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This article deals with the multiscale modeling of stress transfer characteristics of nano-reinforced polymer composite reinforced with regularly staggered carbon fibers. The distinctive feature of construction of nano-reinforced composite…

Materials Science · Physics 2017-02-06 S. I. Kundalwal , S. A. Meguid

We investigate thermal rectification in nanoporous silicon using a semi-classical Monte Carlo (MC) simulation method. We consider geometrically asymmetric nanoporous structures, and investigate the combined effects of porosity, inter-pore…

Materials Science · Physics 2019-11-18 Dhritiman Chakraborty , Joshua Brooke , Nick C S Hulse , Neophytos Neophytou

While recent efforts have shown how local structure plays an essential role in the dynamic heterogeneity of homogeneous glass-forming materials, systems containing interfaces such as thin films or composite materials remain poorly…

Soft Condensed Matter · Physics 2022-04-27 Entao Yang , James F. Pressly , Bharath Natarajan , Robert Colby , Karen I. Winey , Robert A. Riggleman

Machine-learned interatomic potentials (MLIPs) based on message passing neural networks hold promise to enable large-scale atomistic simulations of complex materials with ab initio accuracy. A number of MLIPs trained on energies and forces…

Materials Science · Physics 2025-04-09 Mikkel Ohm Sauer , Peder Meisner Lyngby , Kristian Sommer Thygesen

A data-driven framework was used to predict the macroscopic mechanical behavior of dense packings of polydisperse granular materials. The Discrete Element Method, DEM, was used to generate 92,378 sphere packings that covered many different…

Disordered Systems and Neural Networks · Physics 2020-06-23 Ignacio G. Tejada , Pablo Antolin

Nanocrystalline metals, i.e. metals with grain sizes from 5 to 50 nm, display technologically interesting properties, such as dramatically increased hardness, increasing with decreasing grain size. Due to the small grain size, direct…

Materials Science · Physics 2009-10-31 J. Schiøtz , T. Vegge , K. W. Jacobsen

The permeability of a pore structure is typically described by stochastic representations of its geometrical attributes. Database-driven numerical solvers for large model domains can only accurately predict large-scale flow behaviour when…

Geophysics · Physics 2020-10-02 Hannah P. Menke , Julien Maes , Sebastian Geiger

We explore different ways to simplify the evaluation of the smooth overlap of atomic positions (SOAP) many-body atomic descriptor [Bart\'{o}k et al., Phys. Rev. B 87, 184115 (2013)]. Our aim is to improve the computational efficiency of…

Computational Physics · Physics 2019-09-16 Miguel A. Caro

Herein, we investigate the structural, electronic and mechanical properties of zigzag graphene nanoribbons upon the presence of stress applying Density Functional Theory within the GGA-PBE approximation. The uniaxial stress is applied along…

Materials Science · Physics 2015-05-13 Ricardo Faccio , Pablo A. Denis , Helena Pardo , Cecilia Goyenola , Alvaro W. Mombru

Uniform macroscopic samples of nanoporous metal with high deformability have so far been limited to precious metals such as Au, Pd and Pt. Here we propose nanoporous Copper-Nickel (npCN) as a nanoporous base metal that can be made with mm…

Materials Science · Physics 2018-06-25 Lukas Lührs , Jörg Weissmüller

Machine learning interatomic potentials (MLIPs) are routinely used atomic simulations, but generating databases of atomic configurations used in fitting these models is a laborious process, requiring significant computational and human…

Materials Science · Physics 2022-07-26 Connor Allen , Albert P. Bartók

While the mechanical behavior of noble nanoporous metals has been the subject of numerous studies, less is known about their recently developed refractory-based counterparts. Here we report on the mechanical properties, deformation…

Materials Science · Physics 2024-02-20 N. Vazquez von Bibow , E. N. Millán , C. J. Ruestes

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

Binary metal clusters are of high interest for applications in heterogeneous catalysis and have received much attention in recent years. To gain insights into their structure and composition at the atomic scale, computer simulations can…

Chemical Physics · Physics 2020-04-10 Jan Weinreich , Anton Römer , Martín Leandro Paleico , Jörg Behler

The prediction of atomistic fracture mechanisms in body-centred cubic (bcc) iron is essential for understanding its semi-brittle nature. Existing atomistic simulations of the crack-tip deformation mechanisms under mode-I loading based on…

Materials Science · Physics 2022-09-15 Lei Zhang , Gábor Csányi , Erik van der Giessen , Francesco Maresca

Macroscopic fibres of carbon nanotubes are hierarchical structures combining long building blocks preferentially oriented along the fibre axis and a large porosity arising from the imperfect packing of bundles. Synchrotron small-angle X-ray…

Gaseous nanobubbles (NBs), with their unique physicochemical properties and promising applications, have become an important research topic. Generation of monodispersed bulk NBs with specified gas content remains a challenge. We developed a…

Applied Physics · Physics 2020-06-24 Teng Ma , Yasuo Kimura , Hideaki Yamamoto , Xingyao Feng , Ayumi Hirano-Iwata , Michio Niwano

The structural evolution and dynamics of silver nanodrops Ag${}_{2896}$ (4.4 nm in diameter) during rapid cooling conditions has been studied by means of molecular dynamics simulations and electronic density of state calculations. The…

Materials Science · Physics 2009-01-22 I. Lobato , J. Rojas , C. V. Landauro , J. Torres

The discovery and optimization of high-energy materials (HEMs) are constrained by the prohibitive computational expense and prolonged development cycles inherent in conventional approaches. In this work, we develop a general neural network…

Materials Science · Physics 2025-03-05 Mingjie Wen , Jiahe Han , Wenjuan Li , Xiaoya Chang , Qingzhao Chu , Dongping Chen

The formation of planetesimals requires the growth of dust particles through collisions. Micron-sized particles must grow by many orders of magnitude in mass. In order to understand and model the processes during this growth, the mechanical…

Astrophysics · Physics 2009-11-13 D. Paszun , C. Dominik