ) (3) ( r (2) ( ) is acquired directly from S cR [8]) and the random components c A noteworthy fact is the significant scatter of <h> (from 5.16 to 1.16 nm) and, correspondingly, of (from 2.07 to 0.57 nm) over the entire data set ( Table 1).…”
Section: Figurementioning
confidence: 99%
“…The fraction of such high energy electrons, and there fore the efficiency of the above nuclear transforma tions, depends on irregularities in the metal's surface relief that form under the action of laser pulses. The 3D parameters that characterize features of the relief over the nanometer range are determined by analyzing images of the surface obtained via atomic force microscopy (AFM) [3][4][5][6]. It is in the neighborhood of the greatest high frequency irregularities of the sur face that the electric fields with the highest voltage that lowers the energy barrier to electron injection from the metal (the Frenkel effect [7]) are located and elevated values of the mechanical tensile stresses that also con tribute to reducing the work of electrons escaping from the metal (the Zhurkov effect [8]) are found.…”
Section: Introductionmentioning
confidence: 99%