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Related papers: Understanding defects in amorphous silicon with mi…

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Individual spin defects in solids are promising building blocks for quantum technologies, but their deterministic creation, individual addressability, and operation near surfaces remain major challenges. Two-dimensional materials provide an…

Many soft matter systems exhibit ordered, polycontinuous network morphologies, such as the cubic (double) gyroid or diamond, as well as disordered network morphologies known generically as ``random sponges". While presumed to share similar…

It is difficult to quantify structure-property relationships and to identify structural features of complex materials. The characterization of amorphous materials is especially challenging because their lack of long-range order makes it…

Soft Condensed Matter · Physics 2019-09-11 Kirk Swanson , Shubhendu Trivedi , Joshua Lequieu , Kyle Swanson , Risi Kondor

Extended defects such as dislocation networks and general grain boundaries are ubiquitous in metals, and accurately modeling these extensive defects is crucial for understanding their deformation mechanisms. Existing machine learning…

Materials Science · Physics 2025-06-10 Fei Shuang , Kai Liu , Yucheng Ji , Wei Gao , Luca Laurenti , Poulumi Dey

Amorphous silicon contains tunneling two-level systems, which are the dominant energy loss mechanisms for amorphous solids at low temperatures. These two-level systems affect both mechanical and electromagnetic oscillators and are believed…

Materials Science · Physics 2021-03-10 M. Molina-Ruiz , Y. J. Rosen , H. C. Jacks , M. R. Abernathy , T. H. Metcalf , X. Liu , J. L Dubois , F. Hellman

We present a systematic methodology for the accurate calculation of defect structures in supercells which we illustrate with a study of the neutral vacancy in silicon. This is a prototypical defect which has been studied extensively using…

Materials Science · Physics 2009-11-10 M. I. J. Probert , M. C. Payne

Why are materials with specific characteristics more abundant than others? This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space.…

Materials Science · Physics 2023-07-28 Elena Gazzarrini , Rose K. Cersonsky , Marnik Bercx , Carl S. Adorf , Nicola Marzari

Population and distribution of defects is one of the primary parameters controlling materials functionality, are often non-ergodic and strongly dependent on synthesis history, and are rarely amenable to direct theoretical prediction. Here,…

Thin-shell structures, found in biological systems such as beetle carapaces and widely used in aerospace, civil, and mechanical engineering, achieve remarkable strength-to-mass ratio given their slenderness and curved geometries. However,…

Applied Physics · Physics 2025-07-01 Ilyes Krida , Jacob Tang , Daniel Floryan , Tian Chen

Four-dimensional scanning transmission electron microscopy (4D-STEM) of local atomic diffraction patterns is emerging as a powerful technique for probing intricate details of atomic structure and atomic electric fields. However, efficient…

Image and Video Processing · Electrical Eng. & Systems 2019-01-15 Xin Li , Ondrej E. Dyck , Mark P. Oxley , Andrew R. Lupini , Leland McInnes , John Healy , Stephen Jesse , Sergei V. Kalinin

Amorphous materials are solids that lack long-range atomic order but possess complex short- and medium-range order. Unlike crystalline materials that can be described by unit cells containing few up to hundreds of atoms, amorphous materials…

Machine Learning · Computer Science 2026-04-01 Yan Lin , Jonas A. Finkler , Tao Du , Jilin Hu , Morten M. Smedskjaer

We discuss the efficacy of evolutionary method for the purpose of structural analysis of amorphous solids. At present ab initio molecular dynamics (MD) based melt-quench technique is used and this deterministic approach has proven to be…

Materials Science · Physics 2016-08-03 Suhas Nahas , Anshu Gaur , Somnath Bhowmick

Si dangling bonds without H termination at the interface of quasi-free standing monolayer graphene (QFMLG) are known scattering centers that can severely affect carrier mobility. In this report, we study the atomic and electronic structure…

Point defects in silicon carbide (SiC), particularly the negatively-charged silicon vacancy ($\mathrm{V_{Si}^{-}}$) in 4H-SiC, are leading candidates for scalable quantum technologies due to their favorable spin-optical properties and…

Machine Learning (ML) techniques are revolutionizing the way to perform efficient materials modeling. Nevertheless, not all the ML approaches allow for the understanding of microscopic mechanisms at play in different phenomena. To address…

Materials Science · Physics 2022-06-22 Udaykumar Gajera , Loriano Storchi , Danila Amoroso , Francesco Delodovici , Silvia Picozzi

Our understanding of supercooled liquids and glasses has lagged significantly behind that of simple liquids and crystalline solids. This is in part due to the many possibly relevant degrees of freedom that are present due to the disorder…

Machine Learning · Statistics 2018-08-01 Samuel S. Schoenholz

The inapplicability of amino acid covariation methods to small protein families has limited their use for structural annotation of whole genomes. Recently, deep learning has shown promise in allowing accurate residue-residue contact…

Biomolecules · Quantitative Biology 2019-09-10 Joe G Greener , Shaun M Kandathil , David T Jones

Combinatorial mechanical metamaterials are made of anisotropic, flexible blocks, such that multiple metamaterials may be constructed using a single block type, and the system's response depends on the frustration (or its absence) due to the…

Soft Condensed Matter · Physics 2025-07-02 Chaviva Sirote-Katz , Yotam M. Y. Feldman , Guy Cohen , Tamás Kálmán , Yair Shokef

Structural defects control the kinetic, thermodynamic and mechanical properties of glasses. For instance, rare quantum tunneling two-level systems (TLS) govern the physics of glasses at very low temperature. Because of their extremely low…

Disordered Systems and Neural Networks · Physics 2023-07-19 Simone Ciarella , Dmytro Khomenko , Ludovic Berthier , Felix C. Mocanu , David R. Reichman , Camille Scalliet , Francesco Zamponi

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