Nanoscratching of iron: A novel approach to characterize dislocation microstructures

Gunkelmann, Nina; Alhafez, Iyad Alabd; Steinberger, Dominik; Urbassek, Herbert M.; Sandfeld, Stefan

doi:10.1016/j.commatsci.2017.04.008

Cited by 16 publications

(7 citation statements)

References 35 publications

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“…More recently, efforts are made in studying plasticity of iron during contact loading. [39][40][41] The focus of these studies was primarily to study the plasticity in the iron substrate, so the diamond tool was either considered rigid or was modelled with a hypothetical potential. In this article, a fully parameterized potential function for iron and carbon was used to reveal insights into the chemical interaction and to model realistic forces for a better comparison of EVAM with conventional cutting of iron with a diamond cutting tool.…”

Section: Maximum Vertical Vibration Velocity Vy Max = Bωmentioning

confidence: 99%

Molecular dynamics simulation of the elliptical vibration-assisted machining of pure iron

Goel

Martinez

Chavoshi

et al. 2018

Journal of Micromanufacturing

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It is well known that diamond wears out rapidly (within several metres of cutting length) when machining low carbon ferrous alloys and pure iron. The past few years have seen a growing interest in the field of elliptical vibration-assisted machining (EVAM) due to it being successful in the micromachining of difficult-to-cut materials including steel. During EVAM, a cutting tool is prescribed an oscillatory motion perpendicular to the direction of cutting, thereby causing the tool to be relieved intermittently from chemical and physical contact with the workpiece. This phenomenon serves as a guideline to develop the simulation test bed for studying EVAM in this work to compare it with conventional cutting. The pilot implementation of the EVAM came as a quasi-3-dimensional (Q3D) elliptical cutting model of body-centred cubic (BCC) iron with a diamond cutting tool using molecular dynamics (MD) simulation. The developed MD model supplemented by the advanced visualization techniques was used to probe the material removal behaviour, the development of the peak stress in the workpiece and the way the cutting force evolves during the cutting process. One of the key observations was that the cutting chips of BCC iron during conventional cutting underwent crystal twinning and became polycrystalline, while EVAM resulted in cutting chips becoming highly disordered, leading to better viscous flow compared to conventional cutting.

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Section: Maximum Vertical Vibration Velocity Vy Max = Bωmentioning

confidence: 99%

Molecular dynamics simulation of the elliptical vibration-assisted machining of pure iron

Goel

Martinez

Chavoshi

et al. 2018

Journal of Micromanufacturing

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“…We will therefore take a new approach: Based on the discrete-to-continuous (D2C) framework (Sandfeld and Po, 2015;Steinberger et al, 2016), which "borrows" the field variables of a continuum theory of dislocation dynamics. This method was already successfully used to study the emergent microstructural features of molecular dynamics simulations of plastic deformation via scratching (Gunkelmann et al, 2017) and during shock loading (Kositski et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Machine Learning-Based Classification of Dislocation Microstructures

2019

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Dislocations-the carrier of plastic deformation-are responsible for a wide range of mechanical properties of metals or semiconductors. Those line-like objects tend to form complex networks that are very difficult to characterize or to link to macroscopic properties on the specimen scale. In this work a machine learning based approach for classification of coarse-grained dislocation microstructures in terms of different dislocation density field variables is used. The performance of the model combined with domain knowledge from the underlying physics helps to shed light on the interplay between coarse-graining voxel size and the set of suitable or even required density variables for a faithful microstructure characterization.

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“…The dominant regimes are governed by some sliding parameters such as invasion depth, sliding velocity, and surface lubrication conditions. Gunkelmann et al [27] carried out MD simulations of (a) nanoscratching on iron, and the dislocation microstructure was characterized using continuum field quantities from continuous dislocation dynamics theory [28]. The mechanical response of the material is then linked to the evolution of the dislocation field quantities.…”

Section: Introductionmentioning

confidence: 99%

Multiscale study of the dynamic friction coefficient due to asperity plowing

Song

Sandfeld

et al. 2020

Friction

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A macroscopically nominal flat surface is rough at the nanoscale level and consists of nanoasperities. Therefore, the frictional properties of the macroscale-level rough surface are determined by the mechanical behaviors of nanoasperity contact pairs under shear. In this work, we first used molecular dynamics simulations to study the non-adhesive shear between single contact pairs. Subsequently, to estimate the friction coefficient of rough surfaces, we implemented the frictional behavior of a single contact pair into a Greenwood-Williamson-type statistical model. By employing the present multiscale approach, we used the size, rate, and orientation effects, which originated from nanoscale dislocation plasticity, to determine the dependence of the macroscale friction coefficient on system parameters, such as the surface roughness, separation, loading velocity, and direction. Our model predicts an unconventional dependence of the friction coefficient on the normal contact load, which has been observed in nanoscale frictional tests. Therefore, this model represents one step toward understanding some of the relevant macroscopic phenomena of surface friction at the nanoscale level.

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Nanoscratching of iron: A novel approach to characterize dislocation microstructures

Cited by 16 publications

References 35 publications

Molecular dynamics simulation of the elliptical vibration-assisted machining of pure iron

Molecular dynamics simulation of the elliptical vibration-assisted machining of pure iron

Machine Learning-Based Classification of Dislocation Microstructures

Multiscale study of the dynamic friction coefficient due to asperity plowing

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