Conventional Roughness Parameters Research Articles

Tuning Surface Adhesion Using Grayscale Electron-beam Lithography.

Surface texturing of manufactured products tailors their properties, such as friction, adhesion, biocompatibility, or fluid interactions. However, advancements in this area are largely the result of trial-and-effort testing and generally lack a science-guided framework for determining the surface topography that will optimize performance. The present investigation explores grayscale electron-beam lithography as a means to create multiscale surface patterns to control surface performance. Here, we created and characterized a set of surface textures on a silicon wafer; the textures were superpositions of sine waves of varying wavelengths and amplitudes. First, the multiscale topography of the patterned surface was characterized, using profilometry and atomic force microscopy, to understand its fidelity to the designed-in pattern. The results of this analysis demonstrated how grayscale lithography accurately controlled the lateral size of features but was less precise on the vertical height of the surface, and also introduced inherent roughness below the scale of patterning. Second, a micromechanical tester was used to characterize the adhesion of the surfaces with large-scale polished silicon spheres. The results showed that adhesion could be tailored, with significant contribution from all of the designed-in length scales of topography. The strength of adhesion did not correlate with conventional roughness parameters but could be accurately modeled using simple numerical integration. Taken together, this investigation demonstrates the promise and challenges of grayscale e-beam lithography with multiscale patterns as a method for the tailoring of surface performance.

Natural rock roughness as a key parameter for optimizing seedling adhesion and restoration of the seagrass Posidonia oceanica in its native environment

Seagrasses provide various ecosystem functions in coastal areas of the world. In the Mediterranean Sea, Posidonia oceanica is an endemic species threatened by several activities despite being protected by national and international laws. Currently, several transplanting initiatives have been carried out using different methods, among which those including seeds and seedlings are considered the most ecological and low‐cost ones. Beach‐cast fruits and seeds can be found in spring and their appearance can easily be reported, through a citizen science approach, by the community. One of the obstacles in using these methods is identifying the best substrate in which to place P. oceanica seeds to facilitate root adhesion of the seedlings prior to their transplantation into the sea. In the present study, we analyzed, using a 3D surface optical microscope, the roughness of natural rocks to identify the availability of specific roughness ranges suitable for adhesion and root anchoring of P. oceanica seedlings. Conventional roughness parameters and roughness power spectral density were calculated for the inner and outer surfaces of 9 different rock samples. Among the rock samples examined, the calcarenitic ones and in particular marsala calcarenite, due to the presence of the “ideal roughness for seedlings” can be considered one of the best consolidated substrates to be used for the construction of ad hoc devices on which plantlet of P. oceanica can grow for the purpose of restoration.

Quantitative power spectral density analysis of nano/microstructured Ni-Zn electrodeposit and its correlation with superhydrophobicity

This paper aims to establish a quantitative relationship between wettability and surface morphology. The wettability of surfaces is highly dependent on surface morphology, and this relationship will be explored using either conventional roughness parameters or power spectral density (PSD) derived parameters. To investigate the effect of surface morphology on wettability, various Ni-Zn coatings with different hierarchical surface morphologies were electrodeposited on copper substrates. The coatings exhibited hydrophobic behavior with apparent contact angles ranging from 105° to 155°, depending on the shape, size, and arrangement of their surface features. Although conventional roughness parameters like Sq and Spc influenced the wettability of the coatings, their absolute values could not accurately predict superhydrophobic behavior. Therefore, the PSD analysis was used as an alternative approach to predict the wettability behavior of the coatings by distinguishing between nano- and micro-features. The results revealed that a superhydrophobicity (SH) index could be obtained from the PSD model to predict superhydrophobic properties. Coatings with an SH index below 0.32 exhibited a contact angle greater than 150°, regardless of their deposition parameters. The findings suggest that surface roughness plays a significant role in controlling the wettability of Ni-Zn coatings, and the SH index is a useful tool for predicting the superhydrophobic properties of these coatings.

Surface Area and Local Curvature: Why Roughness Improves the Bioactivity of Neural Implants.

While roughening the surface of neural implants has been shown to significantly improve their performance, the mechanism for this improvement is not understood, preventing systematic optimization of surfaces. Specifically, prior work has shown that the cellular response to a surface can be significantly enhanced by coating the implant surface with inorganic nanoparticles and neuroadhesion protein L1, and this improvement occurs even when the surface chemistry is identical between the nanoparticle-coated and uncoated electrodes, suggesting the critical importance of surface topography. Here, we use transmission electron microscopy to characterize the topography of bare and nanoparticle-coated implants across 7 orders of magnitude in size, from the device scale to the atomic scale. The results reveal multiscale roughness, which cannot be adequately described using conventional roughness parameters. Indeed, the topography is nearly identical between the two samples at the smallest scales and also at the largest scales but vastly different in the intermediate scales, especially in the range of 5-100 nm. Using a multiscale topography analysis, we show that the coating causes a 76% increase in the available surface area for contact and an order-of-magnitude increase in local surface curvature at characteristic sizes corresponding to specific biological structures. These are correlated with a 75% increase in bound proteins on the surface and a 134% increase in neurite outgrowth. The present investigation presents a framework for analyzing the scale-dependent topography of medical device-relevant surfaces, and suggests the most critical size scales that determine the biological response to implanted materials.

Fractal dimensions of blast-cleaned steel surfaces and their effects on the adhesion of polymeric foil systems with integrated pressure-sensitive adhesives

Morphology and structure of substrate surfaces are crucial parameters for the establishment of reliable protective layers as they determine the adhesion of the protective layer to the substrate. Insufficient adhesion will promote unwanted effects, namely delamination and blistering. This applies as well to protective hybrid-layers, consisting of a polymeric foil bonded to the substrate (usually steel) by means of an integrated pressure-sensitive adhesive. Numerous parameters are known to characterize the morphology of metal substrates. In this study, mild steel samples were prepared using dry-blast cleaning with abrasive materials (metallic, minerals) of different particle shapes and particle sizes to investigate the impact of surface profile parameters on the adhesion of polymeric foil systems (PFS). For this purpose, 2D profiles were taken from a total of 12 surface configurations with a digital contact profilometer. Fractal dimensions were estimated based on these recorded profiles using the box-counting method. For comparison, conventional roughness parameters were measured as well. Tests with a pull-off strength testing device were performed on the applied PFS to quantify its adhesion to the substrates. The estimated pull-off tensile strength values were correlated with the estimated fractal dimensions. Design of Experiment (DoE) was applied to the test design in order to establish statistically sound relationships. Using a linear correlation model, it could be shown that fractal dimensions were suitable for quantifying the adhesion with a significantly higher accuracy than commonly used substrate (roughness) parameters.

Classified substrate roughness parameters of blast-cleaned steel substrates and their effects on fractal dimensions

Morphology and texture of substrate surfaces are crucial parameters for the establishment of reliable protective layers as they determine the performance of interlocking polymer-metal interfaces. Numerous parameters are known to characterize the morphology of metal substrates. In this study, mild steel samples were prepared using dry blast-cleaning with abrasive materials (metallic, minerals) of different particle shapes and particle sizes to investigate the effects of surface profile parameters on the fractal dimension. For this purpose, 2D profiles were taken from a total of 12 surface configurations with a digital contact profilometer. Fractal dimensions were estimated based on these recorded profiles using the box-counting method. For comparison, a total of 37 conventional roughness parameters were determined from the same set of measurements. Design of Experiment (DoE) was applied to evaluate significant interactions between roughness parameters and the corresponding fractal dimension. A new classification scheme for profile parameters, considering six profile sections, is suggested. A linear correlation model was utilized to rank the importance of roughness parameters, and of the surface profile sections, on the resulting fractal dimensions. Evidence is provided on which roughness parameter can be used to best explain fractal dimensions.

Structure function-based fractal characterisation of cylinder bore surfaces using stylus profile data

This paper investigates the possibility of the characterisation of cylinder bore surfaces using the fractal parameters computed by means of the structure function derived from stylus profile data. For the study, the surface profile data were obtained from plateau honed grey cast iron cylinder liner surfaces produced with different surface topographies, using a stylus instrument. The logarithmic plot of the structure function based on the stylus data ascertained the bi–fractal nature of the cylinder bore surfaces. Hence, a pair of fractal dimension and topothesy, in addition to the corner frequency was computed by fitting a hyperbola on the structure function plot. The fractal parameter, topothesy, resulting from the stylus data were observed to bear a statistically significant correlation with the conventional roughness parameters and Abbott–Firestone curve–based functional parameters measured from the cylinder bore surface using stylus instrument.

Numerical and experimental analysis of surface roughness generated by shot peening

Shot peening, apart from its various projected effects, modifies also the surface state of treated components in terms of surface irregularities. Bearing in mind that both the macroscopic and the microstructure surface characteristics strongly affect the mechanical structures’ functionality, it is essential to carefully study the surface state of treated components. To assess the surface roughness evolution induced by shot peening, a 3D finite element model of the process is used to investigate surface topography alterations as a function of peening parameters and processing time.Discrete data obtained from the numerical simulations are subsequently elaborated to calculate the conventional roughness parameters. The results obtained from the numerical simulations, correspond quite well with the roughness values measured experimentally on shot peened specimens.It is indicated that the developed numerical model provides an efficient estimation of surface characteristics of shot peened specimens, in terms of surface roughness parameters and thus can be used to properly select the peening parameters considering the eventual surface roughness.

Characterization and robust filtering of multifunctional surfaces using ISO standards

Engineered surfaces containing lubrication pockets and directional surface texture can decrease wear and friction in sliding or rolling contacts. A new generation of multifunctional (MUFU) surfaces has been created by hard machining followed by robot-assisted polishing. The production method allows for a large degree of freedom in specifying surface topography defined by frequency, depth and volume of the lubricant retention valleys, as well as the amount of load bearing area and the surface roughness. The surfaces cannot readily be characterized by means of conventional roughness parameters due to the multi-process production method involved. A series of MUFU surfaces were characterized by using the ISO 13565 standard for stratified surfaces and it is shown that the standard in some cases is inadequate for the characterization of a MUFU surface. To improve the filtering of MUFU surfaces, the robust Gaussian regression filtering technique described in ISO 16610-31 is analyzed and discussed. By slight modifications it is shown how the robust Gaussian regression filter can be applied to remove the form and find a suitable reference surface for further characterization of the MUFU surfaces—even for surfaces with a moderate to small plateau region.

Fractal dimension analysis of machined surface depending on coated tool wear

The surface topography is characterized by parameters, such as a centerline average roughness R a and a maximum height roughness R max. While such parameters are useful to define the quality of surface, they are not sufficiently descriptive characteristics of surface. The reason is that the surface topography is nonstationary and multiscaled. It suggests that fractal dimension which can describe surface roughness invariant with length scale than conventional roughness parameters should be used in characterizing surface topography. Up to now, many fractal models have been developed and applied for the elastic–plastic contact, tribology, surface text and so on. However, no discussion has been made on the characteristics of tool wear. In this paper, the relation between surface roughness and fractal dimension depending on coated tool wear using a generalized formula is identified. The work-piece material used in the experiments was high-hardened die steel and machined surface were obtained with high-speed cutting conditions. The new fractal analysis is an effective tool for in-process monitoring of tool wear using the fractal characteristics of machined surfaces.

Quantitative characterization of the surface topography of cold rolled sheets — new approaches and possibilities

When processing cold rolled metal sheet with modified surfaces textures, the conventional roughness parameters are not sufficient to characterize aspects such as rolling mill wear phenomena, as well as sheet metal and lacquered surface, regarding their formability and/or gloss degree. Furthermore, metal sheet forming processes are increasingly focused on tribological parameters; where the sheet metal surface topography becomes a characteristic that shows great potential for process optimization. This work presents 3D surface characterization methods, searching on the basis of this characterization a correlation between the surface topography and the tribological behavior as well as the formability of Al 6016-T4 sheets.

共焦点光学系の走査型レーザ顕微鏡による表面凹凸形状測定と機能的ディジタルフィルタ処理

By using a confocal scanning laser microscope (SLM) which is commercially available, the topography data of surface texture can be easily obtained in a short time. However, unreasonable short-wavelength components tend to be included in the raw data, when compared with the data obtained through a contact stylus instrument. In order to eliminate such noisy components, a digital filtering process was proposed and its design procedure in the spatial frequency domain was developed. The functional performance of the digital filtering was discussed with regard to the surface texturescreated by several machining methods. A fairly good agreement was reached between the corrected SLM data and the reference data in respect of perspective 3-D plots and some conventional roughness parameters. On the other hand, this filtering process showed unsatisfactory effects on certain local geometry parameters of surface texture.

The surface topography of compacted agglomerates; a means to optimize compaction conditions

The measurement and quantification of the surface topography of single-ended die-pressed cylindrical compacts, prepared using agglomerated alumina powders at various values of compaction pressure and cylinder aspect ratio, are described and a means to study the deformation and breakdown of the agglomerates at the die walls is evaluated. A specially constructed non-contacting laser scanning profilometer, with associated hardware and software, is described and has been used to obtain the surface topographical profiles of the green alumina compacts. Selected data are reported and interpreted using conventional roughness parameters, autocorrelation functions, and bearing area curves. These computed parameters are used to elucidate the deformation characteristics of the agglomerates within the compacts. The deformation of the alumina agglomerates, at the planar (upper and lower) surfaces of the compacts, commences at very low compaction pressures and the inter-agglomerates surface pores are eventually annihilated at relatively high compaction pressures. The optimum normal pressure for the elimination of these inter-agglomerate surface pores, in the present alumina system, was determined as 74 MPa. The results obtained from the curved surface profiles of the compacts, as a function of the distance from the compression sourc,, show that the wall normal pressure distribution, along the height of the compact, decreases exponentially as a function of the height of the compact (from top to bottom).

超精密機械加工された高機能表面の微細形状測定とキャラクタリゼーション スパッタ型薄膜磁気ディスク表面の場合

The appropriate measuring method for the micro-irregularities on a magnetic rigid disk surface was proposed and the characterizing techniques for such minute topographic data have been developed to correlate with its tribological properties. In addition to the conventional roughness parameters, new statistical parameters for evaluating the textured disk surfaces such as modified structure function based on asperity peaks only, peak height distribution and mean slope near the peak were proposed to distinguish the subtle discrepancies among those textured disks and to estimate the frictional characteristics between a head unit and a disk. The main results obtained were as follows. (1) The preliminary disks with no sputter-coated films have shown the gradually decreasing coefficient of friction with the increased value of arithmetic average roughness R. up to 15 nm regardless of the texture. (2) In case of the disks coated with carbon layer or liquid lubricant film, the coefficient is greatly influenced by the height and number distribution of asperity peaks and/or the mean slope near the peaks that are evaluated with those statistical parameters presented in this paper.

Fractal-based characterization of surface texture

The concept of fractal dimension has been applied to analysis of surface roughness. The method is described and practical examples are given for surface profiles of stainless steel with various surface finishes. These examples illustrate how this technique describes surface texture in more detail than conventional roughness parameters and reveals systematic differences in texture depending on the surface treatment.

Frequency Analysis of Surfaces Machined Using Different Lubricants

The paper is concerned with surface roughness analysis as a means of investigating lubricant action in cutting. An experimental setup involving a high-resolution signal analyzer has been used to obtain power spectrum characteristics, as well as conventional surface roughness parameters, of surfaces machined using different work materials and cutting fluids. Across the lay, conventional roughness parameters are dominated by the feed marks, and discrimination between different lubricating conditions is difficult. Frequency analysis, on the other hand, permits one to isolate the feed component, thus making it possible to ascertain the effect of lubrication at other wavelengths. The lubricating action is even more pronounced when measurements are performed in the machining direction, though a larger scatter among the results is experienced here. The averaged power spectrum ratios of surface roughness measured in the direction of cutting are used to describe the lubricating action. Presented at the 37th Annual...