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We introduce a Gaussian approximation potential (GAP) for atomistic simulations of liquid and amorphous elemental carbon. Based on a machine-learning representation of the density-functional theory (DFT) potential-energy surface, such…

Materials Science · Physics 2017-03-08 Volker L. Deringer , Gábor Csányi

Amorphous solids, i.e., systems which feature well-defined short-range properties but lack long-range order, constitute an important research topic in condensed matter. While their microscopic structure is known to differ from their…

Quantum Gases · Physics 2024-08-23 Sergi Julià-Farré , Joseph Vovrosh , Alexandre Dauphin

First-principles molecular dynamics is employed to describe the atomic structure of amorphous SiN, a non-stoichiometric compound belonging to the Si$_x$N$_{y}$ family. To produce the amorphous state via the cooling of the liquid, both the…

Materials Science · Physics 2022-05-19 Achille Lambrecht , Carlo Massobrio , Mauro Boero , Guido Ori , Evelyne Martin

Amorphous silicon nitride (a-SiN) is a material which has found wide application due to its excellent mechanical and electrical properties. Despite the significant effort devoted in understanding how the microscopic structure influences the…

Since the pioneering efforts of Duwez and coworkers in 1965, when a solid amorphous phase of Pd-Si ($a$-PdSi) was obtained in the vicinity of the eutectic concentration, much work has been done. However, some points related to the atomic…

Multiple trapping and release (MTR) is a typical transport mechanism of electron carriers in amorphous and other disordered semiconductors where localized states are significant. Quantitative description of MTR, however, has been based on…

Disordered Systems and Neural Networks · Physics 2025-02-21 Yuezhou Luo , Andrew John Flewitt

Amorphous carbon (a-C) materials have diverse interesting and useful properties, but the understanding of their atomic-scale structures is still incomplete. Here, we report on extensive atomistic simulations of the deposition and growth of…

Materials Science · Physics 2020-11-05 Miguel A. Caro , Gábor Csányi , Tomi Laurila , Volker L. Deringer

The link between the energy surface of bulk systems and their dynamical properties is generally difficult to establish. Using the activation-relaxation technique (ART nouveau), we follow the change in the barrier distribution of a model of…

Disordered Systems and Neural Networks · Physics 2015-05-18 Houssem Kallel , Normand Mousseau , François Schiettekatte

While the dynamics of many complex systems is dominated by activated events, there are very few simulation methods that take advantage of this fact. Most of these procedures are restricted to relatively simple systems or, as with the…

Materials Science · Physics 2009-11-11 Henk Vocks , M. V. Chubynsky , G. T. Barkema , Normand Mousseau

Machine learning interatomic potentials (MLIPs) have substantially advanced atomistic simulations in materials science and chemistry by balancing accuracy and computational efficiency. While leading MLIPs rely on representing atomic…

Materials Science · Physics 2025-05-05 Mingjian Wen , Wei-Fan Huang , Jin Dai , Santosh Adhikari

First-principles based modeling on phonon dynamics and transport using density functional theory and Boltzmann transport equation has proven powerful in predicting thermal conductivity of crystalline materials, but it remains unfeasible for…

Materials Science · Physics 2019-07-23 Xin Qian , Shenyou Peng , Xiaobo Li , Yujie Wei , Ronggui Yang

We develop an empirical potential for silicon which represents a considerable improvement over existing models in describing local bonding for bulk defects and disordered phases. The model consists of two- and three-body interactions with…

Materials Science · Physics 2016-08-31 Joao F. Justo , Martin Z. Bazant , Efthimios Kaxiras , V. V. Bulatov , Sidney Yip

Amorphous and amorphous porous palladium are key materials for catalysis, hydrogen storage, and functional applications, but their complex structures present computational challenges. This study employs a deep neural network trained on…

Materials Science · Physics 2025-02-11 Isaías Rodríguez

Combining the efficiency of semi-empirical potentials with the accuracy of quantum mechanical methods, machine-learning interatomic potentials (MLIPs) have significantly advanced atomistic modeling in computational materials science and…

Materials Science · Physics 2025-05-20 Jiantao Wang , Peitao Liu , Heyu Zhu , Mingfeng Liu , Hui Ma , Yun Chen , Yan Sun , Xing-Qiu Chen

The 7\times7 reconstruction of the Si(111) surface represents arguably the most fascinating surface reconstruction so far observed in nature. Yet, the atomistic mechanism underpinning its formation remains unclear after it was discovered…

Materials Science · Physics 2021-05-05 Lin Hu , Bing Huang , Feng Liu

A recently proposed class of machine-learning interatomic potentials --- Moment tensor potentials (MTPs) --- is investigated in this work. MTPs are able to actively select configurations and parametrize the potential on-the-fly. It is shown…

Computational Physics · Physics 2018-12-11 I. I. Novoselov , A. V. Yanilkin , A. V. Shapeev , E. V. Podryabinkin

We present an accurate machine learning (ML) model for atomistic simulations of carbon, constructed using the Gaussian approximation potential (GAP) methodology. The potential, named GAP-20, describes the properties of the bulk crystalline…

Computational Physics · Physics 2020-08-26 Patrick Rowe , Volker L Deringer , Piero Gasparotto , Gábor Csányi , Angelos Michaelides

Amorphous silicon films prepared by electron beam evaporation have systematically and substantially greater atomic density for higher thickness, higher growth temperature, and slower deposition rate, reaching the density of crystalline Si…

Materials Science · Physics 2022-04-27 H. C. Jacks , M. Molina-Ruiz , M. H. Weber , J. J. Maldonis , P. M. Voyles , T. H. Metcalf , X. Liu , F. Hellman

We use empirical molecular dynamics technique to study the low-energy vibrations in a large 4096 atom model for pure amorphous silicon and a set of models with voids of different size based on it. Numerical vibrational eigenvalues and…

Disordered Systems and Neural Networks · Physics 2009-10-31 Serge M. Nakhmanson , D. A. Drabold

Locally, the atomic structure in well annealed amorphous silicon appears similar to that of crystalline silicon. We address here the question whether a point defect, specifically a vacancy, in amorphous silicon also resembles that in the…

Materials Science · Physics 2020-02-26 Andreas Pedersen , Laurent Pizzagalli , Hannes Jonsson