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Ordered phases on curved substrates experience a complex interplay of ordering and intrinsic curvature, commonly producing frustration and singularities. This is an especially important issue in crystals as ever-smaller scale materials are…

Soft Condensed Matter · Physics 2012-07-23 Ricardo A. Mosna , Daniel A. Beller , Randall D. Kamien

The short-range attraction and long-range repulsion (SALR) between nanoparticles or macromolecules can lead to spontaneous pattern formation on solid surfaces, fluid interfaces or membranes. In order to study the self-assembly in such…

Soft Condensed Matter · Physics 2014-01-07 J. Pekalski , A. Ciach , N. Almarza

Pressure-induced phase transitions of spin-crossover materials were simulated by a Monte Carlo simulation in the constant pressure ensemble for the first time. Here, as the origin of the cooperative interaction, we adopt elastic interaction…

Materials Science · Physics 2008-04-09 Yusuke Konishi , Hiroko Tokoro , Masamichi Nishino , Seiji Miyashita

Elastic systems that are spatially heterogeneous in their mechanical response pose special challenges for molecular simulations. Standard methods for sampling thermal fluctuations of a system's size and shape proceed through a series of…

Materials Science · Physics 2015-05-13 Sander Pronk , Phillip L. Geissler

Computer simulation was used to study the random sequential adsorption of identical discorectangles onto a continuous plane . The problem was analyzed for a wide range of discorectangle aspect ratios ($\varepsilon \in [1;100]$). We studied…

Soft Condensed Matter · Physics 2020-09-02 Nikolai I. Lebovka , Nikolai V. Vygornitskii , Yuri Yu. Tarasevich

Soft particles are known to overlap and form stable clusters that self-assemble into periodic crystalline phases with density-independent lattice constants. We use molecular dynamics simulations in two dimensions to demonstrate that,…

Soft Condensed Matter · Physics 2014-09-08 Kobi Barkan , Michael Engel , Ron Lifshitz

In living cells, proteins self-assemble into large functional structures based on specific interactions between molecularly complex patches. Due to this complexity, protein self-assembly results from a competition between a large number of…

Soft Condensed Matter · Physics 2024-12-10 Lara Koehler , Pierre Ronceray , Martin Lenz

We introduce a `virtual-move' Monte Carlo (VMMC) algorithm for systems of pairwise-interacting particles. This algorithm facilitates the simulation of particles possessing attractions of short range and arbitrary strength and geometry, an…

Statistical Mechanics · Physics 2009-11-11 Stephen Whitelam , Phillip L. Geissler

Anisotropy at the level of the inter-particle interaction provides the particles with specific instructions for the self-assembly of target structures. The ability to synthesize non-spherical colloids, together with the possibility of…

Soft Condensed Matter · Physics 2020-01-03 Carina Karner , Christoph Dellago , Emanuela Bianchi

A microscopic model of adsorption in cluster forming systems with competing interaction is considered. The adsorption process is described by the master equation and modelled by a kinetic Monte Carlo method. The evolution of the particle…

Soft Condensed Matter · Physics 2021-09-07 E. Bildanau , V. Vikhrenko

The complexity of condensed matter arises from emergent behaviors that cannot be understood by analyzing individual constituents in isolation. While traditional condensed-matter approaches-developed primarily for ideal crystalline…

Materials Science · Physics 2025-09-30 Elisabetta Nocerino

The separation of substances into different phases is ubiquitous in nature and important scientifically and technologically. This phenomenon may become drastically different if the species involved, whether molecules or supramolecular…

Successful computer studies of glass-forming materials need to overcome both the natural tendency to structural ordering and the dramatic increase of relaxation times at low temperatures. We present a comprehensive analysis of eleven…

Statistical Mechanics · Physics 2017-06-09 Andrea Ninarello , Ludovic Berthier , Daniele Coslovich

Random sequential adsorption of binary mixtures of extended objects on a two-dimensional triangular lattice is studied numerically by means of Monte Carlo simulations. The depositing objects are formed by self-avoiding random walks on the…

Statistical Mechanics · Physics 2009-11-13 I. Lončarević , Lj. Budinski-Petković , S. B. Vrhovac

Commonly used linear and nonlinear constitutive material models in deformation simulation contain many simplifications and only cover a tiny part of possible material behavior. In this work we propose a framework for learning customized…

Graphics · Computer Science 2020-10-27 Bin Wang , Yuanmin Deng , Paul Kry , Uri Ascher , Hui Huang , Baoquan Chen

Many disordered crystalline materials show chemical short range order and relaxation of neighboring atoms. Local structural information can be obtained by analyzing the atomic pair distribution function (PDF). The viability of reverse Monte…

Materials Science · Physics 2007-05-23 Th. Proffen

Many physical systems are well described on domains which are relatively large in some directions but relatively thin in other directions. In this scenario we typically expect the system to have emergent structures that vary slowly over the…

Dynamical Systems · Mathematics 2016-12-15 A. J. Roberts , J. E. Bunder

A crystal lattice, when confined to the surface of a cylinder, must have a periodic structure that is commensurate with the cylinder circumference. This constraint can frustrate the system, leading to oblique crystal lattices or to…

Soft Condensed Matter · Physics 2013-07-03 D. A. Wood , C. D. Santangelo , A. D. Dinsmore

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

Reduced order models are computationally inexpensive approximations that capture the important dynamical characteristics of large, high-fidelity computer models of physical systems. This paper applies machine learning techniques to improve…

Machine Learning · Computer Science 2015-11-11 Azam Moosavi , Razvan Stefanescu , Adrian Sandu