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We have developed an image-based convolutional neural network (CNN) that is applicable for quantitative time-resolved measurements of the fragmentation behavior of opaque brittle materials using ultra-high speed optical imaging. This model…

Materials Science · Physics 2024-07-19 Erwin Cazares , Brian E. Schuster

This paper discusses some features of the spectral line profile theory used in the treatment of measured atomic transitions. It is shown that going beyond the established linear approximation for the spectral line contour in the case of its…

Atomic Physics · Physics 2024-05-03 D. Solovyev , A. Anikin , T. Zalialiutdinov

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

Scientists use imaging to identify objects of interest and infer properties of these objects. The locations of these objects are often measured with error, which when ignored leads to biased parameter estimates and inflated variance.…

Materials are often heterogeneous at various length scales, with variations in grain structure, defects, and composition which has a strong influence on the emergent macroscopic plastic behavior. In particular, heterogeneities lead to…

Materials Science · Physics 2024-06-17 Dénes Berta , David Kurunczi-Papp , Lasse Laurson , Péter Dusán Ispánovity

We propose a new modeling approach for scatter estimation and descattering in polyenergetic X-ray computed tomography (CT) based on fitting models to local neighborhoods of a training set. X-ray CT is widely used in medical and industrial…

Image and Video Processing · Electrical Eng. & Systems 2021-09-30 Michael T. McCann , Marc L. Klasky , Jennifer L. Schei , Saiprasad Ravishankar

Materials identification and structural understanding from powder X-ray diffraction (PXRD) data is a long-standing challenge in materials science, fundamental to discovering and characterizing novel materials. A prerequisite for full…

Twisted and rope-like assemblies of filamentous molecules are common and vital structural elements in cells and tissue of living organisms. We study the intrinsic frustration occurring in these materials between the two-dimensional…

Soft Condensed Matter · Physics 2015-06-03 Amir Azadi , Gregory M. Grason

Based on the cross correlation analysis of the Kikuchi diffraction patterns high-resolution EBSD is a well established method to determine the internal stress in deformed crystalline materials. In many cases, however, the stress values…

Materials Science · Physics 2017-04-05 Szilvia Kalácska , István Groma , András Borbély , Péter Dusan Ispánovity

Revealing the structure of complex biological macromolecules, such as proteins, is an essential step for understanding the chemical mechanisms that determine the diversity of their functions. Synchrotron based x-ray crystallography and…

Synchrotron Laue microdiffraction and Digital Image Correlation measurements were coupled to track the elastic strain field (or stress field) and the total strain field near a general grain boundary in a bent bicrystal. A 316L stainless…

In recent years there has been renewed interest in the behavior of dislocations in crystals that exhibit strong atomic scale disorder, as typical of compositionally complex single phase alloys. The behavior of dislocations in such crystals…

Materials Science · Physics 2021-10-26 Aviral Vaid , De'an Wei , Erik Bitzek , Samaneh Nasiri , Michael Zaiser

Dislocations are at the heart of the plastic behavior of crystalline materials yet it is notoriously difficult to perform quantitative, non-intrusive, measurements of their single or collective properties. Dislocation density is a critical…

Materials Science · Physics 2012-08-31 Nicolás Mujica , María Teresa Cerda , Rodrigo Espinoza , Judit Lisoni , Fernando Lund

We study the relationship between topological defect formation and ground-state packings in a model of repulsions in external confining potentials. Specifically we consider screened 2D Coulombic repulsions, which conveniently parameterizes…

Soft Condensed Matter · Physics 2021-10-04 Qingyou Meng , Gregory M. Grason

Recent advances in scanning transmission electron and scanning probe microscopies have opened exciting opportunities in probing the materials structural parameters and various functional properties in real space with angstrom-level…

Predicting the behaviour of complex systems is one of the main goals of science. An important example is plastic deformation of micron-scale crystals, a process mediated by collective dynamics of dislocations, manifested as broadly…

Materials Science · Physics 2022-06-03 Marcin Mińkowski , David Kurunczi-Papp , Lasse Laurson

In the present paper we propose to update the standard calculation of Stark line profiles for autoionizing atomic states in dense plasmas, i.e. warm dense matter and strongly coupled plasmas. This is motivated by the importance of taking…

Plasma Physics · Physics 2017-02-10 Y. J. Aouad

Plastic deformation mediated by collective dislocation dynamics is investigated in the two-dimensional phase-field crystal model of sheared single crystals. We find that intermittent fluctuations in the dislocation population number…

Materials Science · Physics 2015-01-05 Jens M. Tarp , Luiza Angheluta , Joachim Mathiesen , Nigel Goldenfeld

(Abridged, full abstract available in the text) The main goal of the study presented in this thesis was to perform in-situ investigations on deformation structures in plastically deformed polycrystalline copper at low degrees (<5%) of…

Materials Science · Physics 2009-09-29 Bo Jakobsen

Parameter inference and uncertainty quantification are important steps when relating mathematical models to real-world observations, and when estimating uncertainty in model predictions. However, methods for doing this can be…

Quantitative Methods · Quantitative Biology 2025-08-27 Michael J. Plank , Matthew J. Simpson