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In order to construct a dielectric analog of spaser, we study theoretically and experimentally several configurations of cluster-based unit cells for an all-dielectric metasurface characterized by resonant conditions of the trapped mode…

We examine the favoured cluster structures for two new potentials, which both behave as monatomic model glass-formers in bulk. We find that the oscillations in the interatomic potential lead to global minima that are non-compact…

Condensed Matter · Physics 2007-05-23 Jonathan P. K. Doye , David J. Wales , Fredrik H. M. Zetterling , Mikhail Dzugutov

A key starting assumption in many classical interatomic potential models for materials is a site energy decomposition of the potential energy surface into contributions that only depend on a small neighbourhood. Under a natural stability…

Mathematical Physics · Physics 2020-09-10 Jack Thomas

Semi-empirical interatomic potentials have been developed for Al, alpha-Ti, and gamma-TiAl within the embedded atomic method (EAM) by fitting to a large database of experimental as well as ab-initio data. The ab-initio calculations were…

Materials Science · Physics 2009-11-10 Rajendra R. Zope , Y. Mishin

Machine learning interatomic potentials (MLIPs) with broad chemical flexibility are important for atomistic simulations of compositionally complex materials such as high-entropy alloys. Here, we study two state-of-the-art MLIP frameworks,…

Materials Science · Physics 2026-04-06 Fei Shuang , Penghua Ying , Kai Liu , Zixiong Wei , Fengxian Liu , Zheyong Fan , Minqiang Jiang , Poulumi Dey

Machine learning potentials (MLPs) are becoming powerful tools for performing accurate atomistic simulations and crystal structure optimizations. An approach to developing MLPs employs a systematic set of polynomial invariants including…

Computational Physics · Physics 2020-11-18 Atsuto Seko

It is shown how traditional development of theories of fluids based upon the concept of physical clustering can be adapted to an alternative local clustering definition. The alternative definition can preserve a detailed valence description…

Chemical Physics · Physics 2015-06-26 Lawrence R. Pratt , Randall A. LaViolette

Accurate representation of the molecular electrostatic potential, which is often expanded in distributed multipole moments, is crucial for an efficient evaluation of intermolecular interactions. Here we introduce a machine learning model…

Chemical Physics · Physics 2017-10-09 Tristan Bereau , Denis Andrienko , O. Anatole von Lilienfeld

A Magnetic Cluster Expansion (MCE) model for ternary face-centered cubic Fe-Ni-Cr alloys has been developed using DFT data spanning binary and ternary alloy configurations. Using this MCE model Hamiltonian, we perform Monte Carlo…

Materials Science · Physics 2016-11-24 M. Y. Lavrentiev , J. S. Wróbel , D. Nguyen-Manh , S. L. Dudarev , M. G. Ganchenkova

Coupled-cluster (CC) theory is often considered the gold standard of quantum chemistry, but its high computational cost limits routine access to accurate energies, forces and response properties. While the right-hand $T$-amplitudes…

In this paper I propose a new model for representing the formation energies of multicomponent crystalline alloys as a function of atom types. In the cases when displacements of atoms from their equilibrium positions are not large, the…

Computational Physics · Physics 2017-08-02 Alexander Shapeev

By combining the Self-Interaction Correction (SIC) with pseudopotential perturbation theory, the role of self-interaction errors inherent to the Local Density Approximation (LDA) to Density Functional Theory is estimated in the…

mtrl-th · Physics 2009-10-28 Jorge M. Pacheco , Walter Ekardt , Wolf-Dieter Schoene

Cluster expansion (CE) is effective in modeling the stability of metallic alloys, but sometimes cluster expansions fail. Failures are often attributed to atomic relaxation in the DFT-calculated data, but there is no metric for quantifying…

Materials Science · Physics 2017-07-19 Andrew H. Nguyen , Conrad W. Rosenbrock , C. Shane Reese , Gus L. W. Hart

In vehicle-to-infrastructure (V2I) networks, a cluster of multi-antenna access points (APs) can collaboratively conduct transmitter beamforming to provide data services (e.g., eMBB or URLLC). The collaboration between APs effectively forms…

Signal Processing · Electrical Eng. & Systems 2022-01-21 Jinfei Wang , Yi Ma , Na Yi , Rahim Tafazolli , Fan Wang

We introduce a numerical linked cluster expansion for square-lattice models whose building block is an L-shape cluster. For the spin-1/2 models studied in this work, we find that this expansion exhibits a similar or better convergence of…

Statistical Mechanics · Physics 2025-07-10 Mahmoud Abdelshafy , Marcos Rigol

The complete $O(\alpha^2)$ correction to the long range interaction between neutral closed shell atoms is obtained, the relation to the asymptotic expansion of the known short range interaction at the atomic scale is presented and a general…

Atomic Physics · Physics 2009-11-11 Krzysztof Pachucki

The past decade has witnessed a spectacular development of machine-learned interatomic potentials (MLIPs), to the extent that they are already the approach of choice for most atomistic simulation studies not requiring an explicit treatment…

Materials Science · Physics 2025-11-24 Iñigo Robredo-Magro , Binayak Mukherjee , Hugo Aramberri , Jorge Íñiguez-González

We extend Mode-Coupling Theory (MCT) to inhomogeneous situations, relevant for supercooled liquid in pores, close to a surface, or in an external field. We compute the response of the dynamical structure factor to a static inhomogeneous…

Statistical Mechanics · Physics 2009-11-11 Giulio Biroli , Jean-Philippe Bouchaud , Kunimasa Miyazaki , David R. Reichman

The development of multireference coupled cluster (MRCC) techniques has remained an open area of study in electronic structure theory for decades due to the inherent complexity of expressing a multi-configurational wavefunction in the…

Chemical Physics · Physics 2023-05-24 Maria-Andreea Filip , Alex J. W. Thom

A cardinal obstacle to understanding and predicting quantitatively the properties of solids and large molecules is that, for these systems, it is very challenging to describe beyond the mean-field level the quantum-mechanical interactions…

Strongly Correlated Electrons · Physics 2020-09-14 Nicola Lanatà
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