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A microscopic model of adsorption in cluster forming systems with competing interaction is considered. The adsorption process is described by the master equation and modelled by a kinetic Monte Carlo method. The evolution of the particle…

Soft Condensed Matter · Physics 2021-09-07 E. Bildanau , V. Vikhrenko

This paper presents a comprehensive analysis of simple models useful to analyze the growth of nanostructures obtained by cluster deposition. After detailing the potential interest of nanostructures, I extensively study the first stages of…

Materials Science · Physics 2015-06-25 Pablo Jensen

We present numerical simulations of the dynamical and chemical evolution of galaxy clusters. X-ray spectra show that the intra-cluster medium contains a significant amount of metals. As heavy elements are produced in the stars of galaxies…

Astrophysics · Physics 2007-05-23 W. Domainko , W. Kapferer , S. Schindler , E. van Kampen , S. Kimeswenger , M. Mair , M. Ruffert

Electrical resistivity evolution during precipitation in Al-Sc alloys is modeled using cluster dynamics. This mesoscopic modeling has already been shown to correctly predict the time evolution of the precipitate size distribution. In this…

Materials Science · Physics 2007-05-23 Emmanuel Clouet , Alain Barbu

Mode clustering is a nonparametric method for clustering that defines clusters using the basins of attraction of a density estimator's modes. We provide several enhancements to mode clustering: (i) a soft variant of cluster assignment, (ii)…

Methodology · Statistics 2015-12-23 Yen-Chi Chen , Christopher R. Genovese , Larry Wasserman

We present a universal method for the large-scale prediction of the atomic structure of clusters. Our algorithm performs the joint evolutionary search for all clusters in a given area of the compositional space and takes advantage of…

Materials Science · Physics 2018-12-18 S. V. Lepeshkin , V. S. Baturin , Yu. A. Uspenskii , Artem R. Oganov

We consider a two-dimensional Ising model with random i.i.d. nearest-neighbor ferromagnetic couplings and no external magnetic field. We show that, if the probability of supercritical couplings is small enough, the system admits a…

Disordered Systems and Neural Networks · Physics 2015-05-30 L. Bertini , Emilio N. M. Cirillo , E. Olivieri

Insight into structural and thermodynamic properties of nanoparticles is crucial for designing optimal catalysts with enhanced activity and stability. We present a semi-automated workflow for parameterizing the atomic cluster expansion…

We have studied the chemical enrichment history of the interstellar medium through an analysis of the n-dimensional stellar abundances space. This work is a non-parametric analysis of the stellar chemical abundance space. The main goal is…

Solar and Stellar Astrophysics · Physics 2017-10-30 R. Boesso , H. J. Rocha-Pinto

In many applications of X-ray computed tomography, an unsupervised segmentation of the reconstructed 3D volumes forms an important step in the image processing chain for further investigation of the digitized object. Therefore, the goal is…

Computer Vision and Pattern Recognition · Computer Science 2023-03-09 Thomas Lang

Both ordered and disordered microphases ubiquitously form in suspensions of particles that interact through competing short-range attraction and long-range repulsion (SALR). While ordered microphases are more appealing materials targets,…

Soft Condensed Matter · Physics 2022-05-03 Yi Hu , Patrick Charbonneau

In many evolutionary stages, low- and intermediate-mass stars show signs of mixing of the surface material with material from the interior. To account for all the details revealed by the observations it is necessary to include non-standard…

Solar and Stellar Astrophysics · Physics 2011-07-01 Rodolfo Smiljanic

The isothermal compressibility of a general crystal is analyzed within classical density functional theory. Our approach can be used for homogeneous and unstrained crystals containing an arbitrarily high density of local defects. We start…

Soft Condensed Matter · Physics 2015-11-18 Johannes Häring , Christof Walz , Grzegorz Szamel , Matthias Fuchs

We study the nucleation of crystalline cluster phases in the generalized exponential model with exponent n=4. Due to the finite value of this pair potential for zero separation, at high densities the system forms cluster crystals with…

Soft Condensed Matter · Physics 2016-09-01 Christian Leitold , Christoph Dellago

Clustering is an essential data mining tool that aims to discover inherent cluster structure in data. For most applications, applying clustering is only appropriate when cluster structure is present. As such, the study of clusterability,…

Machine Learning · Statistics 2018-10-30 A. Adolfsson , M. Ackerman , N. C. Brownstein

The determination of cluster centers generally depends on the scale that we use to analyze the data to be clustered. Inappropriate scale usually leads to unreasonable cluster centers and thus unreasonable results. In this study, we first…

Machine Learning · Statistics 2016-10-20 Xiurui Geng , Hairong Tang

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

A detailed simple model is applied to study a metallic cluster. It is assumed that the ions and delocalized electrons are distributed randomly throughout the cluster. The delocalized electrons are assumed to be degenerate. A spherical ball…

Materials Science · Physics 2011-03-01 Yuri Kornyushin

Clustering ensemble, or consensus clustering, has emerged as a powerful tool for improving both the robustness and the stability of results from individual clustering methods. Weighted clustering ensemble arises naturally from clustering…

Computer Vision and Pattern Recognition · Computer Science 2021-12-14 Mimi Zhang

Clustering techniques are very attractive for extracting and identifying patterns in datasets. However, their application to very large spatial datasets presents numerous challenges such as high-dimensionality data, heterogeneity, and high…

Databases · Computer Science 2018-02-27 Malika Bendechache , Nhien-An Le-Khac , M-Tahar Kechadi
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