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Amorphous silicon (a-Si) is a widely studied non-crystalline material, and yet the subtle details of its atomistic structure are still unclear. Here, we show that accurate structural models of a-Si can be obtained by harnessing the power of…

This paper presents a large-scale $ab$ $initio$ simulation study of amorphous silicon hydride ($a$-Si$_{\text{1-x}}$H$_{\text{x}}$) with an emphasis on the structure and properties of the material across a range of hydrogen concentration by…

Materials Science · Physics 2023-09-19 Raymond Atta-Fynn , Somilkumar J. Rathi , Harsh Arya , Parthapratim Biswas

Amorphous silicon (a-Si) models are analyzed for structural, electronic and vibrational characteristics. Several models of various sizes have been computationally fabricated for this analysis. It is shown that a recently developed…

Disordered Systems and Neural Networks · Physics 2018-11-29 Dale Igram , Bishal Bhattarai , Parthapratim Biswas , D. A. Drabold

Amorphous materials are coming within reach of realistic computer simulations, but new approaches are needed to fully understand their intricate atomic structures. Here, we show how machine-learning (ML)-based techniques can give new,…

In this work We report on the extensive characterization of amorphous silicon carbide (a-SiC) coatings prepared by physical deposition methods. We compare the results obtained on two different sputtering systems (a standard RF magnetron…

A novel approach to predict the atomic densities of amorphous materials is explored on the basis of Car-Parrinello molecular dynamics (CPMD) in density functional theory. Despite that determination of the atomic density of matter is crucial…

Disordered Systems and Neural Networks · Physics 2018-01-17 Yoritaka Furukawa , Yu-ichiro Matsushita

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

We present an information-based total-energy optimization method to produce nearly defect-free structural models of amorphous silicon. Using geometrical, structural and topological information from disordered tetrahedral networks, we have…

Disordered Systems and Neural Networks · Physics 2019-01-28 Dil K. Limbu , Raymond Atta-Fynn , Parthapratim Biswas

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…

We have performed an approximate ab initio calculation of vibrational properties of hydrogenated amorphous silicon (a-Si:H) using a molecular dynamics method. A 216 atom model for pure amorphous silicon (a-Si) has been employed as a…

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

We generate representative structural models of amorphous carbon (a-C) from constant-volume quenching from the liquid with subsequent relaxation of internal stresses in molecular dynamics simulations using empirical and machine-learning…

Materials Science · Physics 2020-01-07 Richard Jana , Daniele Savio , Volker L. Deringer , Lars Pastewka

It is widely accepted in the materials modeling community that defect-free realistic networks of amorphous silicon cannot be prepared by quenching from a molten state of silicon using classical or ab initio molecular-dynamics (MD)…

Disordered Systems and Neural Networks · Physics 2018-06-13 Raymond Atta-Fynn , Parthapratim Biswas

Using first principles molecular dynamics simulations, we have determined the threshold displacement energies and the associated created defects in cubic silicon carbide. Contrary to previous studies using classical molecular dynamics, we…

Materials Science · Physics 2007-09-12 Guillaume Lucas , Laurent Pizzagalli

We report a new approach to simulate amorphous networks of covalently bonded materials that leads to excellent radial distribution functions and realistic atomic arrangements. We apply it to generate the first ab initio structures of…

Materials Science · Physics 2007-05-23 Fernando Alvarez , Ariel A. Valladares

We propose a novel approach to model amorphous materials using a first principles density functional method while simultaneously enforcing agreement with selected experimental data. We illustrate our method with applications to amorphous…

Materials Science · Physics 2009-11-10 Parthapratim Biswas , De Nyago Tafen , Raymond Atta-Fynn , D. A. Drabold

The atomistic modeling of amorphous materials requires structure sizes and sampling statistics that are challenging to achieve with first-principles methods. Here, we propose a methodology to speed up the sampling of amorphous and…

Disordered Systems and Neural Networks · Physics 2018-03-29 Nongnuch Artrith , Alexander Urban , Gerbrand Ceder

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

We present a first-principles study of the structural, electronic, and optical properties of hydrogenated amorphous silicon (a-Si:H). To this end, atomic configurations of a-Si:H with 72 and 576 atoms respectively are generated using…

Materials Science · Physics 2017-03-31 Philippe Czaja , Urs Aeberhard , Massimo Celino , Simone Giusepponi , Michele Gusso

The structure of amorphous silicon is widely thought of as a fourfold-connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such…

Ab initio simulations are capable of providing detailed information of material behavior at the nanoscale. Simulating experimentally relevant situations is, however, often computationally intense. Using hybrid approaches between ab initio…

Computational Physics · Physics 2019-03-26 Michael Sluydts , Michiel Larmuseau , Johan Lauwaert , Stefaan Cottenier
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