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The putative ground-state structures of 13-atom Cu and Ag clusters have been studied using ${\it ab \: initio}$ molecular-dynamics (AIMD) simulations based on the density-functional theory (DFT). An ensemble of low-energy configurations,…

Disordered Systems and Neural Networks · Physics 2019-10-02 Dil K. Limbu , Michael U. Madueke , Raymond Atta-Fynn , David A. Drabold , Parthapratim Biswas

Identifying a suitable set of descriptors for modeling physical systems often utilizes either deep physical insights or statistical methods such as compressed sensing. In statistical learning, a class of methods known as structured sparsity…

Materials Science · Physics 2019-10-30 Zhidong Leong , Teck Leong Tan

We study the thermodynamics of cubic Ti1-xAlxN using a unified cluster expansion approach for the alloy problem. The purely configurational part of the alloy Hamiltonian is expanded in terms of concentration and volume dependent effective…

Statistical Mechanics · Physics 2012-11-22 B. Alling , A. V. Ruban , A. Karimi , L. Hultman , I. A. Abrikosov

We present a large deviation analysis of a recently proposed probabilistic approach to the study of the ground-state properties of lattice quantum systems. The ground-state energy, as well as the correlation functions in the ground state,…

Other Condensed Matter · Physics 2011-02-16 Massimo Ostilli , Carlo Presilla

The coupled cluster method has been applied to the eigenvalue problem lattice Hamiltonian QCD (without quarks) for SU(2) gauge fields in two space dimensions. Using a recently presented new formulation and the truncation prescription of Guo…

High Energy Physics - Lattice · Physics 2007-05-23 D. Schuette , A. Wichmann , C. Weichmann

We introduce machine-learned potentials for Ag-Pd to describe the energy of alloy configurations over a wide range of compositions. We compare two different approaches. Moment tensor potentials (MTP) are polynomial-like functions of…

The cluster expansion method is applied to electronic excitations and a set of effective cluster density of states (ECDOS) are defined, analogous to effective cluster interactions (ECI). The ECDOS are used to generate alloy thermodynamic…

Materials Science · Physics 2012-03-06 H. Y. Geng , M. H. F. Sluiter , N. X. Chen

Kinetic Monte Carlo models parameterized by first principles calculations are widely used to simulate atomic diffusion. However, accurately predicting the activation energies for diffusion in substitutional alloys remains challenging due to…

Chemical Physics · Physics 2021-02-03 Chenyang Li , Thomas Nilson , Liang Cao , Tim Mueller

The genetic cluster-exact approximation algorithm is an efficient method to calculate ground states of EA spin glasses. The method can be used to study ground-state landscapes by calculating many independent ground states for each…

Disordered Systems and Neural Networks · Physics 2007-05-23 Alexander K. Hartmann

We develop an approach to apply Wang-Landau algorithm to multicomponent alloys in semi-grand-canonical ensemble. Although the Wang-Landau algorithm has great advantages over conventional sampling methods, there are few applications to…

Materials Science · Physics 2017-10-18 Kazuhito Takeuchi , Ryohei Tanaka , Koretaka Yuge

Predicting and characterizing the crystal structure of materials is a key problem in materials research and development. We report the results of ab initio LDA/GGA computations for the following systems: AgAu, AgCd, AgMg, AgMo*, AgNa,…

Materials Science · Physics 2009-09-29 Stefano Curtarolo , Dane Morgan , Gerbrand Ceder

This article deals with the general implementation of 4-component spinor relativistic extended coupled cluster (ECC) method to calculate first order property of atoms and molecules in their open-shell ground state configuration. The…

Chemical Physics · Physics 2015-02-25 Sudip Sasmal , Himadri Pathak , Malaya K. Nayak , Nayana Vaval , Sourav Pal

A central problem in many-body quantum physics is the determination of the ground state of a thermodynamically large physical system. We construct a cluster expansion for ground states of local Hamiltonians, which naturally incorporates…

Statistical Mechanics · Physics 2016-07-29 Alvise Bastianello , Spyros Sotiriadis

Long-standing challenges in cluster expansion (CE) construction include choosing how to truncate the expansion and which crystal structures to use for training. Compressive sensing (CS), which is emerging as a powerful tool for model…

Materials Science · Physics 2013-10-30 Lance J Nelson , Vidvuds Ozolins , Shane Reese , Fei Zhou , Gus L. W. Hart

The development of new engineering alloy chemistries is a time consuming and iterative process. A necessary step is characterization of the nano/microstructure to provide a link between the processing and properties of each alloy chemistry…

Materials Science · Physics 2015-08-28 F. De Geuser , M. J. Styles , A. Deschamps , C. R. Hutchinson

We propose machine learning (ML) models to predict the electron density -- the fundamental unknown of a material's ground state -- across the composition space of concentrated alloys. From this, other physical properties can be inferred,…

The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make…

Materials Science · Physics 2015-05-18 Ohad Levy , Gus Hart , Stefano Curtarolo

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

High-entropy alloys have attracted attention for their exceptional mechanical properties and thermal stability. However, the combinatorial explosion in the number of possible elemental compositions renders traditional trial-and-error…

Materials Science · Physics 2025-04-30 Ryo Murakami , Seiji Miura , Akihiro Endo , Satoshi Minamoto

Density functional theory (DFT)-based simulations of materials have first-principles accuracy, but are very computationally expensive. For simulating various properties of multi-component alloys, the cluster expansion (CE) technique has…

Materials Science · Physics 2026-04-01 Jacob Jeffries , Bochuan Sun , Enrique Martinez