Pattern Edge Research Articles

Mixing intensification using sound-driven micromixer with sharp edges

Strong acoustic streaming can be generated inside a microchannel near sharp-edge structures. In this study, three Sharp-Edge Acoustic Streaming (SEAS) micromixers with multiple sharp edge patterns actuated by piezoelectric transducers are investigated. Direct Numerical Simulation (DNS) is used to numerically solve the multi-physics phenomenon involving acoustics, fluid dynamics and mass transfer. Experiments are carried out to validate the numerical results by visualization, as well as to evaluate micromixing performance with Iodide–Iodate Reactions. Influence of the sharp edge pattern (i.e. the spacing between individual structures, the number of sharp edges), channel throughput as well as acoustic intensity are studied. The shape of flow streamlines first unveils the interaction between acoustic streaming and main flow, which is shown to be a key for mixing enhancement. Following this, an optimal structure is found among the three mixers which allows achieving a decrease of micromixing time from 0.28 s to 0.03 s. Finally, a comparison with literature on passive mixers confirms the micromixing performance of SEAS mixer in terms of micromixing time at low Reynolds flow.

Highly Strained Silicon on Polymer Obtained By Temporary Polymer Wafer Bonding

Strain engineering can be called upon to tune the band structures of semiconductors. It is widely used in different types of microelectronics devices and it is expected to enable unprecedented responses in optoelectronics [1]. In the case of single crystal Silicon (sc-Si), several approaches have been proposed, relying either on the lattice mismatch inherent to hetero-epitaxial growth (Si on relaxed SiGe) or on substrate expansion (porous Si) [2, 3]. However, these methods are limited to bi-axial strain and by the maximum strain achievable in sc-Si thin film. We recently evaluated a method enabling to transfer a 200nm thick sc-Si film on a stretchable polymer substrate. Tensile tests proved that applying an external mechanical load on the substrate injected significant amounts of strain into sc-Si [4]. This work is focused on studying different parameters to improve the maximum strain in a Silicon On Polymer (SOP) stack obtained from a 200mm Silicon On Insulator (SOI) wafer using temporary polymer bonding.The overall fabrication process is described in figure 1(a). 2 × 24mm2 rectangles are defined using photolithography in a SOI thin film. The wafer is temporary bonded to a handling silicon substrate with a 40µm thick glue layer. Then, the backside of the SOI is removed with mechanical grinding and selective chemical etching. Finally, the sc-Si thin film is transferred to a 230µm thick flexible substrate thanks to a release layer between the glue and the sc-Si layer. The substrate is cut into tensile test samples as described in figure 1(a).In a previous study we have shown that a 200nm thick sc-Si film could be uniaxialy strained up to 1.5% along the [110] direction [4]. In the present work, we quantify the impact of strain orientation, sc-Si film thickness and pattern edge roughness on maximum uniaxial strain. In order to change the sc-Si film thickness a dry etching step was used after removing the backside of the SOI ubstrate. A soft lithography mask and a standard chrome 1X lithography mask were compared for the fabrication of rectangles. To achieve even smoother pattern edges, TetraMethylAmmonium Hydroxide (TMAH) etching was also used (for 90 minutes in a 25 %wt solution at 80◦C) on a patterned SOI with a silicon oxide layer as a hard mask. Resulting samples were tested on a uniaxial tensile stage coupled to a Raman spectrometer, giving us access simultaneously to the sample macroscopic strain and the silicon local strain.Tensile test results are summarized in figure 1(b). Reducing the thickness of the sc-Si did not improve the strain limit while better edges definitions did. Indeed, using TMAH, uniaxial strains up to 3% along [100] were reached in a 200nm thick sc-Si film on a flexible polymer substrate. These results are highly encouraging for the development of films with a wide range of strain. Furthermore, this method is easily transferable to other materials such as AlN or Ge.

(Invited) Epitaxial Growth of Ge/III-V Films and Hetero-Layer Lift-off for Ultra-Thin GeOI Fabrication

Monolithic 3D (M3D) integration has been thought of as an attractive idea to realize multi-functional heterogeneous integration devices. M3D integration enables us to combine logic devices with different functional devices such as memory, sensor, or optics to create extremely compact and efficient system-on-chips. Ge and III-V compound semiconductors are expected to be implemented as high mobility channel materials and optical components which cannot be realized with Si. The layer transfer technique with low processing temperature has great potential for stacking non-lattice-matched crystalline materials for M3D ICs. Here, we discuss the layer transfer technology utilizing high quality epitaxial growth, low-temperature direct bonding and advanced epitaxial lift-off (ELO) process, which reveals the applicability of transferred layers for heterogeneous integration.The low temperature ELO process is essential for realizing reliable layer transfer with different materials because the process is almost free from the issues of thermal expansion mismatch. Process flow of GaAs or Ge layer transfer with ELO process is described in Fig. 1. First of all, a lattice-matched single crystal GaAs or Ge layer is epitaxially grown on GaAs substrate with an AlAs release layer by MOCVD. Subsequently, Al2O3 layer is deposited on the epitaxial layer by atomic layer deposition (ALD). ALD Al2O3 layer serves as the buried oxide (BOX) and the passivation layer for Ge or GaAs surface. Then, Ge or GaAs layer is patterned using photolithography. The patterned GaAs or Ge/AlAs/GaAs donor wafer is then bonded on host substrate by direct bonding technique with wet activation process. Finally, the epitaxial GaAs or Ge layer is transferred on host substrates by splitting GaAs donor wafer from AlAs layer with HCl side etching thanks to extremely high etching selectivity. Note that the fabrication of patterned transfer layer is effective in shortening the required time of ELO process. In this ELO process, the thickness of a transferred layer can be control by epitaxial layer thickness. After the layer transfer process, the released donor GaAs wafer can be reclaimed and reused for the subsequent re-epitaxial growth to reduce the process cost.Figs. 2 (a) and (b) show cross-sectional SEM and TEM images of fabricated GeOI substrate with different BOX structures. Ge pattern edge shows no peeling from SiO2(100nm)/Si substrate, indicating strong bonding strength at the pattern edge. In Fig. 2 (b), the bonding interface is clearly observed at Al2O3(5nm)/SiO2(50nm) interface formed by the wet activation process. The bonding interface exhibits very smooth and no defect. There is no observable defect in transferred Ge layer, suggesting dislocation density is below TEM detection limit. Compared to Smart-CutTM technique, ELO process has significant advantages in terms of crystal quality, thickness control and the surface flatness thanks to totally low temperature processing.To reduce wafer-scale thickness variation, etching stopper (ES) technique with high etching selectivity is quite useful. As a donor wafer, we prepare Ge active layer (20nm)/SiGe ES layer (5nm)/Ge buffer layer/AlAs/GaAs structures. Here, the SiGe layer serves as ES against the etching of Ge buffer layer to control the final GeOI thickness and attain the wafer-scale thickness uniformity. In addition, Si passivation on Ge surface was performed during initial epitaxial growth of donor wafer since Si passivation was proved to be effective in reducing interfacial trap density (D it) between Ge and oxide. After ELO process, Ge buffer layer /SiGe ES layer/Ge active layer / Al2O3 /SiO2/Si heterostructure was obtained. Then, the top Ge buffer layer was removed in HCl/H2O2 solution. We found the etching selectivity was more than 30 between Ge and SiGe layer, which is high enough to yield very smooth SiGe surface. Finally, SiGe layer was removed by TMAH preferentially.Further conformal thinning of Ge active layer was performed by the cyclic dry oxidation/wet digital etching (DE) at room temperature. In addition to thickness control with the etching rate of about 0.8 nm/cycle, it is found that dozens digital etching (DDE) process is effective for reducing Ge surface roughness. Finally, UTB GeOI substrates with high crystal quality down to 3 nm have been successfully fabricated through SiGe ES and DDE processes. Ultra-smooth GeOI surface with reduced thickness fluctuation was confirmed after DDE by TEM cross-sectional images, resulting in significant improvement of device performances. Figure 1

Probing edge condition of nanoscale CoFeB/MgO magnetic tunnel junctions by spin-wave resonance

We investigate spin-wave resonance in nanoscale CoFeB/MgO magnetic tunnel junctions (MTJs) with a perpendicular easy axis and various free-layer sizes. Two types of MTJs are fabricated by different process conditions, and the spin-wave resonance is measured with homodyne-detected ferromagnetic resonance. We focus on the distance between resonance frequencies of the uniform and spin-wave modes as a function of the free-layer size in order to examine the effect of the edge state of MTJs. A marked difference is observed between the two types of MTJs, and the result is consistently reproduced by a model assuming free- or fixed-edge boundary conditions with or without reduced magnetic properties near the pattern edge for each MTJ. The obtained results indicate that the edge state of nanoscale MTJs is crucially affected by the process condition, and spin-wave resonance can serve as a sensitive probe for the edge condition.

Experimental Investigation of Microstructure-Related Scale Effect on Tensile Failure of Coal

We explored the microstructure-related scale effect on the tensile failure of coal. Disc specimens with different diameters (25 mm, 38 mm, 50 mm, and 75 mm) were processed for the Brazil split test. The influence of microstructures on fracture initiation and propagation was detected and analysed by the combination of X-ray computed tomography scanning, digital image correlation approach, and acoustic emission monitoring. The investigation indicated that tensile strength decreased with increasing specimen diameter, and the relationship can be described by an exponential equation. Four tensile failure modes were observed in specimens with different diameters, namely central, non-central, central edge, and central multiple pattern. Larger specimens exhibited more complicated failure patterns (central edge and central multiple failure patterns) and a greater percentage of shear failure fractures. Strain concentration and strain reversal were observed, respectively, in mineral—inclusion-rich regions and pre-existing discontinuities regions. This possibly contributed to fracture initiation, propagation, and coalescence. Fractures tended to grow along with the interface of mineral inclusion and coal matrix, and they could have propagated into and connect the pre-existing discontinuities. The greater volume of microstructure in larger specimens resulted in fractures that were more complex and may have increased the number of shear failure cracks and led to failure modes that were more complicated.

Direct X-ray and electron-beam lithography of halogenated zeolitic imidazolate frameworks.

Metal-organic frameworks (MOFs) offer disruptive potential in micro- and optoelectronics because of the unique properties of these microporous materials. Nanoscale patterning is a fundamental step in the implementation of MOFs in miniaturized solid-state devices. Conventional MOF patterning methods suffer from low resolution and poorly defined pattern edges. Here, we demonstrate the resist-free, direct X-ray and electron-beam lithography of MOFs. This process avoids etching damage and contamination and leaves the porosity and crystallinity of the patterned MOFs intact. The resulting high-quality patterns have excellent sub-50-nm resolution, and approach the mesopore regime. The compatibility of X-ray and electron-beam lithography with existing micro- and nanofabrication processes will facilitate the integration of MOFs in miniaturized devices.

Aeroacoustic design and broadband noise predictions of a fan stage with serrated outlet guide vanes

This work, realized in the framework of the European project TurboNoiseBB, presents an advanced aeroacoustic design methodology of Outlet Guide Vanes (OGVs) with leading edge serrations, including details on their broadband noise and aerodynamic performance. The serrated OGV corresponds to a modified stator from an aeroengine fan stage tested at the AneCom AeroTest’s facility (Germany). Sinusoidal leading edge patterns with varying amplitude and wavelength along the span are designed in collaboration with Safran Aircraft Engines. Serrations are adjusted to account for the turbulence characteristics provided by Reynolds-Averaged Navier–Stokes (RANS) calculations. Optimal parameters are found using simple design rules discussed in this paper. Down selection of serrated OGV designs (patent pending) is conducted through a RANS control of aerodynamic performances and in accordance with industrial specifications, ensuring acceptable penalties on the loss coefficient and isentropic efficiency. Broadband noise simulations are performed using a computational aeroacoustic (CAA) code that solves the linearized Euler equations with a synthetic turbulence model. Additionally, the acoustic response of the serrated leading edge airfoils is also estimated using the most relevant analytical formulation in the literature, based on the Wiener–Hopf technique. Numerical predictions at approach conditions are compared to available experimental measurements (on the untreated baseline case) and analytical Amiet-based and Wiener–Hopf solutions, showing satisfactory agreement in the sound power spectrum in the bypass duct. Finally, the acoustic performances estimated at the design stage are numerically assessed by both the CAA and Wiener–Hopf methods, providing around 2.5 dB and 3.5 dB reduction in the overall power level, respectively.

Frame overlap Bragg edge imaging

Neutron Bragg edge imaging enables spatially resolved studies of crystalline features through the exploitation and analysis of Bragg edges in the transmission spectra recorded in each pixel of an imaging detector. Studies with high spectral resolutions, as is required e.g. for high-resolution strain mapping, and with large wavelength ranges have been largely reserved to pulsed neutron sources. This is due to the fact, that the efficiency for high wavelength resolution measurements is significantly higher at short pulse sources. At continuous sources a large fraction of the available neutrons must be sacrificed in order to achieve high wavelength resolution for a relevant bandwidth e.g. through a chopper system. Here we introduce a pulse overlap transmission imaging technique, which is suited to increase the available flux of high wavelength resolution time-of-flight neutron Bragg edge imaging at continuous neutron sources about an order of magnitude. Proof-of-principle measurements utilizing a chopper with a fourfold repeated random slit distribution of eight slits were performed at a thermal neutron beamline. It is demonstrated, that disentanglement of the overlapping pulses is achieved with the correlation theorem for signal processing. Thus, the Bragg edge pattern can be reconstructed from the strongly overlapping Bragg edge spectra recorded and the results demonstrate the feasibility of the technique.

Contributions of runoff from paved farm roads to soil erosion in karst uplands under simulated rainfall conditions

In upland areas, paved farm roads (PFRs) change surface hydrological characteristics and may affect soil erosion. The effect of runoff from PFR (hereafter, road runoff) on soil erosion at the road shoulder edge was investigated at two rainfall intensities (50 and 75 mm/h) under laboratory conditions. Two road shoulder edges (i.e., acute angle (AA) and right angle (RA) intersections between the road shoulder and soil surface) were simulated at a 10° slope, and road runoff rates were applied of 0.4 and 0.6 m3/h, which are typical rates for a 2 m wide road under 50 and 75 mm/h rainfall intensity, respectively. A surface without road runoff served as a control (CK). The experiments showed that at the 50 mm/h rainfall intensity, no surface runoff was generated for the CK, while the mean surface runoff was 0.34 and 0.38 m3/h for RA and AA, respectively; at the 75 mm/h rainfall intensity, the mean runoff and sediment yields increased to 9–15 times that of the CK. The road runoff caused rill erosion, shortening the surface runoff initiation time and greatly increasing the sediment loss for AA and RA. Moreover, road shoulder edge patterns impacted soil erosion by influencing the confluence patterns of road runoff, surface runoff and rill development. Because the soil surface is low for AA, it promotes a more concentrated flow along the road shoulder than RA, potentially limiting lateral erosion and downward erosion during rainfall. Indeed, compared to AA, on average, the rill length for RA was 13%-28% shorter, the rill depth and width were 9%-65% greater; and the sediment yield was 26%-64% higher. Therefore, road runoff increases soil loss near the road shoulder, and it is necessary to either divert road runoff away from the shoulder or reduce flow erosivity through appropriate land management.

In vitro toxicity from a physical perspective of polyethylene microplastics based on statistical curvature change analysis

Microplastics which are gradually and randomly decompose into small fragment by exposure of physical and biological external stress are emerging as a significant threat to the all the environments. Here, we have demonstrated the in vitro toxicity of microplastics of two different shapes. To minimize the chemical effect, polyethylene (PE), was used. PE microplastics with two different shapes were prepared, high-density PE microbeads and irregularly ground low-density PE from bulk pellets. It is hypothesized that morphological characteristics and concentration of PE microplastics could affect cellular viability, immunity, and lysis. To quantify the randomness of the microplastic shape, the edge patterns of the generated PE microplastics were converted into numerical values and analyzed using a statistical method. A 10-fold difference in curvature value was observed between microbeads and ground microfragments. To correlate shape differences to toxicology, cells were exposed to PE microplastics on the demand of toxicology studies. We found that the higher concentration and rough structure were associated with the toxicity of plastics toward cells, pro-inflammatory cytokine release, and hemolysis, even though PE is buoyant onto medium. The PE microbeads did not exhibit severe cytotoxicity at any of the tested concentrations, but induced immune and hemolysis responses at high concentrations. When comparing the toxicity of different shapes of PE microplastics, we confirmed by statistical analysis that irregular-shape plastics with sharp edges and higher curvature differences may adversely affect cells, further having possibility to human toxicity in real environment.

Pattern Directive Sensing Selectivity of Graphene for Wearable Multifunctional Sensors via Femtosecond Laser Fabrication

AbstractGraphene has great potential in wearable sensors. However, the sensing selectivity of graphene‐based sensors is still a big challenge, limiting their application in the multifunctional sensors. Herein, different types and distributions of defects are introduced into graphene by femtosecond laser patterning to realize sensing selectivity for wearable multifunctional sensors. The imperfect graphene with four pattern arrays, circle, square, triangle, and hexagon with none, right, acute, and obtuse angle, is fabricated by laser to control the types and distributions of defects. The graphene with different patterns shows remarkable sensing selectivity, owing to the dangling bonds and vacancies on the edge of patterns. The graphene‐based sensor with the circle pattern array is used to detect the strain variation; the triangle one is for temperature detection; and the hexagon one can collect the information of gas. The gauge factor is demonstrated to be as high as ≈104. The as‐produced sensor with the above‐mentioned four patterns can simultaneously detect body pulse, temperature, and harmful gas by attaching to human body or clothes, offering real‐time health monitoring and protection. The patterned graphene‐based sensors with high sensing selectivity are expected to develop multifunctional sensor platform and versatile artificial electronic skin.

Temporal Fresnel diffraction induced by phase jumps in linear and nonlinear optical fibres

We analytically and numerically study the temporal intensity pattern emerging from the linear or nonlinear evolutions of a single or double phase jump in an optical fiber. The results are interpreted in terms of interferences of the well-known diffractive patterns of a straight edge, strip and slit and a complete analytical framework is derived in terms of Fresnel integrals for the case of purely dispersive evolution. When Kerr nonlinearity affects the propagation, various coherent nonlinear structures emerge according to the regime of dispersion.

45‐1: Invited Paper: Multi‐Spliced LCDs for Foldable Mobile Device ‐ Seamless Technology and Applications

This article presents the use of spliced LCD displays on foldable mobile devices. In order to achieve a perfect spliced display, we need to use a four‐sided narrow border design LCD and visual seamless technology. The article introduces two new techniques for ultra narrow borders and uses these two techniques to overcome the rainbow pattern and textual continuity of the seam edges between two adjacent LCD displays.

Hexagonal boron nitride with nanoslits as a membrane for water desalination: A molecular dynamics investigation

In this work, we investigate how nanoporous hexagonal boron nitride (hBN) membrane can achieve efficient water/ion separation using molecular dynamics simulations. In particular, it is interesting to figure out the transport mechanisms through slit-like orifices with different edge patterns, namely armchair, B-edged, and N-edged. It is observed that the water and ion conduction rates are sensitive to the edge patterns, which is attributed to the intriguing electrostatic interactions between hBN and solution particles. The armchair nanoslits barely discriminate ion from water molecules, whereas the nanoslits edged with zigzag patterns collaboratively impede ion permeation and allow fast water conduction. Our simulations not only support that hBN is a promising candidate for the development of permeable membrane for water desalination but also highlight the importance of nanoslit edge pattern. Together, this work will be helpful for the design of permeable membrane in the future.

Salt and pepper noise removal from images: An extensive analysis

In the process of image acquisition and transmission, the digital images are often corrupted with impulse noise. This is mainly because of the errors in the sensors or in the communication channel. It is highly imperative that this noise should be removed prior to its subjection for further processing, such as edge detection, image segmentation, object recognition, and pattern recognition. Various methods have been developed for salt and pepper noise removal from corrupted images. This paper analyses the various methods proposed for removal of salt and pepper noise from images.

A Multilayer Neural Network Merging Image Preprocessing and Pattern Recognition by Integrating Diffusion and Drift Memristors

With the development of research on novel memristor model and device, neural networks by integrating various memristor models have become a hot research topic recently. However, state-of-the-art works still build such neural networks using drift memristor only. Furthermore, some other related works are only applied to a few individual applications, including pattern recognition and edge detection. In this article, a novel kind of multilayer neural network is proposed, in which diffusion and drift memristor models are applied to construct a system merging image preprocessing and pattern recognition. Specifically, the entire network consists of two diffusion memristive cellular layers for image preprocessing and one drift memristive feedforward layer for pattern recognition. The experimental results show that good recognition accuracy of noisy MNIST is obtained due to the fusion of image preprocessing and pattern recognition. Moreover, owing to high-efficiency in-memory computing and brief spiking encoding methods, high processing speed, high throughput, and few hardware resources of the entire network are achieved.

State-Dependent Kernel Selection for Conditional Sampling of Graphs

This article introduces new efficient algorithms for two problems: sampling conditional on vertex degrees in unweighted graphs, and conditional on vertex strengths in weighted graphs. The resulting conditional distributions provide the basis for exact tests on social networks and two-way contingency tables. The algorithms are able to sample conditional on the presence or absence of an arbitrary set of edges. Existing samplers based on MCMC or sequential importance sampling are generally not scalable; their efficiency can degrade in large graphs with complex patterns of known edges. MCMC methods usually require explicit computation of a Markov basis to navigate the state space; this is computationally intensive even for small graphs. Our samplers do not require a Markov basis, and are efficient both in sparse and dense settings. The key idea is to carefully select a Markov kernel on the basis of the current state of the chain. We demonstrate the utility of our methods on a real network and contingency table. Supplementary materials for this article are available online.

Fully memristive spiking-neuron learning framework and its applications on pattern recognition and edge detection

Fully memristive neuron learning framework, which uses drift and diffusion memristor models to build an artificial neuron structure, becomes a hot topic recently with the development of memristor. However, some other devices like resistor or capacitor are still necessary in recent works of fully memristive learning framework. Theoretically, if one neuron is built by memristors only, the technique process will be simpler and learning framework will be more like biological brain. In this paper, a fully memristive spiking-neuron learning framework is introduced, in which a neuron structure is just built of one drift and one diffusion memristive models and spikes are used as transmission signals. The learning framework and spiking coding mode are simple and direct without any complicated calculation on hardware. To verify its merits, a feedforward neural network for pattern recognition and a cellular neural network for edge detection are designed. Experimental results show that compared to other memristive neural networks, processing speed of the proposed framework is very high, and the hardware resource is saved in pattern recognition. Further, due to the dynamic filtering function of diffusion memristor model in our learning framework, its peak signal noise ratio (PSNR) is much higher than traditional algorithms in edge detection.

Image Interpolation via Gradient Correlation-Based Edge Direction Estimation

This paper introduces an image interpolation method that provides performance superior to that of the state-of-the-art algorithms. The simple linear method, if used for interpolation, provides interpolation at the cost of blurring, jagging, and other artifacts; however, applying complex methods provides better interpolation results, but sometimes they fail to preserve some specific edge patterns or results in oversmoothing of the edges due to postprocessing of the initial interpolation process. The proposed method uses a new gradient-based approach that makes an intelligent decision based on the edge direction using the edge map and gradient map of an image and interpolates unknown pixels in the predicted direction using known intensity pixels. The input image is subjected to the efficient hysteresis thresholding-based edge map calculation, followed by interpolation of low-resolution edge map to obtain a high-resolution edge map. Edge map interpolation is followed by classification of unknown pixels into obvious edges, uniform regions, and transitional edges using the decision support system. Coefficient-based interpolation that involves gradient coefficient and distance coefficient is applied to obvious edge pixels in the high-resolution image, whereas transitional edges in the neighborhood of an obvious edge are interpolated in the same direction to provide uniform interpolation. Simple line averaging is applied to pixels that are not detected as an edge to decrease the complexity of the proposed method. Applying line averaging to smooth pixels helps to control the complexity of the algorithm, whereas applying gradient-based interpolation preserves edges and hence results in better performance at reasonable complexity.

RETRACTED ARTICLE: Local Directional Maximum Edge Patterns for facial expression recognition

Cognitive science and neuroscience use human facial expressions of emotion. Every single facial expression can be seen at different passions in a face space. Nowadays, facial expression recognition and analysis is vital due to the demand of introducing advanced biometric applications in every domain space. The imperative task in facial expressions of emotion classification is precise feature extraction, which helps to get detailed description of facial marks. Existing feature descriptors are suffering from various problems such as intensity variations, discrimination, vulnerability etc. In this paper, propose a new feature descriptor method called LDMEP (Local Directional Maximum Edge Patterns) for facial expression analysis to overcome the hindrance. We calculated the gradients in four directions of reference pixel to elicit the more feature for better recognition instead of calculating the local differences among neighboring pixels. We also access the orientations of the pixels then thresholded based on the dynamic threshold to avoid the featureless area calculation. Furthermore, we considered only dominant magnitude and orientation directions instead of all eight directions to generate feature. Thus, imperative and efficient features are covered in dominant positions to detect the strong edges. The paper confers that how the subsequent model can be used for the recognition of facial expression of emotion.