Mechanical characterization and interfacial enzymatic activity of AISI 316L stainless steel after surface nanocrystallization

Maleki, Erfan; Maleki, Nasim; Fattahi, Alborz; Ünal, Okan; Guagliano, Mario; Bagherifard, Sara

doi:10.1016/j.surfcoat.2020.126729

Cited by 27 publications

(13 citation statements)

References 57 publications

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“…[ 9 ] Surface texturing modifies the surface with the primary aim to generate patterns or textures with tiny features on the material surface to improve superficial functionalities. [ 10 ] These can include scratch and mar resistance, [ 11 ] tribological properties, [ 12 ] biological characteristics, [ 13 ] and energy‐related performances such as wettability and capillarity, [ 14 ] let alone aesthetics. The type and size of the generated features depend on the specific texturing technique.…”

Section: Introductionmentioning

confidence: 99%

Adapting Shot Peening for Surface Texturing Using Customized Additive Manufactured Shots

et al. 2023

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Surface textures in engineering materials not only affect the reflective properties and aesthetics but if properly designed can modulate surface‐related properties such as wettability, fatigue, wear, corrosion, and scratch resistance. Herein, a new surface texturing method is introduced based on the conventional shot peening process. Custom shots are designed, and their surface texturing capability is investigated on acrylonitrile butadiene styrene (ABS) polymer substrates. A finite‐element model is developed to bombard the substrate using AISI 316 stainless steel customized shots. The generated unique textures are compared qualitatively by visual examination and quantitatively using the standard surface roughness parameters. As a proof of concept, preliminary experiments are performed using a candidate custom shot and a spherical shot to treat the ABS sheets. The results highlight the high potential of the shot peening technique paired with additive manufacturing for customizing the peening media to be used for surface texturing polymeric materials.

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Section: Introductionmentioning

confidence: 99%

Adapting Shot Peening for Surface Texturing Using Customized Additive Manufactured Shots

et al. 2023

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“…However, combination of fatigue and corrosion simultaneously can afford faster failure and generally, amounts of damages caused by corrosion fatigue are higher [3]. Therefore, considering effective approaches to improve the corrosion resistance and fatigue have critical roles in this area [4,5]. To improve the corrosion resistance of conventionally manufactured materials (specially steels), varieties of treatments can be performed such as shot peening [6][7][8][9][10][11][12][13][14], carburizing [15][16][17], and plating [18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Application of Deep Neural Network to Predict the High-Cycle Fatigue Life of AISI 1045 Steel Coated by Industrial Coatings

Maleki

Ünal

Sahebari

et al. 2022

JMSE

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In this study, deep learning approach was utilized for fatigue behavior prediction, analysis, and optimization of the coated AISI 1045 mild carbon steel with galvanization, hardened chromium, and nickel materials with different thicknesses of 13 and 19 µm were used for coatings and afterward fatigue behavior of related specimens were achieved via rotating bending fatigue test. Experimental results revealed fatigue life improvement up to 60% after applying galvanization coat on untreated material. Obtained experimental data were used for developing a Deep Neural Network (DNN) modelling and accuracy of more than 99%.was achieved. Predicted results have a fine agreement with experiments. In addition, parametric analysis was carried out for optimization which indicated that coating thickness of 10–15 µm had the highest effects on fatigue life improvement.

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“…The failure can be prevented by the formation of nanocrystals on the surface. In recent decades, this technology has been successfully applied to various metals, such as nickel [2], stainless steel [3][4][5], low carbon steel [6,7], pure iron [8], aluminium and aluminium alloy [9], titanium and titanium alloy [10,11], cobalt [12], Ni 3 Al [13,14], copper and copper alloy [15][16][17][18][19][20], magnesium alloy [21][22][23], and Inconel 600 [24].…”

Section: Introductionmentioning

confidence: 99%

Correlation of stacking fault energy with deformation mechanism in Cu–(2, 20)Zn alloys

Wei

Jia

et al. 2022

Materials Science and Technology

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Copper–zinc alloys with different zinc contents contain different stacking fault energies (SFE). The influence of SFE on the deformation mechanism during surface mechanical attrition treatment was studied in this work. Research results indicate that the deformation mechanism directly correlated with the SFE in Cu–Zn alloys. Deformation twinning plays a paramount role during original deformation in Cu–20Zn (19 mJ/m2). However, for Cu–2Zn alloy with low-medium SFE (38 mJ/m2), the deformation mechanism is dominated by the dislocation slipping. Microbands are the predominant microstructural features in large strain and high strain rate regions for both Cu–Zn alloys in the present study. They are likely to be formed by the splitting of the high-density dislocation walls.

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Mechanical characterization and interfacial enzymatic activity of AISI 316L stainless steel after surface nanocrystallization

Cited by 27 publications

References 57 publications

Adapting Shot Peening for Surface Texturing Using Customized Additive Manufactured Shots

Adapting Shot Peening for Surface Texturing Using Customized Additive Manufactured Shots

Application of Deep Neural Network to Predict the High-Cycle Fatigue Life of AISI 1045 Steel Coated by Industrial Coatings

Correlation of stacking fault energy with deformation mechanism in Cu–(2, 20)Zn alloys

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