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Microstructural geometry plays a critical role in the response of heterogeneous materials. Consequently, methods for generating microstructural samples are increasingly crucial to advanced numerical analyses. We extend Sonon et al.'s…

Computational Geometry · Computer Science 2020-03-13 Martin Doškář , Jan Zeman , Daniel Rypl , Jan Novák

This paper is about similarity between objects that can be represented as points in metric measure spaces. A metric measure space is a metric space that is also equipped with a measure. For example, a network with distances between its…

Discrete Mathematics · Computer Science 2020-11-03 Evgeny Dantsin , Alexander Wolpert

This monograph introduces key concepts and problems in the new research area of Periodic Geometry and Topology for materials applications.Periodic structures such as solid crystalline materials or textiles were previously classified in…

Computational Geometry · Computer Science 2021-06-10 Olga Anosova , Vitaliy Kurlin

Accurately measuring the size, morphology, and structure of nanoparticles is very important, because they are strongly dependent on their properties for many applications. In this paper, we present a deep-learning based method for…

Materials Science · Physics 2022-07-29 Claudius Zelenka , Marius Kamp , Kolja Strohm , Akram Kadoura , Jacob Johny , Reinhard Koch , Lorenz Kienle

Recent developments of imaging techniques enable researchers to visualize materials at the atomic resolution to better understand the microscopic structures of materials. This paper aims at automatic and quantitative characterization of…

Materials Science · Physics 2018-05-11 Jianfeng Lu , Haizhao Yang

In this paper, we predict the effect of texture on the anisotropy in plastic properties of polycrystalline metallic sheets. The constituent grain behavior is modelled using the new single crystal yield criterion developed by Cazacu, Revil,…

Materials Science · Physics 2018-08-01 Nitin Chandola , Oana Cazacu , Benoit Revil-Baudard

When modeling microstructures, the computational resource requirements increase rapidly as the simulation domain becomes larger. As a result, simulating a small representative fraction under periodic boundary conditions is often a necessary…

Particle-wall interactions play a crucially important role in various applications such as microfluidic devices for cell sorting, particle separation, entire class of hydrodynamic filtration and its derivatives, etc. Yet, accurate…

Fluid Dynamics · Physics 2025-03-18 Aryan Mehboudi , Shrawan Singhal , S. V. Sreenivasan

With the evolution of new manufacturing technologies such as multi-material 3D printing, one can think of new type of objects that consist of considerably less, yet heterogeneous, material, consequently being porous, lighter and cheaper,…

A crystal lattice, when confined to the surface of a cylinder, must have a periodic structure that is commensurate with the cylinder circumference. This constraint can frustrate the system, leading to oblique crystal lattices or to…

Soft Condensed Matter · Physics 2013-07-03 D. A. Wood , C. D. Santangelo , A. D. Dinsmore

Materials with nanoscale phase separation are considered. These materials are formed by a mixture of several phases, so that inside one phase there exist nanosize inclusions of other phases, with random shapes and random spatial locations.…

Mesoscale and Nanoscale Physics · Physics 2014-03-31 V. I. Yukalov , E. P. Yukalova

The reader is informed about a method for the objective identification of the plane symmetry group of a "noisy" crystal pattern. Without giving numerical details, this information theory based method is applied to two beautiful pieces of…

Computational Physics · Physics 2023-05-03 Peter Moeck

3D microstructural datasets are commonly used to define the geometrical domains used in finite element modelling. This has proven a useful tool for understanding how complex material systems behave under applied stresses, temperatures and…

Machine Learning · Computer Science 2022-10-14 Steve Kench , Isaac Squires , Amir Dahari , Samuel J Cooper

A suitable measure for the similarity of shapes represented by parameterized curves or surfaces is the Fr\'echet distance. Whereas efficient algorithms are known for computing the Fr\'echet distance of polygonal curves, the same problem for…

Computational Geometry · Computer Science 2007-05-23 Helmut Alt , Maike Buchin

Natural materials often feature a combination of soft and stiff phases, arranged to achieve excellent mechanical properties, such as high strength and toughness. Many natural materials have even independently evolved to have similar…

Soft Condensed Matter · Physics 2025-07-03 Chelsea Fox , Kyrillos Bastawros , Tommaso Magrini , Chiara Daraio

Graphene, a single atomic layer of graphitic carbon, has attracted intense attention due to its extraordinary properties that make it a suitable material for a wide range of technological applications. Large-area graphene films, which are…

Mesoscale and Nanoscale Physics · Physics 2015-02-18 Oleg V. Yazyev , Yong P. Chen

Dislocations - linear defects within the crystal lattice of, e.g., metals - already have been directly observed and analyzed for nearly a century. While experimental characterization methods can nowadays reconstruct three-dimensional…

Materials Science · Physics 2016-05-19 Dominik Steinberger , Riccardo Gatti , Stefan Sandfeld

Precise determination of the solid-state microstructure of semiconducting polymers is of paramount importance for the further development of these materials in various organic electronic technologies. Yet, prior characterization of the…

A micromorphic computational homogenization framework has recently been developed to deal with materials showing long-range correlated interactions, i.e. displaying patterning modes. Typical examples of such materials are elastomeric…

Soft Condensed Matter · Physics 2024-06-21 S. Maraghechi , O. Rokoš , R. H. J. Peerlings , M. G. D. Geers , J. P. M. Hoefnagels

Motivated by the statistical and computational challenges of computing Wasserstein distances in high-dimensional contexts, machine learning researchers have defined modified Wasserstein distances based on computing distances between…

Probability · Mathematics 2022-06-02 Jiaqi Xi , Jonathan Niles-Weed