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相关论文: Coarse-grained simulations of flow-induced nucleat…

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The nucleation process of polyethylene under quiescent and shear flow conditions are comparatively studied with all_atom molecular dynamical simulations. At both conditions, nucleation are demonstrated to be two_step processes, which,…

软凝聚态物质 · 物理学 2021-12-08 Xiaoliang Tang , Junsheng Yang , Fucheng Tian , Tingyu Xu , Chun Xie , Liangbin Li

The non-linear response of entangled polymers to shear flow is complicated. Its current understanding is framed mainly as a rheological description in terms of the complex viscosity. However, the full picture requires an assessment of the…

计算物理 · 物理学 2018-08-21 Airidas Korolkovas , Philipp Gutfreund , Max Wolff

As a model for a suspension of hard-sphere like colloidal particles where small nonadsorbing dissolved polymers create a depletion attraction, we introduce an effective colloid-colloid potential closely related to the Asakura-Oosawa model…

软凝聚态物质 · 物理学 2015-10-28 Antonia Statt , Peter Virnau , Kurt Binder

The investigation of freezing transitions of single polymers is computationally demanding, since surface effects dominate the nucleation process. In recent studies we have systematically shown that the freezing properties of flexible,…

软凝聚态物质 · 物理学 2012-07-18 Stefan Schnabel , Michael Bachmann , Wolfhard Janke

We investigate the influence of a shear flow on the process of nucleation. Mesoscopic nonequilibrium thermodynamics is used to derive the Fokker-Planck equation governing the evolution of the cluster size distribution in a metastable phase…

统计力学 · 物理学 2009-11-10 D. Reguera , J. M. Rubi

We present a novel thermodynamically guided, low-noise, time-scale bridging, and pertinently efficient strategy for the dynamic simulation of microscopic models for complex fluids. The systematic coarse-graining method is exemplified for…

软凝聚态物质 · 物理学 2010-11-12 Patrick Ilg , Hans Christian Öttinger , Martin Kröger

Classical nucleation theory offers a good framework for understanding the common features of new phase formation processes in metastable homogeneous media at rest. However, nucleation processes in liquids are ubiquitously affected by…

软凝聚态物质 · 物理学 2016-04-18 F. Mura , A. Zaccone

We have developed a new multiscale simulation technique to investigate history-dependent flow behavior of entangled polymer melt, using a smoothed particle hydrodynamics simulation with microscopic simulators that account for the dynamics…

软凝聚态物质 · 物理学 2011-11-01 Takahiro Murashima , Takashi Taniguchi

The crystallisation of entangled polymers from their melt is investigated using computer simulation with a coarse-grained model. Using hybrid Monte Carlo simulations enables us to probe the behaviour of long polymer chains. We identify…

软凝聚态物质 · 物理学 2020-06-12 Xiaoliang Tang , Fucheng Tian , Tingyu Xu , Liangbin Li , Aleks Reinhardt

Continuum Monte-Carlo simulations at constant pressure are performed on short chain molecules at surfaces. The rodlike chains, consisting of seven effective monomers, are attached at one end to a flat twodimensional substrate. It is found…

凝聚态物理 · 物理学 2007-05-23 R. Hilfer , F. M. Haas

We propose an efficient Monte Carlo algorithm for the off-lattice simulation of dense hard sphere polymer melts using cluster moves, called event chains, which allow for a rejection-free treatment of the excluded volume. Event chains also…

软凝聚态物质 · 物理学 2015-09-24 Tobias Alexander Kampmann , Horst-Holger Boltz , Jan Kierfeld

Due to the complex characteristics of bottle-brush polymers, it became a challenge to develop an efficient algorithm for studying such macromolecules under various solvent conditions or some constraints in the space by using computer…

软凝聚态物质 · 物理学 2011-07-08 Hsiao-Ping Hsu

The past few years have seen many advances in our understanding of the dynamics of polymeric fluids. These include improvements on the successful reptation theory; an emerging molecular theory of semiflexible chain dynamics; and an…

软凝聚态物质 · 物理学 2007-05-23 Peter D. Olmsted

The crystallization of a metastable melt is one of the most important non equilibrium phenomena in condensed matter physics, and hard sphere colloidal model systems have been used for several decades to investigate this process by…

软凝聚态物质 · 物理学 2015-05-20 Tanja Schilling , Sven Dorosz , Hans Joachim Schoepe , George Opletal

Based upon kinetic Monte Carlo simulations of crystallization in a simple polymer model we present a new picture of the mechanism by which the thickness of lamellar polymer crystals is constrained to a value close to the minimum…

凝聚态物理 · 物理学 2007-05-23 Jonathan Doye , Daan Frenkel

Recent advances in machine learning have led to the development of new methods for enhancing Monte Carlo methods such as Markov chain Monte Carlo (MCMC) and importance sampling (IS). One such method is normalizing flows, which use a neural…

统计计算 · 统计学 2024-01-12 Charly Andral

We present a kinetic model of crystal growth of polymers of finite molecular weight. Experiments help to classify polymer crystallization broadly into two kinetic regimes. One is observed in melts or in high molar mass polymer solutions and…

软凝聚态物质 · 物理学 2009-11-11 Arindam Kundagrami , M. Muthukumar

We present computer simulations of a dynamic Monte Carlo algorithm for polymer chains on the FCC lattice which takes explicitly into account the possibility to overcome topological constraints by controlling the rate at which nearby polymer…

软凝聚态物质 · 物理学 2021-12-01 Mattia Alberto Ubertini , Angelo Rosa

The viscosity enhancement of a solvent produced by the addition of thickening branched polymers is predicted as a function of polymer concentration, branch length and persistence length, and strength of the covalent bonding interactions.…

软凝聚态物质 · 物理学 2021-08-02 E. Mayoral , A. Gama Goicochea

Normalizing flows are a class of machine learning models used to construct a complex distribution through a bijective mapping of a simple base distribution. We demonstrate that normalizing flows are particularly well suited as a Monte Carlo…

核理论 · 物理学 2021-08-11 Jack Brady , Pengsheng Wen , Jeremy W. Holt
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