Optimum Roughness for Minimum Adhesion

2008 ◽  
Author(s):  
D.-L. Liu ◽  
J. Martin ◽  
N. A. Burnham
Keyword(s):  
Surface Roughness ◽  
Rough Surfaces ◽  
Optimal Size ◽  
Fractal Surfaces ◽  
Single Asperity ◽  
Roughness Exponent ◽  
Asperity Model ◽  
Roughness Exponents ◽  
Adhesive Forces

Surface roughness has a significant affect on adhesion. We used a single-asperity model to describe a smooth tip in contact with a rough surface and predicted that an optimal size of asperity will yield a minimum of adhesion. Experimentally, adhesive forces on silicon wafers with varying roughness were measured using AFM cantilevers with varying tip radii. It was found that minima do exist, and for all tip radii, the adhesion falls significantly for roughness greater than 1–2 nm and drops at higher roughness for larger tips. In addition to RMS roughness, the roughness exponent is another important parameter for the characterization of rough surfaces and its affect on adhesion was also investigated. We developed computer programs to simulate a set of fractal rough surfaces with differing roughness exponents. The adhesive forces between an AFM tip and the fractal surfaces were calculated and the adhesion was seen to decrease as the roughness exponent increases. This work should help minimize MEMS stiction and progress the understanding of nanoscale contact mechanics.

Mathematical Modeling of Flattening Process on Rough Surfaces in Thermal Spray

1996 ◽  
Author(s):  
H. Fukanuma
Keyword(s):  
Mathematical Modeling ◽  
Surface Roughness ◽  
Thermal Spray ◽  
Rough Surfaces ◽  
Time Decrease ◽  
Flattening Process

Abstract Thermal spray layers are formed on rough surfaces; however, the flattening process on rough surfaces has not yet been clarified. A mathematical flattening model which takes into account the roughness of the substrate or previously coated layers is proposed in this paper. As a result of surface roughness, the flattening degree and the flattening time decrease with increasing surface roughness in this model. In addition, the characterization of surface roughness is introduced for the flattening model. Several calculated cases of the flattening model are shown.

Study on Reconstruction of Fractal Rough Surfaces

2013 ◽  
Vol 278-280 ◽  
pp. 527-530
Author(s):  
Nan Zhang ◽  
Li Hua Wang ◽  
Yu Song He ◽  
Zi Lu
Keyword(s):  
Rough Surfaces ◽  
Three Dimensional ◽  
Computer Models ◽  
Contact Analysis ◽  
Solid Model ◽  
Fractal Surfaces ◽  
Contact Conductivity ◽  
Surface Contact

The geometric topography of the engineering surfaces play key roles in many issue of engineering and science including the analysis of friction, wear, lubrication, sealing and contact conductivity, especially microcosmic surface contact, thus the characterization of surface is one of the most important topics of tribology. Using the technology of CAD/CAE, a three-dimensional solid model of the fractal surfaces was established and meshed to provide the computer models for microcosmic contact analysis between two rough surfaces in this paper.

Surface Roughness Characterization of al Films by Spectroscopic Ellipsometry

1985 ◽  
Vol 54 ◽  
Author(s):  
J. R. Blanco ◽  
K. Vedam ◽  
P. J. McMarr ◽  
J. M. Bennett
Keyword(s):  
Surface Roughness ◽  
Rough Surface ◽  
Spectroscopic Ellipsometry ◽  
Rough Surfaces ◽  
Scalar Theory ◽  
Nondestructive Technique ◽  
Aluminum Films ◽  
Random Rough Surfaces ◽  
Scalar Theory Of Diffraction

ABSTRACTWell characterized rough surfaces of aluminum films have been studied by the nondestructive technique of Spectroscopie Ellipsometry (SE). The roughness of the aluminum specimens had been characterized earlier by Total Integrated Scattering and Stylus Profilometry techniques to obtain numerical estimates of ras roughness and autocovariance lengths. The present SE measurements on these specimens were carried out at a number of angles of incidence in the range 30–80° and at a number of discrete wavelengths in the spectral range 300–650nm. The SE results were then analyzed by the scalar theory of diffraction from random rough surfaces by treating the surface as a simple random rough surface. The results of such analyses of the SE measurements are compared with the results of the earlier characterization techniques.

FRACTAL ROUGHNESS CHARACTERIZATION OF SUPER-GROUND Mn-Zn FERRITE SINGLE CRYSTALS

Fractals ◽  
1996 ◽  
Vol 04 (02) ◽  
pp. 205-211 ◽  
Author(s):  
J. YU ◽  
Y. NAMBA ◽  
M. SHIOKAWA
Keyword(s):  
Surface Roughness ◽  
Single Crystal ◽  
Single Crystals ◽  
Feed Rate ◽  
Scaling Behavior ◽  
Machining Process ◽  
Roughness Exponent ◽  
Zn Ferrite ◽  
Fractal Roughness

The surface of superground Mn-Zn ferrite single crystal may be identified as a self-affine fractal in the stochastic sense. The rms roughness increased as a power of the scale from 102 nm to 106 nm with the roughness exponent α=0.17±0.04, and 0.11±0.06, for grinding feed rate of 15 and 10 μm/rev, respectively. The scaling behavior coincided with the theory prediction well used for growing self-affine surfaces in the interested region for magnetic heads performance. The rms roughnesses increased with increase in the feed rate, implying that the feed rate is a crucial grinding parameter affecting the supersmooth surface roughness in the machining process.

A COMPARISON BETWEEN THE ATOMIC FORCE MICROSCOPY AND X-RAY REFLECTIVITY ON THE CHARACTERIZATION OF SURFACE ROUGHNESS

2003 ◽  
Vol 02 (04n05) ◽  
pp. 343-348 ◽  
Author(s):  
CHIH-HAO LEE ◽  
WEN-YEN PEN ◽  
MING-ZHE LIN ◽  
KUAN-LI YU ◽  
JEN-CHUNG HSUEH
Keyword(s):  
Surface Roughness ◽  
Atomic Force Microscopy ◽  
Surface Morphology ◽  
Power Spectra ◽  
X Ray ◽  
Force Microscopy ◽  
Atomic Force ◽  
Roughness Exponent ◽  
Buried Layer

Atomic force microscopy and X-ray reflectivity methods are used to characterize a surface morphology which includes the information of rms roughness, roughness exponent, and the height–height correlation length. Two major reasons to interpret the discrepancy of rms roughness data measured by AFM and X-ray reflectivity are (1) the bandpass of power spectra density is different and (2) the X-ray reflectivity probes the high density buried layer.

Fractal Network Model for Contact Conductance

1991 ◽  
Vol 113 (3) ◽  
pp. 516-525 ◽  
Author(s):  
A. Majumdar ◽  
C. L. Tien
Keyword(s):  
Fractal Dimension ◽  
Network Model ◽  
Rough Surfaces ◽  
Surface Profile ◽  
Contact Conductance ◽  
Fractal Surfaces ◽  
Real Area Of Contact ◽  
Similar Images ◽  
Fractal Network

The topography of rough surfaces strongly influences the conduction of heat and electricity between two surfaces in contact. Roughness measurements on a variety of surfaces have shown that their structure follows a fractal geometry whereby similar images of the surface appear under repeated magnification. Such a structure is characterized by the fractal dimension D, which lies between 2 and 3 for a surface and between 1 and 2 for a surface profile. This paper uses the fractal characterization of surface roughness to develop a new network model for analyzing heat conduction between two contacting rough surfaces. The analysis yields the simple result that the contact conductance h and the real area of contact At are related as h ~ AtD/2 where D is the fractal dimension of the surface profile. Contact mechanics of fractal surfaces has shown that At varies with the load F as At ~ Fη where η ranges from 1 to 1.33 depending on the value of D. This proves that the conductance and load are related as h ~ FηD/2 and resolves the anomaly in previous investigations, which theoretically and experimentally obtained different values for the load exponent. The analytical results agreed well with previous experiments although there is a tendency for overprediction.

scholarly journals Post-Processing and Surface Characterization of Additively Manufactured Stainless Steel 316L Lattice: Implications for BioMedical Use

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1376
Author(s):  
Alex Quok An Teo ◽  
Lina Yan ◽  
Akshay Chaudhari ◽  
Gavin Kane O’Neill
Keyword(s):  
Surface Roughness ◽  
Stainless Steel ◽  
Surface Characterization ◽  
High Surface ◽  
Surface Characteristics ◽  
Post Processing ◽  
Stainless Steel 316L ◽  
Processing Methods ◽  
Particulate Debris

Additive manufacturing of stainless steel is becoming increasingly accessible, allowing for the customisation of structure and surface characteristics; there is little guidance for the post-processing of these metals. We carried out this study to ascertain the effects of various combinations of post-processing methods on the surface of an additively manufactured stainless steel 316L lattice. We also characterized the nature of residual surface particles found after these processes via energy-dispersive X-ray spectroscopy. Finally, we measured the surface roughness of the post-processing lattices via digital microscopy. The native lattices had a predictably high surface roughness from partially molten particles. Sandblasting effectively removed this but damaged the surface, introducing a peel-off layer, as well as leaving surface residue from the glass beads used. The addition of either abrasive polishing or electropolishing removed the peel-off layer but introduced other surface deficiencies making it more susceptible to corrosion. Finally, when electropolishing was performed after the above processes, there was a significant reduction in residual surface particles. The constitution of the particulate debris as well as the lattice surface roughness following each post-processing method varied, with potential implications for clinical use. The work provides a good base for future development of post-processing methods for additively manufactured stainless steel.

scholarly journals Skewness and Kurtosis: Important Parameters in the Characterization of Dental Implant Surface Roughness—A Computer Simulation

2011 ◽  
Vol 2011 ◽  
pp. 1-6 ◽  
Author(s):  
Karl Niklas Hansson ◽  
Stig Hansson
Keyword(s):  
Surface Roughness ◽  
Shear Strength ◽  
Roughness Parameter ◽  
Interface Shear Strength ◽  
Interface Shear ◽  
Implant Surface ◽  
Bone Response ◽  
Dental Implant Surface ◽  
Skewness And Kurtosis

The surface roughness affects the bone response to dental implants. A primary aim of the roughness is to increase the bone-implant interface shear strength. Surface roughness is generally characterized by means of surface roughness parameters. It was demonstrated that the normally used parameters cannot discriminate between surfaces expected to give a high interface shear strength from surfaces expected to give a low interface shear strength. It was further demonstrated that the skewness parameter can do this discrimination. A problem with this parameter is that it is sensitive to isolated peaks and valleys. Another roughness parameter which on theoretical grounds can be supposed to give valuable information on the quality of a rough surface is kurtosis. This parameter is also sensitive to isolated peaks and valleys. An implant surface was assumed to have a fairly well-defined and homogenous “semiperiodic” surface roughness upon which isolated peaks were superimposed. In a computerized simulation, it was demonstrated that by using small sampling lengths during measurement, it should be possible to get accurate values of the skewness and kurtosis parameters.

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