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Related papers: Neighborhoods and Functionality in Metals

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We survey the application of a relatively new branch of statistical physics--"community detection"-- to data mining. In particular, we focus on the diagnosis of materials and automated image segmentation. Community detection describes the…

Materials Science · Physics 2017-11-22 Z. Nussinov , P. Ronhovde , Dandan Hu , S. Chakrabarty , M. Sahu , Bo Sun , N. A. Mauro , K. K. Sahu

Gold clusters Aun of size n = 2 to 12 atoms were studied by the density-functional theory with an ab-initio pseudopotential and a generalized gradient approximation. Geometry optimizations starting from a number of initial candidate…

Other Condensed Matter · Physics 2007-05-23 Prashant K. Jain

We present a first-principles methodology, within the context of linear-response theory, that greatly facilitates the perturbative study of physical properties of metallic crystals. Our approach builds on ensemble density-functional theory…

Materials Science · Physics 2024-01-31 Asier Zabalo , Massimiliano Stengel

We apply a number of atomic decomposition schemes across the standard QM7 dataset -- a small model set of organic molecules at equilibrium geometry -- to inspect the possible emergence of trends among contributions to atomization energies…

Chemical Physics · Physics 2023-04-19 Frederik Ø. Kjeldal , Janus J. Eriksen

Functional data clustering is to identify heterogeneous morphological patterns in the continuous functions underlying the discrete measurements/observations. Application of functional data clustering has appeared in many publications across…

Methodology · Statistics 2022-10-04 Mimi Zhang , Andrew Parnell

The chemistry (composition and bonding information) of metallic glasses (MGs) is at least as important as structural topology for understanding their properties and production/processing peculiarities. This article reports a machine…

Materials Science · Physics 2020-11-18 Ary R. Ferreira

Complex crystal structures are composed of multiple local environments, and how this type of order emerges spontaneously during crystal growth has yet to be fully understood. We study crystal growth across various structures and along…

Soft Condensed Matter · Physics 2024-06-03 Maya M. Martirossyan , Matthew Spellings , Hillary Pan , Julia Dshemuchadse

The formation of bulk metallic glass requires the constituent elements to have a negative heat of mixing but has no restrictions on its magnitude. An understanding of this issue is lacking due to the absence of a valid method for describing…

Materials Science · Physics 2023-05-10 Song Ling Liu , Xin Yu Luo , Jing Shan Cao , Zhao Yuan Liu , Bei Bei Xu , Yong Hao Sun , Weihua Wang

The chemical flexibility of metal-organic frameworks (MOFs) offers an ideal platform to tune structure and composition for specific applications, from gas sensing to catalysis and from photoelectric conversion to energy storage. This…

Materials Science · Physics 2024-02-13 Joshua Edzards , Holger-Dietrich Saßnick , Julia Santana Andreo , Caterina Cocchi

We define the block neighborhood of a reversible CA, which is related both to its decomposition into a product of block permutations and to quantum computing. We give a purely combinatorial characterization of the block neighborhood, which…

Discrete Mathematics · Computer Science 2010-12-30 Pablo Arrighi , Vincent Fabrice Nesme

We investigate the locality of electronic interactions in aluminum as a function of smearing/electronic temperature in the context of $\mathcal{O}(N)$ Density Functional Theory calculations. Specifically, we determine the convergence in…

Materials Science · Physics 2017-05-24 Phanish Suryanarayana

A correlation is established between the macro-scale friction regimes of metals and a transition between two dominant atomistic mechanisms of deformation. Metals tend to exhibit bi-stable friction behavior -- low and converging or high and…

Materials Science · Physics 2018-05-23 Nicolas Argibay , Michael E. Chandross , Shengfeng Cheng , Joseph R. Michael

Machine learning has proven to be a valuable tool to approximate functions in high-dimensional spaces. Unfortunately, analysis of these models to extract the relevant physics is never as easy as applying machine learning to a large dataset…

Materials Science · Physics 2020-05-06 Conrad W. Rosenbrock , Eric R. Homer , Gábor Csányi , Gus L. W. Hart

The metal content of clusters of galaxies and its relation to their stellar content is revisited making use of a cluster sample for which all four basic parameters are homogeneously measured within consistent radii, namely core-excised…

Astrophysics of Galaxies · Physics 2015-06-22 A. Renzini , S. Andreon

'Big' high-dimensional data are commonly analyzed in low-dimensions, after performing a dimensionality-reduction step that inherently distorts the data structure. For the same purpose, clustering methods are also often used. These methods…

Machine Learning · Statistics 2019-02-20 Tom Lorimer , Karlis Kanders , Ruedi Stoop

Complex systems are usually represented as an intricate set of relations between their components forming a complex graph or network. The understanding of their functioning and emergent properties are strongly related to their structural…

Data Analysis, Statistics and Probability · Physics 2014-01-08 Sergio Gomez , Alberto Fernandez , Clara Granell , Alex Arenas

Zinc and cadmium clusters interacting with a Gupta potential have previously been identified as prototypical metallic systems that exhibiting disordered cluster structures. Here, putative global minima of the potential energy have been…

Condensed Matter · Physics 2007-05-23 Jonathan P. K. Doye

This study investigates the molecular-level self-assembly behavior of seven functionalized diamondoids, examining how diverse substituents influence structural organization, thermal stability, and aggregate morphology. Using a combination…

Mesoscale and Nanoscale Physics · Physics 2024-12-13 Sonam Phuntsho

Covalent molecules are characterized by directed bonds, which provide stability-of-form to the molecules relative atomic positions. In contrast, bulk metals are characterized by delocalized bonds, where a large number of resonance…

Mesoscale and Nanoscale Physics · Physics 2013-05-27 Harsh Deep Chopra , J. N. Armstrong , Susan Z. Hua

We study the composition dependent evolution of geometric and magnetic structures of MnO clusters within density functional theory. A systematic and extensive search through the potential energy surface is performed to identify the correct…

Materials Science · Physics 2018-10-16 Shreemoyee Ganguly , Mukul Kabir , Carmine Autieri , Biplab Sanyal