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We develop a combined theoretical and experimental method for estimating the amount of heating that occurs in metallic nanoparticles that are being imaged in an electron microscope. We model the thermal transport between the nanoparticle…

Mesoscale and Nanoscale Physics · Physics 2024-03-25 Cuauhtemoc Nuñez Valencia , William Bang Lomholdt , Matthew Helmi Leth Larsen , Thomas W. Hansen , Jakob Schiøtz

Developing fast and accurate methods to discover intermetallic compounds is relevant for alloy design. While density-functional-theory (DFT)-based methods have accelerated design of binary and ternary alloys by providing rapid access to the…

Materials Science · Physics 2020-09-09 Zhaohan Zhang , Mu Li , Katharine Flores , Rohan Mishra

A critical limitation to the wide-scale use of classical molecular dynamics for alloy design is the limited availability of suitable interatomic potentials. Here, we introduce the Rapid Alloy Method for Producing Accurate General Empirical…

The properties of MgO/Ag(001) ultrathin films with substitutional Mg atoms in the interface metal layer have been investigated by means of Auger electron diffraction experiments, ultraviolet photoemission spectroscopy, and density…

Materials Science · Physics 2014-11-26 T. Jaouen , P. Aebi , S. Tricot , G. Delhaye , B. Lépine , D. Sébilleau , G. Jézéquel , P. Schieffer

The advent of neural-network-based deep learning techniques has led to the emergence of increasingly sophisticated numerical interatomic potentials, including graph neural networks and large language-motivated foundation models.…

Chemical Physics · Physics 2026-03-09 Susan R. Atlas

Unlike covalent two-dimensional (2D) materials like graphene, 2D metals have non-layered structures due to their non-directional, metallic bonding. While experiments on 2D metals are still scarce and challenging, density-functional theory…

Materials Science · Physics 2023-01-06 Kameyab Raza Abidi , Pekka Koskinen

Supported nanoparticle catalysts are widely used in the chemical industry. Computational modeling of supported nanoparticles based on density functional theory (DFT) often involves structural searches of stable local minimum energy…

Materials Science · Physics 2026-03-26 Jiayan Xu , Abhirup Patra , Amar Deep Pathak , Sharan Shetty , Detlef Hohl , Roberto Car

The development of CdMgO ternary alloy with a single cubic phase is challenging but meaningful work for technological advancement. In this work, we have grown a series of Cd1-xMgxO ternary random alloys with various Mg concentrations (x =…

Materials Science · Physics 2023-05-08 A. Adhikari , A. Wierzbicka , A. Lysak , P. Sybilski , B. S. Witkowski , E. Przezdziecka

Over many years, computational simulations based on Density Functional Theory (DFT) have been used extensively to study many different materials at the atomic scale. However, its application is restricted by system size, leaving a number of…

Mesoscale and Nanoscale Physics · Physics 2018-12-05 Carlos Romero-Muñiz , Ayako Nakata , Pablo Pou , David R. Bowler , Tsuyoshi Miyazaki , Rubén Pérez

We propose an approach to materials prediction that uses a machine-learning interatomic potential to approximate quantum-mechanical energies and an active learning algorithm for the automatic selection of an optimal training dataset. Our…

Materials Science · Physics 2018-06-28 Konstantin Gubaev , Evgeny V. Podryabinkin , Gus L. W. Hart , Alexander V. Shapeev

The theorems of density functional theory (DFT) and reduced density matrix functional theory (RDMFT) establish a bijective map between the external potential of a many-body system and its electron density or one-particle reduced density…

Chemical Physics · Physics 2023-02-22 Xuecheng Shao , Lukas Paetow , Mark E. Tuckerman , Michele Pavanello

Understanding how structural flexibility affects the properties of metal-organic frameworks (MOFs) is crucial for the design of better MOFs for targeted applications. Flexible MOFs can be studied with molecular dynamics simulations, whose…

Materials Science · Physics 2024-05-13 Abhishek Sharma , Stefano Sanvito

Metal-organic frameworks (MOFs) are nanoporous compounds composed of metal ions and organic linkers. MOFs play an important role in industrial applications such as gas separation, gas purification, and electrolytic catalysis. Important MOF…

Machine Learning · Computer Science 2020-11-02 Shehtab Zaman , Christopher Owen , Kenneth Chiu , Michael Lawler

A simplified density functional theory (DFT) method for charged adsorbates on an ultrathin, insulating film supported by a metal substrate is developed and presented. This new method is based on a previous DFT development that uses a…

Materials Science · Physics 2017-03-27 Ivan Scivetti , Mats Persson

Atomistic simulations of the experimental W L$_3$-edge extended X-ray absorption fine structure (EXAFS) of bcc tungsten at T = 300 K were performed using classical molecular dynamics (MD) and reverse Monte Carlo (RMC) methods. The MD-EXAFS…

Materials Science · Physics 2018-02-27 Inga Jonane , Andris Anspoks , Alexei Kuzmin

In this work, we developed a compositionally transferable machine learning interatomic potential using atomic cluster expansion potential and PBE-D3 method for (NaCl)1-x(MgCl2)x molten salt and we showed that it is possible to fit a robust…

Materials Science · Physics 2024-09-27 Siamak Attarian , Chen Shen , Dane Morgan , Izabela Szlufarska

The microstructure of the Ti-Al binary system is an area of great interest as it affects material properties and plasticity. Phase transformations induce microstructural changes; therefore, accurately modeling the phase transformations of…

Materials Science · Physics 2024-11-13 Micah Nichols , Christopher D. Barrett , Doyl E. Dickel , Mashroor S. Nitol , Saryu J. Fensin

Choice of appropriate force field is one of the main concerns of any atomistic simulation that needs to be seriously considered in order to yield reliable results. Since, investigations on mechanical behavior of materials at micro/nanoscale…

Computational Physics · Physics 2016-07-12 Seyed Moein Rassoulinejad-Mousavi , Yijin Mao , Yuwen Zhang

Accurate prediction of metal-oxide adhesion in high-entropy alloys (HEAs) is challenging because interfacial segregation, atomic environments, and macroscopic thermodynamic quantities are strongly correlated. Relying solely on…

Materials Science · Physics 2026-03-06 Dennis Boakye , Chuang Deng

We present a systematical method for obtaining analytical long-range embedded-atom potentials based on the lattice-inversion method. The potentials converge faster (exponentially) than Sutton and Chen's power-law potentials (Philos. Mag.…

Materials Science · Physics 2008-02-03 Qian Xie , Wen-Qing Zhang , Nan-xian Chen
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