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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…

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,…

Structurally disordered materials continue to pose fundamental questions, including that of how different disordered phases ("polyamorphs") can coexist and transform from one to another. As a widely studied case, amorphous silicon (a-Si)…

The structure of amorphous silicon (a-Si) has been studied for decades. The two main theories are based on a continuous random network and on a `paracrystalline' model, respectively -- the latter being defined as showing localized…

Materials Science · Physics 2024-07-24 Louise A. M. Rosset , David A. Drabold , Volker L. Deringer

The structural and electronic properties of amorphous silicon ($a$-Si) are investigated by first-principles calculations based on the density-functional theory (DFT), focusing on the intrinsic structural defects. By simulated melting and…

Materials Science · Physics 2017-10-11 Yoritaka Furukawa , Yu-ichiro Matsushita

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

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

The nature of the atomic defects on the hydrogen passivated Si (100) surface is analyzed using deep learning and scanning tunneling microscopy (STM). A robust deep learning framework capable of identifying atomic species, defects, in the…

Materials Science · Physics 2020-02-19 Maxim Ziatdinov , Udi Fuchs , James H. G. Owen , John N. Randall , Sergei V. Kalinin

Disordered elemental semiconductors, most notably a-C and a-Si, are ubiquitous in a myriad of different applications. These exploit their unique mechanical and electronic properties. In the past couple of decades, density functional theory…

Materials Science · Physics 2023-03-14 Miguel A. Caro

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

Although fabrication capabilities of Silicon Dangling Bonds have rapidly advanced from manual labor-driven laboratory work to automated manufacturing in just recent years, sub-nanometer substrate defects still pose a hindrance to production…

Two-dimensionally extended amorphous carbon ("amorphous graphene") is a prototype system for disorder in 2D, showing a rich and complex configurational space that is yet to be fully understood. Here we explore the nature of amorphous…

Chemical Physics · Physics 2023-06-06 Zakariya El-Machachi , Mark Wilson , Volker L. Deringer

Metal-organic frameworks (MOFs) are highly interesting and tunable materials. By incorporating spatial defects into their atomic structure, MOFs can be finetuned to exhibit precise chemical functionalities, extending their applicability in…

Materials Science · Physics 2025-04-08 Pieter Dobbelaere , Sander Vandenhaute , Veronique Van Speybroeck

Amorphous silica ($a-SiO_2$) is a widely used inorganic material. Interestingly, the relationship between the local atomic structures of $a-SiO_2$ and their effects on ductility and fracture is seldom explored. Here, we combine large-scale…

Mesoscale and Nanoscale Physics · Physics 2023-04-17 Jiahao Liu , Jingjie Yeo

Localized basis ab initio molecular dynamics simulation within the density functional framework has been used to generate realistic configurations of amorphous silicon carbide (a-SiC). Our approach consists of constructing a set of smart…

Disordered Systems and Neural Networks · Physics 2015-05-13 Raymond Atta-Fynn , Parthapratim Biswas

The dynamics of amorphous silicon at low temperatures can be characterized by a sequence of discrete activated events, through which the topological network is locally reorganized. Using the activation-relaxation technique, we create more…

Condensed Matter · Physics 2009-10-31 G. T. Barkema , Normand Mousseau

Structural defects within amorphous packings of symmetric particles can be characterized using a machine learning approach that incorporates structure functions of radial distances and angular arrangement. This yields a scalar field,…

Soft Condensed Matter · Physics 2019-03-06 Matt Harrington , Andrea J. Liu , Douglas J. Durian

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

We have used tight-binding molecular-dynamics simulations to investigate the role of point defects (vacancies and interstitials) on structural relaxation in amorphous silicon. Our calculations give unambiguous evidence that point defects…

Materials Science · Physics 2007-05-23 Cristiano L. Dias , Laurent J. Lewis , S. Roorda

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
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