Laser surface treatment of Al-12%Si alloy

Abbas, M; Mahmoud, Adel K.

doi:10.1016/j.matpr.2017.06.308

Cited by 7 publications

(2 citation statements)

References 2 publications

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“…Therefore, surface modification is usually necessary for many Al-Si alloy products. Laser cladding, thermal spraying, anodic oxidation, and micro-arc oxidation (i.e., plasma electrolytic oxidation) are effective technologies to enhance the surface performance of Al-Si alloys [4][5][6][7]. Among them, anodic oxidation and microarc oxidation (MAO) are powerful approaches to deposit strong joint-strength layers on workpieces with complex shapes.…”

Section: Introductionmentioning

confidence: 99%

Tuning the Surface Characteristic of Al-Si Alloys and Its Impacts on the Formation of Micro Arc Oxidation Layers

et al. 2021

Coatings

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Aluminum Silicon (Al-Si) alloys are the most important among cast alloys and have widespread application. The β-Si phase is detrimental to the growth of micro arc oxidation (MAO) layers on Al-Si alloys. In this paper, the β-Si in the skin layer of different Al-Si alloys was removed by an acid etching pretreatment. Then, the impacts of different etching condition on their MAO process were investigated. Results show that, as etching time was prolonged, the Si content on the surface of Al-12 Si was decreased greatly (less than 0.5 wt.%), and the average size of pores left on the sample surface was increased gradually. This then led to the occurrence of some bigger and more drastic discharge sparks at the earlier oxidation stage. The corresponding layers had a higher ratio of Al2O3 and better corrosion resistance after 30 min of oxidation. Moreover, a 60 s etching pretreatment benefitted and boosted the growth rate and energy efficiency of layers on the Al-9 Si, Al-12 Si and Al-15 Si alloys. Such pretreatment was believed to be applicable to restrain the negative effects of Si on the MAO of different Al-Si alloys.

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Section: Introductionmentioning

confidence: 99%

Tuning the Surface Characteristic of Al-Si Alloys and Its Impacts on the Formation of Micro Arc Oxidation Layers

et al. 2021

Coatings

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“…Figure 18 shows the variation of wear loss for different wt.% of reinforcements. The wear loss decreases as the reinforcements increases for all the load conditions of 10 N, 20 N and 30 N. Compared to pure alloy, the composite has considerable wear resistance that can be attributed to higher values of hardness possessed by ZrO 2 particles and slipperiness produced by the higher temperature at the wear interface due to the applied load [33][34][35][36]. Figure 19 depicts the SEM images of worn surface during wear tests for different compositions.…”

Section: Wear Behaviourmentioning

confidence: 99%

Investigations on mechanical and wear behaviour of graphene and zirconia reinforced AA6061 hybrid nanocomposites using ANN and Sugeno-type fuzzy inference systems

Jayakumar

Bharathiraja

et al. 2022

Mater. Res. Express

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This research work investigates the mechanical and wear behaviour of graphene (C) and zirconium dioxide (ZrO2) reinforced Aluminium alloy 6061 hybrid nanocomposites (AMMHNCs) fabricated by the ultrasonic-assisted stir casting method. Graphene and ZrO2 are selected as reinforcements for increasing the wear resistance and hardness of the base alloy AA6061. The mixing proportions of graphene and ZrO2 reinforced with AA6061 in weight are 100% AA6061 / 0% Graphene / 0% ZrO2, 98.5% AA6061 / 0.5% Graphene / 1% ZrO2, 97.5% AA6061 / 0.5% Graphene / 2% ZrO2, 98% AA6061 / 1% Graphene / 1% ZrO2, 97% AA6061 / 1% Graphene / 2% ZrO2. A microstructural study was carried out using optical and scanning electron microscopic images to analyze the dispersion of reinforcements in the composite. The results show that the ultrasonic-assisted stir casting method improves the uniformity in the dispersion of reinforcements. The hardness, tensile, impact, and wear tests were carried out based on ASTM standards to analyze the properties of the proposed composite specimens. It was observed that the hardness, tensile strength, and impact strength increased by 21.88%, 69.42%, and 78.57% respectively, and percentage elongation decreased by 63.52% with the increase of reinforcements. Wear resistance increases with the increase of reinforcements. In order to analyze the wear behavior originality of new composite underwear test parameters, Artificial Neural Network (ANN) and Artificial Neuro-Fuzzy Inference Systems (ANFIS) models were used to predict the wear rate for experimented and non-experimented parameters. The prediction analysis was useful in studying the wear behavior of the composite. Comparative analysis for ANN and ANFIS was performed and the results have shown that the ANFIS model predicted with an accuracy of R2 with 99.9%.

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Characterizing Laser-Modified Microstructures and Electrical and Mechanical Properties of Al-15.3%Si(wt.%) Alloys

Bashir

Iqbal

2023

J. of Materi Eng and Perform

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Laser surface treatment of Al-12%Si alloy

Cited by 7 publications

References 2 publications

Tuning the Surface Characteristic of Al-Si Alloys and Its Impacts on the Formation of Micro Arc Oxidation Layers

Tuning the Surface Characteristic of Al-Si Alloys and Its Impacts on the Formation of Micro Arc Oxidation Layers

Investigations on mechanical and wear behaviour of graphene and zirconia reinforced AA6061 hybrid nanocomposites using ANN and Sugeno-type fuzzy inference systems

Characterizing Laser-Modified Microstructures and Electrical and Mechanical Properties of Al-15.3%Si(wt.%) Alloys

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