Paper
18 August 2005 Size effects on stylus tip reconstruction for micro and nano roughness measurement
Chao-Chang A. Chen, Jr-Rung Chen, Huay-Chung Liou, Yen-Liang Chen
Author Affiliations +
Abstract
Stylus tip reconstruction is imperative in tracing and calibration of micro and nano surface roughness measurement either for surface roughness analyzer or for scanning probe microscopy. This research is to investigate the size effects on stylus tip reconstruction in micro and nano roughness measurement. Aspect ratios within and between tips and gages, such as Tip Aspect Ratio (TAR) of tip width to height, Gage Aspect Ratio (GAR), Height Aspect Ratio (HAR) of tip height to gage height, and Width Aspect Ratio (WAR) have been formulated to develop a stylus tip reconstruction method (STRM) to estimate tip profile from the measured profile image and the traced gage profile. A simulated program has been used to test the developed STRM with different aspect ratios of tips and gages. Experiments have been conducted on a Hommelwerke T4000 surface roughness analyzer with a TKL T100 tip of radius 5 μm and a Veeco Dektak 200 surface roughness analyzer with nominal radius values of stylus tip radius 12.5 μm to measure a traced roughness gage (Mitutoyo Serial No. 0300042) of step height of 10 μm and razor blade in ISO 5436 standard. Experimental results show that the difference of STRM on step gage and razor blade measurement is about 4 % and the developed STRM can be further used to estimate the geometric size effects of tip reconstruction in scanning probe microscopy (SPM).
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chao-Chang A. Chen, Jr-Rung Chen, Huay-Chung Liou, and Yen-Liang Chen "Size effects on stylus tip reconstruction for micro and nano roughness measurement", Proc. SPIE 5879, Recent Developments in Traceable Dimensional Measurements III, 58790H (18 August 2005); https://doi.org/10.1117/12.616831
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Cited by 2 scholarly publications.
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KEYWORDS
Surface roughness

Scanning probe microscopy

Reconstruction algorithms

Standards development

Convolution

Ear

Algorithm development

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