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Related papers: Machine learning plastic deformation of crystals

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The yield surface in crystal plasticity can be approached from various directions during mechanical loading. We consider the competition between nanoindentation and tensile loading towards plastic yielding. For this purpose, we develop a…

Materials Science · Physics 2017-07-14 Hengxu Song , Hakan Yavas , Erik Van der Giessen , Stefanos Papanikolaou

Machine learning models are susceptible to being misled by biases in training data that emphasize incidental correlations over the intended learning task. In this study, we demonstrate the impact of data bias on the performance of a machine…

Materials Science · Physics 2024-12-11 Ali Davariashtiyani , Busheng Wang , Samad Hajinazar , Eva Zurek , Sara Kadkhodaei

The ubiquitous appearance of regions of localized deformation (shear bands) in different kinds of disordered materials under shear is studied in the context of a mesoscopic model of plasticity. The model may or may not include relaxational…

Soft Condensed Matter · Physics 2015-05-19 E. A. Jagla

We deform, in pure shear, a thin sample of Cu$_{50}$Zr$_{50}$ metallic glass using a molecular dynamics simulation up to, and including, failure. The experiment is repeated ten times in order to have average values and standard deviations.…

Materials Science · Physics 2020-02-19 Matias Sepulveda-Macias , Gonzalo Gutierrez , Fernando Lund

The relative permittivity of a crystal is a fundamental property that links microscopic chemical bonding to macroscopic electromagnetic response. Multiple models, including analytical, numerical and statistical descriptions, have been made…

Materials Science · Physics 2020-07-15 Kazuki Morita , Daniel W. Davies , Keith T. Butler , Aron Walsh

High speed machining has been improved thanks to considerable advancement on the tools (optimum geometry, harder materials), on machined materials (increased workability and machining capacity for harder workpieces) and finally on the…

Classical Physics · Physics 2009-09-29 Olivier Cahuc , Alain Gérard

During development and under normal physiological conditions, biological tissues are continuously subjected to substantial mechanical stresses. In response to large deformations cells in a tissue must undergo multicellular rearrangements in…

Biological Physics · Physics 2025-04-08 Anh Q. Nguyen , Junxiang Huang , Dapeng Bi

Morphological development into evolutionary patterns under structural instability is ubiquitous in living systems and often of vital importance for engineering structures. Here we propose a data-driven approach to understand and predict…

Pattern Formation and Solitons · Physics 2024-07-23 Yingjie Zhao , Zhiping Xu

Fatigue simulation requires accurate modeling of unloading and reloading. However, classical ductile damage models treat deformations after complete failure as irrecoverable -- which leads to unphysical behavior during unloading. This…

Computational Engineering, Finance, and Science · Computer Science 2023-12-06 Leon Herrmann , Alireza Daneshyar , Stefan Kollmannsberger

Crystal plasticity is the result of the motion and interaction of dislocations. There is, however, still a major gap between microscopic and mesoscopic simulations and continuum crystal plasticity models. Only recently a higher dimensional…

Materials Science · Physics 2010-10-15 Thomas Hochrainer , Michael Zaiser , Peter Gumbsch

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either…

Materials Science · Physics 2018-04-10 Tian Xie , Jeffrey C. Grossman

Within the continuum dislocation theory the asymptotic analysis of the plane strain crack problem for a single crystal having only one active slip system on each half-plane is provided. The results of this asymptotic analysis show that the…

Materials Science · Physics 2015-08-17 Khanh Chau Le , Van Nha Tran

Predicting material properties of 3D printed polymer products is a challenge in additive manufacturing due to the highly localized and complex manufacturing process. The microstructure of such products is fundamentally different from the…

Soft Condensed Matter · Physics 2023-11-01 Caglar Tamur , Shaofan Li , Danielle Zeng

A model has been developed which simulates the deformation of single crystal austenitic stainless steels and cap-tures the effects of hydrogen on stress corrosion cracking. The model is based on the crystal plasticity theory which relates…

Materials Science · Physics 2019-10-21 E. I. Ogosi , U. B. Asim , M. A. Siddiq , M. E. Kartal

The plastic flow of a polycrystal is analyzed assuming grains as fine that the rate limiting process is grain boundary sliding, and grains readily accommodate their shapes by slip to preserve spatial continuity. It is shown that thinking of…

Materials Science · Physics 2009-11-19 Miguel Lagos , César Retamal

We present a framework which unifies classical phenomenological $J_2$ and crystal plasticity theories with quantitative dislocation mechanics. The theory allows the computation of stress fields of arbitrary dislocation distributions and,…

Soft Condensed Matter · Physics 2020-07-15 Rajat Arora , Amit Acharya

During plastic deformation, metals change shape while continuously becoming stronger. The microscopic origin of these processes lies in the proliferation and movement of line defects, dislocations, and the subsequent self-organisation and…

Strain can affect the morphology of a crystal surface, and cause modifications of its reconstruction even when weak, as in the case of mechanical bending. We carried out calculations of strain-dependent surface free energy and direct…

Materials Science · Physics 2007-05-23 U. Tartaglino , E. Tosatti , D. Passerone , F. Ercolessi

Atomistic simulations of the molecular dynamics/statics kind are regularly used to study small scale plasticity. Contemporary simulations are performed with tens to hundreds of millions of atoms, with snapshots of these configurations…

Materials Science · Physics 2022-06-17 Aruna Prakash , Stefan Sandfeld

Machine learning approaches informed by physics have offered new insights into the discovery of constitutive models from data, helping overcome some limitations of traditional constitutive modelling while reducing the cost of otherwise…

Materials Science · Physics 2026-05-19 Filippo Masi