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The formation and subsequent growth of structural defects in an irradiated material can strongly influence the material's performance in technological and industrial applications. Predicting how the growth of defects affects material…

It is often of interest to perform clustering on longitudinal data, yet it is difficult to formulate an intuitive model for which estimation is computationally feasible. We propose a model-based clustering method for clustering objects that…

Methodology · Statistics 2020-05-19 Daniel K. Sewell , Yuguo Chen , William Bernhard , Tracy Sulkin

Emergent design failures are ubiquitous in complex systems, and often arise when system elements cluster. Approaches to systematically reduce clustering could improve a design's resilience, but reducing clustering is difficult if it is…

Physics and Society · Physics 2023-08-22 Pheerawich Chitnelawong , Andrei A. Klishin , Norman MacKay , David J. Singer , Greg van Anders

Deterministic simulations of the rate equations governing cluster dynamics in materials are limited by the number of equations to integrate. Stochastic simulations are limited by the high frequency of certain events. We propose a coupling…

Materials Science · Physics 2017-10-11 Pierre Terrier , Manuel Athènes , Thomas Jourdan , Gilles Adjanor , Gabriel Stoltz

Irradiation of materials in nuclear test reactors and power plants is known to alter the properties of the material. The irradiation event happening at pico- or nanosecond time scales are affecting the evolution and properties of the…

Modeling point defects at an atomic scale requires careful treatment of the long-range atomic relaxations. This elastic field can strongly affect point defect properties calculated in atomistic simulations because of the finite size of the…

Materials Science · Physics 2013-10-23 Céline Varvenne , Fabien Bruneval , Mihai-Cosmin Marinica , Emmanuel Clouet

Change detection in heterogeneous multitemporal satellite images is a challenging and still not much studied topic in remote sensing and earth observation. This paper focuses on comparison of image pairs covering the same geographical area…

Computer Vision and Pattern Recognition · Computer Science 2017-02-13 Luigi Tommaso Luppino , Stian Normann Anfinsen , Gabriele Moser , Robert Jenssen , Filippo Maria Bianchi , Sebastiano Serpico , Gregoire Mercier

Numerical simulations of clusters of galaxies provide a unique way to follow the dynamics of these systems. The models reveal many characteristics of the merging process of subclusters: shock structure and strength, temperature distribution…

Astrophysics · Physics 2007-05-23 Sabine Schindler

We present a novel approach for finding and evaluating structural models of small metallic nanoparticles. Rather than fitting a single model with many degrees of freedom, the approach algorithmically builds libraries of nanoparticle…

A review is given on the studies of formation of light clusters and heavier fragments in heavy-ion collisions at incident energies from several tens of MeV/nucleon to several hundred MeV/nucleon, focusing on dynamical aspects and on…

Nuclear Theory · Physics 2019-03-05 Akira Ono

This work proposes an ensemble clustering method using transfer learning approach. We consider a clustering problem, in which in addition to data under consideration, "similar" labeled data are available. The datasets can be described with…

Machine Learning · Computer Science 2020-01-22 Vladimir Berikov

Metal-organic frameworks (MOFs) are highly interesting and tunable materials. By incorporating spatial defects into their atomic structure, MOFs can be finetuned to exhibit precise chemical functionalities, extending their applicability in…

Materials Science · Physics 2025-04-08 Pieter Dobbelaere , Sander Vandenhaute , Veronique Van Speybroeck

A quantitative first-principles description of complex substitutional materials like alloys is challenging due to the vast number of configurations and the high computational cost of solving the quantum-mechanical problem. Therefore,…

Materials Science · Physics 2025-06-24 Adrian Stroth , Claudia Draxl , Santiago Rigamonti

A range of percolation models of cluster systems of composites is discussed. In the models the parameters of the clusters of a substance and inner boundaries were obtained by the Monte Carlo method, and the possibility of affecting the…

Materials Science · Physics 2017-08-18 Alexander Herega

Machine learning promises to deliver powerful new approaches to neutron scattering from magnetic materials. Large scale simulations provide the means to realise this with approaches including spin-wave, Landau Lifshitz, and Monte Carlo…

Computational Physics · Physics 2020-11-12 Anjana M. Samarakoon , D. Alan Tennant

The structure of defect clusters formed in a displacement cascade plays a significant role in the micro-structural evolution during irradiation. Molecular dynamics simulations have been widely used to study collision cascades and subsequent…

Computational Physics · Physics 2024-02-02 Utkarsh Bhardwaj , Andrea E. Sand , Manoj Warrier

Machine learning techniques can reveal hidden structure in large data amounts and can potentially extent or even replace analytical scientific methods. In nanophotonics, modes can increase the light yield from emitters located inside the…

Optics · Physics 2018-10-02 Carlo Barth , Christiane Becker

We consider the dynamics of pattern formation in a system of point defects under sustained irradiation within the framework of the rate theory. In our study we generalize the standard approach taking into account a production of defects by…

Materials Science · Physics 2013-09-25 V. O. Kharchenko , D. O. Kharchenko

We review recent experimental and theoretical progress in understanding the microscopic details of clustering in light nuclei. We discuss recent experimental results on $\alpha$-conjugate systems, molecular structures in neutron-rich…

Nuclear Theory · Physics 2018-08-30 Martin Freer , Hisashi Horiuchi , Yoshiko Kanada-En'yo , Dean Lee , Ulf-G. Meißner

In this tutorial-style review we discuss basic concepts of coupled cluster theory and recent developments that increase its computational efficiency for calculations of molecules, solids and materials in general. We will touch upon the…

Materials Science · Physics 2020-04-15 Igor Ying Zhang , Andreas Grüneis
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