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Related papers: Recent Developments in Computer Modeling of Amorph…

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Computer simulation plays a central role in modern day materials science. The utility of a given computational approach depends largely on the balance it provides between accuracy and computational cost. Molecular crystals are a class of…

Neuromorphic computing approaches become increasingly important as we address future needs for efficiently processing massive amounts of data. The unique attributes of quantum materials can help address these needs by enabling new…

Spontaneous structural relaxation is intrinsic to glassy materials due to their metastable nature. For phase-change materials (PCMs), the resultant temporal change in electrical resistance seriously hamper in-memory computing (IMC)…

The purpose of this manuscript is to review my recent activity on three main research topics. The first concerns the nature of low temperature amorphous solids and their relation with the spin glass transition in a magnetic field. This is…

Disordered Systems and Neural Networks · Physics 2024-05-13 Pierfrancesco Urbani

Ab initio electronic structure calculations of two-dimensional layered structures are typically performed using codes that were developed for three-dimensional structures, which are periodic in all three directions. The introduction of a…

Strongly Correlated Electrons · Physics 2016-06-22 Paolo E. Trevisanutto , Giovanni Vignale

Glass-like materials are nonequilibrium systems where the relaxation time may exceed reasonable time scales of observations. In the present paper a dynamic percolation model is introduced in order to explain the principal properties of…

Condensed Matter · Physics 2007-05-23 A. Vazquez , O. Sotolongo-Costa

We use a Monte Carlo bond-switching method to study systematically the thermodynamic properties of a "continuous random network" model, the canonical model for such amorphous systems as a-Si and a-SiO$_2$. Simulations show first-order…

Statistical Mechanics · Physics 2009-10-31 Yuhai Tu , J. Tersoff , G. Grinstein , David Vanderbilt

The last two decades have seen major developments in interpolatory methods for model reduction of large-scale linear dynamical systems. Advances of note include the ability to produce (locally) optimal reduced models at modest cost; refined…

Numerical Analysis · Mathematics 2014-09-18 Christopher Beattie , Serkan Gugercin

The interplay of electronic and nuclear degrees of freedom presents an outstanding problem in condensed matter physics and chemistry. Computational challenges arise especially for large systems, long time scales, in nonequilibrium, or in…

Strongly Correlated Electrons · Physics 2024-02-14 Arne Schobert , Jan Berges , Erik G. C. P. van Loon , Michael A. Sentef , Sergey Brener , Mariana Rossi , Tim O. Wehling

This work represents the first chapter of a project on the foundations of first-principle calculations of the electron transport in crystals at finite temperatures. We are interested in the range of temperatures, where most electronic…

Computational Physics · Physics 2018-04-04 Thomas D. Kühne , Emil Prodan

We propose here a method to generate random networked amorphous structure using only readily available short-range properties like bond lengths, bond angles and connectivity of the constituents. This method is a variant of Monte-Carlo (MC)…

Materials Science · Physics 2022-05-26 Shakti Singh , Sharat Chandra

Electrochemical metallization (ECM) memristors have potential applications in future neuromorphic computing hardware. The set, reset, and variable-resistance features of these devices originate in the formation and breakup of metal…

Mesoscale and Nanoscale Physics · Physics 2026-05-05 Justin Brutger , Xiao Shen

The kinetic process of mechanical amorphization plays a central role in tailoring material properties. Therefore, a quantitative understanding of how this process depends on loading parameters is critical for optimizing mechanical…

Materials Science · Physics 2025-09-09 Baoshuang Shang , Xinxin Li , Pengfei Guan , Weihua Wang

First principles calculations of magnetic and, to a lesser extent, electronic properties of the novel LaFeAsO-based superconductors show substantial apparent controversy, as opposed to most weakly or strongly correlated materials. Not only…

Materials Science · Physics 2009-11-13 I. I. Mazin , M. D. Johannes , L. Boeri , K. Koepernik , D. J. Singh

The deformation and flow of disordered solids, such as metallic glasses and concentrated emulsions, involves swift localized rearrangements of particles that induce a long-range deformation field. To describe these heterogeneous processes,…

Disordered Systems and Neural Networks · Physics 2019-01-02 Alexandre Nicolas , Ezequiel E. Ferrero , Kirsten Martens , Jean-Louis Barrat

Procedural material models have been gaining traction in many applications thanks to their flexibility, compactness, and easy editability. We explore the inverse rendering problem of procedural material parameter estimation from…

Graphics · Computer Science 2025-04-22 Yu Guo , Milos Hasan , Lingqi Yan , Shuang Zhao

We apply a new method "force enhanced atomic refinement" (FEAR) to create a computer model of amorphous silicon (a-Si), based upon the highly precise X-ray diffraction experiments of Laaziri et al. The logic underlying our calculation is to…

Materials Science · Physics 2016-12-28 Anup Pandey , Parthapratim Biswas , Bishal Bhattarai , D. A. Drabold

Crystalline materials, with symmetrical and periodic structures, exhibit a wide spectrum of properties and have been widely used in numerous applications across electronics, energy, and beyond. For crystalline materials discovery,…

Computational Engineering, Finance, and Science · Computer Science 2026-02-11 Zhenzhong Wang , Haowei Hua , Wanyu Lin , Ming Yang , Kay Chen Tan

Computational study of molecules and materials from first principles is a cornerstone of physics, chemistry, and materials science, but limited by the cost of accurate and precise simulations. In settings involving many simulations, machine…

Computational Physics · Physics 2022-03-17 Marcel F. Langer , Alex Goeßmann , Matthias Rupp

First-order methods for solving convex optimization problems have been at the forefront of mathematical optimization in the last 20 years. The rapid development of this important class of algorithms is motivated by the success stories…

Optimization and Control · Mathematics 2021-01-07 Pavel Dvurechensky , Mathias Staudigl , Shimrit Shtern
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