2012
DOI: 10.1186/1556-276x-7-174
|View full text |Cite
|
Sign up to set email alerts
|

Nanoscale measurement of the power spectral density of surface roughness: how to solve a difficult experimental challenge

Abstract: In this study, we show that the correct determination of surface morphology using scanning force microscopy (SFM) imaging and power spectral density (PSD) analysis of the surface roughness is an extremely demanding task that is easily affected by experimental parameters such as scan speed and feedback parameters. We present examples were the measured topography data is significantly influenced by the feedback response of the SFM system and the PSD curves calculated from this experimental data do not correspond… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

1
33
0

Year Published

2012
2012
2021
2021

Publication Types

Select...
9

Relationship

2
7

Authors

Journals

citations
Cited by 62 publications
(34 citation statements)
references
References 33 publications
1
33
0
Order By: Relevance
“…Pyramidal silicon nitride triangular cantilevers (DNP) with a nominal stiffness of 0.12 N m 21 and a nominal radius of 20 nm were used (Bruker Corporation, Camarillo, CA, USA). Imaging parameters (SetPoint ¼ 1 V; line rate ¼ 0.7 Hz; IGain ¼ 100 Hz) were kept constant for all samples, to enable accurate comparison between the different surfaces [39]. Scans of both 10 and 100 mm areas were taken from different bone slices, each at seven different locations.…”
Section: Atomic Force Microscopy Characterization and Roughness Analysismentioning
confidence: 99%
“…Pyramidal silicon nitride triangular cantilevers (DNP) with a nominal stiffness of 0.12 N m 21 and a nominal radius of 20 nm were used (Bruker Corporation, Camarillo, CA, USA). Imaging parameters (SetPoint ¼ 1 V; line rate ¼ 0.7 Hz; IGain ¼ 100 Hz) were kept constant for all samples, to enable accurate comparison between the different surfaces [39]. Scans of both 10 and 100 mm areas were taken from different bone slices, each at seven different locations.…”
Section: Atomic Force Microscopy Characterization and Roughness Analysismentioning
confidence: 99%
“…In the modern approach from material applied science, nanostructure of materials can be characterized properly using quantitative descriptions. Two main approaches to describe the 3D engineering surface roughness: statistical 22,23 and fractal description 24,25 are used in 3D surface characterization. Traditional Euclidean geometry describes objects with integer dimensions: zero-dimensional points, one-dimensional lines and curves, two-dimensional surfaces such as planes, and three-dimensional solid objects like cubes and spheres.…”
Section: Fractal Theorymentioning
confidence: 99%
“…(g)] for each of the images shown in Figure . The PSD allows to determine not only the total roughness (height variation from the mean value) but also the lateral length scale on which this height variation occurs, that is the lateral size of the features that contribute to the roughness …”
Section: Resultsmentioning
confidence: 99%