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Techniques for simulating molecules whose conformations satisfy constraints are presented. A method for selecting appropriate moves in Monte Carlo simulations is given. The resulting moves not only obey the constraints but also maintain…

Computational Physics · Physics 2007-05-23 Charles F. F. Karney , Jason E. Ferrara

This review provides an introduction to the essential physics of soft adhesion, including the thermodynamics of adhesion and wetting, the mechanics of contact with deformable materials, and the material properties that most affect…

Soft Condensed Matter · Physics 2026-03-23 Katharine E. Jensen , Chelsea S. Davis

We use molecular dynamic to simulate the directional growth of binary mixtures. our results compare very well with analitical and experimental results. This opens up the possibility to probe growth situations which are difficult to reach…

Statistical Mechanics · Physics 2007-05-23 B. V. Costa , P. Z. Coura , O. N. Mesquita

We examine the performance of various commonly used integration schemes in dissipative particle dynamics simulations. We consider this issue using three different model systems, which characterize a variety of different conditions often…

Soft Condensed Matter · Physics 2009-11-07 Ilpo Vattulainen , Mikko Karttunen , Gerhard Besold , J. M. Polson

Living organisms intertwine soft (e.g., muscle) and hard (e.g., bones) materials, giving them an intrinsic flexibility and resiliency often lacking in conventional rigid robots. The emerging field of soft robotics seeks to harness these…

Robotics · Computer Science 2018-02-21 John Rieffel , Jean-Baptiste Mouret

We study the thermodynamics and kinetics of folding for a small peptide. Our data rely on Monte Carlo simulations where the interactions among all atoms are taken into account. Monte Carlo kinetics is used to study folding of the peptide at…

Condensed Matter · Physics 2009-11-07 Ulrich H. E. Hansmann , Jose N. Onuchic

Particles added to a fluid interface can be used as a surface stabilizer in the food, oil and cosmetic industries. As an alternative to rigid particles, it is promising to consider highly deformable particles that can adapt their…

Soft Condensed Matter · Physics 2016-10-27 Hadi Mehrabian , Jens Harting , Jacco H. Snoeijer

This paper gives an overview of the particle transport theory essentials, the basics of particle-material interaction simulation, physical quantities needed to simulate particle transport and interactions in materials, Monte Carlo…

Accelerator Physics · Physics 2020-06-18 Nikolai Mokhov

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

adap-org · Physics 2012-08-29 Thorsten Poeschel , Volkhard Buchholtz

We propose a new model for the description of complex granular particles and their interaction in molecular dynamics simulations of granular material in two dimensions. The grains are composed of triangles which are connected by deformable…

Materials Science · Physics 2007-05-23 Thorsten Poeschel , Volkhard Buchholtz

The mechanisms of physical and chemical interactions of low temperature plasmas with surfaces can be fruitfully explored using molecular dynamics (MD) simulations. MD simulations follow the detailed motion of sets of interacting atoms…

Computational Physics · Physics 2015-05-13 David B. Graves , Pascal Brault

Along with recent progress in structural biology and genome biology, structural dynamics of molecular systems including nucleic acids has attracted attention in the context of gene regulation. Structure-function relationship is an important…

Biomolecules · Quantitative Biology 2021-11-23 Takeru Kameda , Akinori Awazu , Yuichi Togashi

A computer simulation has to be fast to be helpful, if it is employed to study the behavior of a multicomponent dynamic system. This paper discusses modeling concepts and algorithmic techniques useful for creating such fast simulations.…

Data Structures and Algorithms · Computer Science 2007-05-23 Boris D. Lubachevsky

The systematic errors due to the practical implementation of the Contact Dynamics method for simulation of dense granular media are examined. It is shown that, using the usual iterative solver to simulate a chain of rigid particles,…

Soft Condensed Matter · Physics 2009-11-07 Tamas Unger , Lothar Brendel , Dietrich E. Wolf , Janos Kertesz

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-bridging over brute-force increases in the number of mesh…

In recent years, soft robotics simulators have evolved to offer various functionalities, including the simulation of different material types (e.g., elastic, hyper-elastic) and actuation methods (e.g., pneumatic, cable-driven, servomotor).…

Robotics · Computer Science 2025-02-03 Etienne Ménager , Louis Montaut , Quentin Le Lidec , Justin Carpentier

Since the surge of data in materials science research and the advancement in machine learning methods, an increasing number of researchers are introducing machine learning techniques into the next generation of materials discovery, ranging…

Soft Condensed Matter · Physics 2024-08-12 Maya M. Martirossyan , Hongjin Du , Julia Dshemuchadse , Chrisy Xiyu Du

I review recent progress in study of strongly interacting matter at high temperatures using Monte-Carlo simulations in lattice QCD.

High Energy Physics - Lattice · Physics 2015-06-04 P. Petreczky

The Dynamic Monte Carlo (DMC) method is an established molecular simulation technique for the analysis of the dynamics in colloidal suspensions. An excellent alternative to Brownian Dynamics or Molecular Dynamics simulation, DMC is…

Soft Condensed Matter · Physics 2020-07-15 Fabián A. García Daza , Alejandro Cuetos , Alessandro Patti

Active learning (AL) can drastically accelerate materials discovery; its power has been shown in various classes of materials and target properties. Prior efforts have used machine learning models for the optimal selection of physical…

Materials Science · Physics 2021-10-18 David E. Farache , Juan C. Verduzco , Zachary D. McClure , Saaketh Desai , Alejandro Strachan