Localized power spectral density analysis on atomic force microscopy images for advanced patterning applications

Author(s):  
Alain Moussa ◽  
Mohamed Saib ◽  
Sara Paolillo ◽  
Frederic Lazzarino ◽  
Andrea Illiberi ◽  
...  
1996 ◽  
Vol 440 ◽  
Author(s):  
A.G. Gilicinski ◽  
S.E. Beck ◽  
R.M. Rynders ◽  
D.A. Moniot

AbstractDespite the growing use of atomic force microscopy (AFM) for the measurement of silicon wafer microroughness, no generally accepted method has been developed to deal with issues around accuracy and reproducibility. We review problems that affect these AFM studies and demonstrate the effect of probe tip size on AFM microroughness data. Without knowledge of AFM probe tip geometry, it is impossible to quantitatively compare Ra or RMS microroughness data between different measurements. An experimental solution is to characterize tip sizes during imaging and compare data taken with similar size tips. While this will significantly improve quantitation, it is restrictive in that data taken with different size tips cannot be easily compared. We propose a solution to this problem in the use of power spectral density (PSD) to evaluate microroughness with a “cutoff frequency” at the lateral wavelength where tip effects begin to affect the accuracy of the microroughness measurement. An example of this approach is described


Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 593
Author(s):  
Ekaterina Babich ◽  
Sergey Scherbak ◽  
Ekaterina Lubyankina ◽  
Valentina Zhurikhina ◽  
Andrey Lipovskii

The problem of optimizing the topography of metal structures allowing Surface Enhanced Raman Scattering (SERS) sensing is considered. We developed a model, which randomly distributes hemispheroidal particles over a given area of the glass substrate and estimates SERS capabilities of the obtained structures. We applied Power Spectral Density (PSD) analysis to modeled structures and to atomic force microscope images widely used in SERS metal island films and metal dendrites. The comparison of measured and calculated SERS signals from differing characteristics structures with the results of PSD analysis of these structures has shown that this approach allows simple identification and choosing a structure topography, which is capable of providing the maximal enhancement of Raman signal within a given set of structures of the same type placed on the substrate.


2011 ◽  
Vol 279 ◽  
pp. 313-317
Author(s):  
Dong Ju Chen ◽  
Jin Wei Fan ◽  
Fei Hu Zhang

A new method for extracting spectrum feature of spindle unbalance of machine tool is proposed. The flatness error of workpiece surface includes much errors information, and the information contains high frequency signal and low frequency signal. For these errors information, a new identification method of turning errors of workpiece based on the wavelet transform and power spectral density analysis is proposed. According to the focal variation character of wavelet and the energy value of power spectral density analysis, the feature of spindle unbalance from the measured flatness error of workpiece is extracted and identified.


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