Areal Autocorrelation Function Research Articles

Interwoven of γ-MnO2 and V2O5 nanostructures with polyindole grafted reduced graphene oxide nano-platform for high-efficient supercapacitors: A collaborated insight of experimental and surface morphological studies

The continuous evolution toward high-yield electronic devices with green and mechanical robust properties offers an emerging demand for polymeric nanocomposite electrodes. Herein, an efficient in-situ electro-synthesized route was pursued in designing novel reduced graphene oxide/polyindole (rGO/PIND) nanocomposite electrodes decorated by γ-MnO2 and V2O5 nanostructures. A nanosecond fiber laser was applied to synthesize V2O5 nanoparticles through laser ablation in liquid (LAL) technique and γ-MnO2 nanostructure was constructed by a solid-state reaction method. The fabricated electrodes were characterized by physical and electrochemical methods. To investigate the effect of the surface morphological features on the electrochemical (EC) performance of nanocomposite electrodes the surface statistical, Areal Autocorrelation Function (AACF), and fractal studies were carried out by using AFM analysis. These studies revealed the presence of nanoparticles results in more compactness and well-developed surface morphology with more roughness and irregularity. The electrochemical study of the design electrodes was performed in three and two-electrode setups. Two asymmetric supercapacitors (ASCs) of rGO//rGO/PIND/V2O5, rGO//rGO/PIND/γ-MnO2 were fabricated and characterized by physical and electrochemical methods. The rGO//rGO/PIND/γ-MnO2 ASSC device provided a superior specific capacitance (CS) of 165F g−1, energy density of 51.5 Wh kg−1, and power density of 3.7 kW kg−1 at 5.0 A g−1 with 95.7% retention of CS after 10,000 cycles and with a broad 1.50 V potential window. Additionally, the rGO/PIND/γ-MnO2//rGO/PIND/γ-MnO2 symmetric supercapacitor (SSC) device exhibited 28.5 Wh kg−1 energy density, and 6.8 kW kg−1 power density at 5.0 A g−1 with 92.8% retention capacitance after 10,000 cycles.

Surface fractality and crystallographic texture properties of mixed and mono metallic MOFs as a new concept for energy storage devices

Herein, fractality, morphology and crystallography studies as a novel approach were introduced to evaluate the effect of inorganic nodes on energy storage device performances of Ni/Co-BTC and Ni/Zn-BTC mixed metallic (MM) and Ni-BTC, Zn-BTC, and Co-BTC mono metallic (mM) MOFs electrode materials. Through XRD data, crystallographic texture studies were pursued by calculating crystallite size (D), interplanar space (dhkl), strain and dislocation density (ε,δ), and texture coefficients (TC(hkl)). Besides statistical studies, the Areal Autocorrelation Function (AACF) via AFM analysis was developed to investigate morphological features. Fractality results of electrochemical and physical methods verified the reliability of these methods for describing the pseudocapacitive nature of MM-MOF and mM-MOF electrode materials. Based on our findings, compared with mM-MOFs, Ni/Co-BTC and Ni/Zn-BTC MM-MOF electrodes with the beneficiary of the synergistic effect of mixed-metallic cations, smaller crystallite size (D=21.53 nm), higher maximum height (Sz=21.64 nm) with larger fractal dimensions (Df=2.58), and more interface width roughness (RMS=2.65 nm) offers an impressive architecture capable of pseudocapacitance storing charge. Therefore, Ni/Co-BTC and Ni/Zn-BTC MM-MOF electrodes offer the specific capacity of 263.8 and 203.3 mA h g−1 at 2.5 A g−1 with a dominant contribution of battery-like features.

On the linear transform technique for generating rough surfaces

The linear filtering model is widely adopted because it can effectively control the areal autocorrelation function (AACF). However, these methods either constrain only half of the AACF or add the assumption of symmetry along one coordinate axis, which leads to a limited scope of applicability of the model. In this paper, a new AACF constraint for all spatial information is present. The new constraint function can provide objectives for all AACFs, and thus both isotropic rough surfaces, anisotropic surfaces of arbitrary orientation, and cross-textured surfaces can be reconstructed. The numerical experimental results show that the AACF fits well for isotropic as well as arbitrarily oriented anisotropic surfaces. For cross-textures surfaces, the errors are significant, indicating that the linear filtering model still has potential for improvement.

Micromorphology analysis of sputtered indium tin oxide fabricated with variable ambient combinations

This study experimentally investigates the fractal nature of DC magnetron sputtered indium-tin oxide (ITO) fabricated utilizing mixed ambient combinations and post-annealed at 450 °C in air towards solar cell applications. The structural properties of the films were examined by X-ray diffraction technique. In addition, three-dimensional (3-D) surface morphology of the films was analyzed using the areal autocorrelation function and pseudo-topothesy K for the atomic force microscopy images. The fractal nature of films was co-related with respect to electrical and optical properties of ITO films prepared under five different ambient conditions.

An improved rough surface modeling method based on linear transformation technique

Abstract An effective rough surface model is the foundation for the evaluation of the contact, lubrication, friction and wear behaviors of engineering assemblies. This study first presented an investigation of the time series method, linear transformation method and Johnson transformation system. Then, an improved rough surface modeling method was proposed. The solving of the autocorrelation coefficient matrix was transformed to a nonlinear least squares problem and the analytical gradient formula was derived. The fast Fourier transform (FFT) method was further employed to improve the computational efficiency. Using this approach, rough surfaces with different autocorrelation function (ACF) and statistical parameters were generated and then compared with the prescribed surfaces. It was found that the ACF, areal autocorrelation function (AACF) and statistical parameters of the simulated surfaces were consistent with those of the prescribed surfaces. Moreover, an extremely good agreement was also found between the measured and generated grinding surfaces in terms of ACF, AACF and statistical parameters, which further proved the validity of the proposed method at large autocorrelation length. Therefore, the technique developed in this study may serve as a novel approach to generate rough surfaces with high efficiency and accuracy.

Microstructure of nickel nanoparticles embedded in carbon films: case study on annealing effect by micromorphology analysis

The presented study is aimed at analyzing the surface texture of amorphous hydrogenated carbon layers containing nickel nanoparticles (Ni‐NPs@a‐C:H) within their structure, which were deposited by Radio Frequency (RF) sputtering and RF‐Plasma Enhanced Chemical Vapor Deposition (RF‐PECVD) methods on glass substrates. Prepared films were then used as research material following their annealing at two different temperatures of 250 °C and 350 °C in an inert argon atmosphere. Series of height samples were taken with the help of atomic force microscopy (AFM) operating in a non‐contact mode and examined in order to determine their fractal characteristics. Raw AFM data were first plane‐fitted to remove the surface bow exhibiting the so‐called residual surface, and then numerically processed to calculate the Areal Autocorrelation Function (AACF), which was later used to compute the Structure Function (SF). The log–log plots of the latter served for calculation of fractal properties of surfaces under investigation, including fractal dimension D, and pseudo‐topothesy K. The analysis of 3‐D surface texture helps to understand their essential characteristics and their implications as well as graphical models and their implementation in computer simulation. Copyright © 2016 John Wiley & Sons, Ltd.

Influence of the artificial saliva storage on 3-D surface texture characteristics of contemporary dental nanocomposites.

The aim of this study was to analyse the influence of the artificial saliva on a three-dimensional (3-D) surface texture of contemporary dental composites. The representatives of four composites types were tested: nanofilled (Filtek Ultimate Body, FUB), nanohybrid (Filtek Z550, FZ550), microfilled (Gradia Direct, GD) and microhybrid (Filtek Z250, FZ250). The specimens were polymerised and polished by the multistep protocol (SuperSnap, Shofu). Their surface was examined, before and after 3 weeks' exposure to artificial saliva storage. The surface texture was analysed using the atomic force microscope (AFM). The obtained images were processed to calculate the areal autocorrelation function (AACF), anisotropy ratio Str (texture aspect ratio), and structure function (SF). The log-log plots of SF were used to calculate fractal properties, such as fractal dimension D, and pseudo-topothesy K. The analysis showed changes in surface anisotropy ratio Str values, which became higher, whereas the Sq roughness (root-mean-square) reduced after the artificial saliva storage. All the samples exhibited bifractal structure before the saliva treatment, but only half of them remained bifractal afterwards (GD, FZ250), whereas the other half turned into a monofractal (FUB, FZ550). The cube-count fractal dimension Dcc was found to be material- and treatment-insensitive.

Gold nanoparticles embedded in carbon film: Micromorphology analysis

In this paper the sputtered gold nanoparticles (NPs) deposited by Radio Frequency-Plasma Enhanced Chemical Vapor Deposition (RF-PECVD) method on the glass substrates in trace of amorphous hydrogenated carbon (Au NPs @ a-C: H) were analyzed to study the three-dimensional (3-D) surface texture. The prepared Au NPs @ a-C: H films were used as research materials. The synthesis of samples was carried out in different powers from 80 to 120W while all other parameters were kept constant. The X-ray diffraction patterns and UV–vis spectra were applied to study the structure and Localized Surface Plasmon Resonance (LSPR), respectively. An atomic force microscope in a non-contact mode was used to record the sample surface images then the fractal geometry was studied. The images were numerically processed to calculate the Areal Autocorrelation Function (AACF), which was used to determine the anisotropy ratio Str, and to compute the Structure Function (SF). The log–log plots of the latter were used to calculate fractal properties of the studied surfaces, such as fractal dimension D, and pseudo-topothesy K. The analysis of 3-D surface texture was helpful in optimizing the functional performance of the thin film.

Correlation of Surface Roping with Through-Thickness Microtextures in an AA6xxx Sheet

Strain-induced surface roughness was quantitatively correlated with microtexture spatial distributions from the surface to the midthickness of a strongly roping AA6016 sheet. The microtexture variations through the sheet were measured by acquiring a series of large area electron backscatter diffraction (EBSD) scans at intervals of about the grain size. The orientations of the different layers were translated into out-of-plane strains using a crystal plasticity model for comparison with the surface roping. The spatial distributions (particularly the characteristic wavelengths) of the microtexture layers were determined by areal auto-correlation functions, and quantitatively compared to the surface appearance by correlation coefficients. The results show that texture banding of Cube/Goss components along the rolling direction is present from the surface to midthickness but with significant variations from one grain layer to another. The wavelength correlation coefficient exhibits a maximum at about 55 μm, or 2 grain thicknesses, below the surface. It is shown that the spatial distribution of Cube/Goss components of the first three or four surface grain layers plays an important role in strong roping of AA6016 sheets.

Simulation of 3D Gaussian surface topography

Abstract Gaussian isotropic and anisotropic surfaces of desired areal autocorrelation function were modeled using procedures found in technical literature. Next measured 3D surfaces of normal ordinate distribution were tested. The special procedure was developed for simulating 3D surfaces after one-step honing. The similarities between the modeled and real areal autocorrelation functions were analysed. Measured and modeled surface topography parameters were also compared. It was found that surface topography modeling ensured good matching accuracy of statistical height parameters and slope. The uncertainty of other parameters was greater.

Surface characterisation-based tool wear monitoring in peripheral milling

In the last decade, the progress of surface metrology has led to improved 3D characterisation of surfaces, offering the possibility of monitoring manufacturing operations and providing highly detailed information regarding the machine tool condition. This paper presents a case study where areal surface characterisation is used to monitor tool wear in peripheral milling. Due to the fact that tool wear has a direct effect on the machined workpiece surface, the machined surface topography contains much information concerning the machining conditions, including the tool wear state. By analysing the often subtle changes in the surface topography, one can highlight the tool wear state. This paper utilises areal surface characterization, areal auto-correlation function (AACF) and pattern analysis to illustrate the effect of tool wear on the workpiece surface. The result shows the following: (1) tool wear, previously difficult to detect, will influence almost all of the areal surface parameters; (2) the pattern features of AACF spectrum can reflect the subtle surface texture variation with increasing tool wear. The authors consider that, combined analysis of the surface roughness and its AACF spectrum are a good choice for monitoring the tool wear state especially with the latest developments in on-machine surface metrology.

Modelling of fluid continuum considering 3D surface parameters in hydraulic assemblies

Friction in servo hydraulic assemblies reduces the response characteristics of the system. The friction is influenced by various factors including the geometry (form and surface errors) of the sliding surfaces. In this work, functionally significant 3D surface parameters from the Birmingham parameters are investigated for reduced friction. A 3D surface modelling approach is presented using random process modelling as the basis. An exponential decay areal autocorrelation function is used to model the grinding and honing processes which are commonly employed for the manufacture of the hydraulic assemblies. Honed surface is modelled with the crosshatches of appropriate angle. Method of surface modelling is validated using the data obtained through measurements on a practical surface. Different surface maps with varying surface parameters of the ground and honed surfaces are generated. The fluid continuum gap geometries of the hydraulic assemblies are modelled using these surface maps as envelopes. Pressure distribution, velocity and viscous friction force are used as measurands of the frictional characteristics. Using computational fluid dynamics (CFD) approach, these measurands are evaluated for different functionally significant Birmingham parameters. Based on further analysis, negative skewness, lower kurtosis values, higher valley fluid retention index were found to have lower frictional characteristics.

Surface analysis techniques to optimise the performance of CNC machine tools

A series of cutting trails have been carried out utilising milling operations and the development of chatter on the machmed surface has been analysed. 3D surface metrology techmques have been used to characterise the surface and particular attention has been paid to the use of Areal Auto Correlation Function (AACF) and Areal Power Spectral Densities (APSD). Both the AACF and APSD have been shown to effectively characterise the development and appearance of chatter and the implications of the use of these techniques for potentially controlling the machining process have been outlined.

Topographic features of cylinder liners — an application of three-dimensional characterization techniques

Studies of wear patterns on engine cylinder liners show that radial wear is greatest on the anti-thrust side, and close to top dead centre. As a result of this wear, surface topography features at different positions exhibit different characteristics. Quantitative representation of the features is helpful for functional analysis and functional control of cylinder liner manufacture. In this paper three-dimensional characterization techniques are applied to produce a comprehensive characterization of cylinder liner wear at different longitudinal positions. The areal autocorrelation function and the areal power spectrum reveal the changes in topographic features. The different topographic features of newly created, after running-in, severely worn and bore polished surfaces of cylinder liners are identified by quantitative functional indices. The characterization techniques and parameters used in the paper constitute an effective approach to the characterization of surface topography of cylinder liners and other tribological surfaces.

Model-based topography characterisation of machined surfaces in three dimensions

An integrated model-based approach has been proposed for the topography characterization of surfaces in three dimensions. The approach is the integration of advantages of several techniques, such as areal autocorrelation functions in the identification of surface features and the diagnostics of model adequacy; spectral analysis in the understanding of frequency components of surfaces. The approach is based on the Wold theorem, which justifies in theory the decomposition of a stationary, surface into deterministic and stochastic components. The deterministic constituent (as a periodic lay structure for most machined surfaces) may be modelled by a Fourier series. In contrast, the stochastic constituent may be represented by a spatial model. The developed model-based system, using the technique of data compression, has been applied successfully to the investigation of 3D topography features of some machined surfaces.