With AFM data, how to calculate surface roughness? what is difference between surface roughness and grain size?
Most commercial AFM software have a dedicated tool that can directly give you surface roughness values of an image, e.g. the RMS roughness. Just note that there are several possible ways to quantify the roughness.
I'm not entirely certain what you're aiming at with the 2nd part of our question. Surface roughness is a general quantity that may depend on a variety of factors. Grain size is the size of an individual, continous crystalline domain on a polycrystalline surface. Maybe you can explain a bit more about the system you are looking at?
Surface roughness is a calculation done in three dimensions. Grain size is a calculation from a cross-section in two dimensions.
Can you please give me some reference on how to calculate surface roughness using different parameters, and what are the meanings of different parameters?
I suggest that you use the freeware Gwyddion, where (i) you will find all the Tools necessary for analysing your AFM data, and (ii) for which there are plenty of online tutorials and explanations about the theory behind each Tools.
Anyway, make sure, when you mention roughness that you keep the surface area constant (always use the same image size), and mention it. Roughness strongly depends on the surface area considered (usually it increases with increasing surface area). Additionaly, give the type of roughness (RMS, total, arithmetic, ...).
Grain size distribution is a different story. Many parameters can be measured, such as the projected diameter, the inner or outer circle, etc. But AFM is not well suited for this kind of analysis. Prefer SEM images, or determine crystallite size by XRD.
Dear all, there is no absolute "best method". Always consider roughness with regard to what mechanism you want to discuss, and what scale is important for your study. AFM or interferometry or profilometry are complementary.
Best regards,
Thomas
With AFM data, how to calculate roughness ?
--> In practice, commercial AFM systems have built-in analysis routines to calculate roughness. Off-line software also exists as noted. In theory, the methods used to acquire and pre-process the data make a significant difference in the results.
What is difference between surface roughness and grain size?
--> Surface roughness is a 3-D measurement and grain size is a 2-D measurement.
Dear Imtiaz,
Roughness test, profilometer, modern interferometers instruments are generally used for roughness measurement. Surface measurement conceptually includes surface shape, surface finish, surface profile roughness (Ra), surface texture, asperity and structural characterization. Optical profilometry can be used to measure surface area roughness (Sa). Ra and RMS can be calculated differently and popular calculation method for roughness, Ra is calculated as the Roughness average of a surfaces measured microscopic peaks and valleys and RMS is calculated as the Root Mean Square of a surfaces measured microscopic peaks and valleys.
Popular interferometeries are phase-shifting interferometry (PSI), vertical scanning interferometry (VSI), and enhanced vertical scanning interferometry (EVSI). Advance nano-measuring techniques are scanning probe microscope (SPM) and its two primary forms scanning tunneling microscope (STM) and atomic force microscope (AFM) can be used for surface roughness characterizations. Atomic force microscope is an advanced and important device in the family of SPMs as a non-optical measuring technique.3D computed tomography (CT) metrology is able to perform dimensional measurements like CMMs(coordinate measuring machine). SEM using LSM techniques specially on color intensity can also used for surface measurements types of polymers, polyvinylchloride (PVC), polymethylmethacrylate (PMMA), and polystyrene (PS).
Average surface roughness measurement calculations (skewness and kurtosis statistical analysis):
Ra= CLA= AA=1/L ∫│z-m│dx, L= sample length profile, z-peak to vally height and m- peak to mean hight
Hope it work out for you.
Ashish
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