English
Related papers

Related papers: Learning crystal plasticity using digital image co…

200 papers

Printing of metallic films has been preferred for roll-to-roll processes over vacuum technologies due to faster processing times and lower processing costs. Films can be produced by depositing inks containing suspended metallic particles…

Applied Physics · Physics 2019-07-18 C. Katsarelis , O. Glushko , C. Tonkin , M. S. Kennedy , M. J. Cordill

Deformation gradient tensor fields are reconstructed in three dimensions (mapping all 9 tensor components) using synthetic Dark-Field X-ray Microscopy data. Owing to the unique properties of the microscope, our results imply that the…

Materials Science · Physics 2025-09-09 Axel Henningsson , Sina Borgi , Grethe Winther , Anter El-Azab , Henning Friis Poulsen

The multi-scale nature of architectured materials raises the need for advanced experimental methods suitable for the identification of their effective properties, especially when their size is finite and they undergo extreme deformations.…

Applied Physics · Physics 2024-03-04 Filippo Agnelli , Pierre Margerit , Paolo Celli , Chiara Daraio , Andrei Constantinescu

A physically-informed continuum crystal plasticity model is presented to elucidate the deformation mechanisms and dislocation evolution in body-centered-cubic (bcc) tantalum widely used as a key structural material for mechanical and…

We develop a fully coupled theoretical description of dislocation dynamics on deformable crystalline surfaces, using continuum modeling and the amplitude-phase-field crystal (APFC) framework extended to curved geometries. We derive a…

Soft Condensed Matter · Physics 2026-02-17 Marcello De Donno , Luiza Angheluta , Marco Salvalaglio

Integrated digital image correlation (IDIC) is applied to identify the constitutive parameters of an elastic and two elastoplastic laws with kinematic hardening. An experiment is conducted on a cruciform specimen in a biaxial setup. The…

Classical Physics · Physics 2015-09-11 Morgan Bertin , F Hild , S Roux

Machine learning has significantly advanced the understanding and application of structural materials, with an increasing emphasis on integrating existing data and quantifying uncertainties in predictive modeling. This study presents a…

Materials Science · Physics 2025-06-27 Jing Luo , Yejun Gu , Yanfei Wang , Xiaolong Ma , Jaafar. A El-Awady

Fracture toughness ($K_\mathrm{Ic}$) and fracture strength ($\sigma_\mathrm{f}$) are key criteria in the selection and design of reliable ceramics. However, their experimental characterization remains challenging -- especially for ceramic…

Differential Dynamic Microscopy (DDM) analyzes traditional real-space microscope images to extract information on sample dynamics in a way akin to light scattering, by decomposing each image in a sequence into Fourier modes, and evaluating…

Soft Condensed Matter · Physics 2017-11-10 Fabio Giavazzi , Paolo Edera , Peter J. Lu , Roberto Cerbino

In medical image segmentation, particularly in UNet-like architectures, upsampling is primarily used to transform smaller feature maps into larger ones, enabling feature fusion between encoder and decoder features and supporting multi-scale…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Chengkun Sun , Jinqian Pan , Renjie Liang , Zhengkang Fan , Xin Miao , Jiang Bian , Jie Xu

The plasticity transition at the yield strength of a crystal typically signifies the tendency of dislocation defects towards relatively unrestricted motion. For an isolated dislocation the motion is in the slip plane with velocity…

Materials Science · Physics 2020-01-15 Péter Dusán Ispánovity , Stefanos Papanikolaou , István Groma

A comprehensive and systematic framework for easily extending and implementing the subset-based spatial-temporal digital image correlation (DIC) algorithm is presented. The framework decouples the three main factors (i.e. shape function,…

Computer Vision and Pattern Recognition · Computer Science 2019-01-23 Yuxi Chi , Bing Pan

Two-dimensional simulations of the coarsening process of the isotropic/smectic-A phase transition are presented using a high-order Landau-de Gennes type free energy model. Defect annihilation laws for smectic disclinations, elementary…

Soft Condensed Matter · Physics 2008-06-30 Nasser Mohieddin Abukhdeir , Alejandro D Rey

Coherent x-ray micro-diffraction and local mechanical loading can be combined to investigate the mechanical deformation in crystalline nanostructures. Here we present measurements of plastic deformation in a copper crystal of sub-micron…

Materials Science · Physics 2013-05-31 G. Beutier , M. Verdier , M. De Boissieu , B. Gilles , F. Livet , M. -I. Richard , T. W. Cornelius , S. Labat , O. Thomas

Progress toward a first-principles theory of plasticity and work-hardening is currently impeded by an insufficient picture of dislocation kinetics (the dynamic effect of driving forces in a given dislocation theory). This is because present…

Materials Science · Physics 2024-02-13 Joseph Pierre Anderson , Anter El-Azab

In this study, we present the first simulation results of the formation of dislocation cell wall microstructures in tantalum subjected to shock loading. Dislocation patterns and cell wall formation are important to understanding the…

Materials Science · Physics 2023-05-04 Jaehyun Cho , Luke L. Hsiung , Robert E. Rudd , Sylvie Aubry

Digital pathology images play a crucial role in medical diagnostics, but their ultra-high resolution and large file sizes pose significant challenges for storage, transmission, and real-time visualization. To address these issues, we…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 SeonYeong Lee , EonSeung Seong , DongEon Lee , SiYeoul Lee , Yubin Cho , Chunsu Park , Seonho Kim , MinKyung Seo , YoungSin Ko , MinWoo Kim

The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled roughly half a million annotated images of macromolecular crystallization experiments from various sources and setups. Here, state-of-the-art machine…

Diffusion models have demonstrated exceptional performances in various fields of generative modeling, but suffer from slow sampling speed due to their iterative nature. While this issue is being addressed in continuous domains, discrete…

Machine Learning · Computer Science 2025-05-12 Satoshi Hayakawa , Yuhta Takida , Masaaki Imaizumi , Hiromi Wakaki , Yuki Mitsufuji

Continuum dislocation dynamics (CDD) represents the evolution of systems of curved and connected dislocation lines in terms of density-like field variables which include the volume density of loops (or 'curvature density') as an additional…

Materials Science · Physics 2023-01-04 Xi Luo , Michael Zaiser