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Achieving strongly symmetric stress approximations for linear elasticity problems in high-contrast media poses a significant computational challenge. Conventional methods often struggle with prohibitively high computational costs due to…

Numerical Analysis · Mathematics 2025-09-03 Eric T. Chung , Changqing Ye , Xiang Zhong

The last decade has witnessed a swiftly increasing interest in the design and production of novel multivalent molecules as powerful alternatives for conventional antibodies in the fight against cancer and infectious diseases. However, while…

Soft Condensed Matter · Physics 2019-08-23 Suman Saurabh , Francesco Piazza

Geochemical data provide key information on the timing of accretion and on the prevailing physical conditions during core/mantle differentiation. However, their interpretation depends critically on the efficiency of metal/silicate chemical…

Geophysics · Physics 2018-12-20 Victor Lherm , Renaud Deguen

New hybrid Molecular Dynamics-Monte Carlo methods are proposed to increase the efficiency of constant-pressure simulations. Two variations of the isobaric Molecular Dynamics component of the algorithms are considered. In the first, we use…

Soft Condensed Matter · Physics 2009-11-07 Roland Faller , Juan J. de Pablo

We report here how the hydration of complex surfaces can be efficiently studied thanks to recent advances in classical molecular density functional theory. This is illustrated on the example of the pyrophylite clay. After presenting the…

The microstructure of materials evolves through chemical reactions and mechanical stress, often strongly coupled in phenomena such as pressure solution or crystallization pressure. This article presents MASKE: a simulator to address the…

Other Condensed Matter · Physics 2024-09-26 Enrico Masoero

Molecular dynamics is a powerful tool for studying the thermodynamics and kinetics of complex molecular events. However, these simulations can rarely sample the required time scales in practice. Transition path sampling overcomes this…

Chemical Physics · Physics 2023-07-31 Gianmarco Lazzeri , Hendrik Jung , Peter G. Bolhuis , Roberto Covino

Na-montmorillonite hydrates in presence of ethane molecules are studied by means of hybrid Monte Carlo simulations in the NPzzT and MuPzzT ensembles. The NPzzT ensemble allows us to study the interlaminar distance as a function of water and…

Chemical Physics · Physics 2016-08-16 G. Odriozola , J. F. Aguilar , J. López-Lemus

Recently, bacterial nanocellulose (BNC), a biological material produced by non-pathogenic bacteria that possesses excellent material properties for various medical applications, has received increased interest as a carrier system for drug…

Signal Processing · Electrical Eng. & Systems 2026-03-03 Sebastian Lotter , Marco Seiter , Maryam Pirmoradi , Lukas Brand , Dagmar Fischer , Robert Schober

Treating realistically the ambient water is one of the main difficulties in applying Monte Carlo methods to protein folding. The solvent-accessible area method, a popular method for treating water implicitly, is investigated by means of…

Soft Condensed Matter · Physics 2007-05-23 Hsiao-Ping Hsu , Bernd A. Berg , Peter Grassberger

This paper presents recent investigation results on free molecular flows over a diffusely or specularly reflective ellipse, by using the gaskinetic theory. A virtual density distribution along the a diffusely reflective surface is…

Fluid Dynamics · Physics 2020-06-03 Shiying Cai , Chunpei Cai , Jun Li

Monte Carlo simulations are widely employed to measure the physical properties of glass-forming liquids in thermal equilibrium. Combined with local Monte Carlo moves, the Metropolis algorithm can also be used to simulate the relaxation…

Statistical Mechanics · Physics 2024-09-23 Ludovic Berthier , Federico Ghimenti Frédéric van Wijland

A key factor influencing a drug's efficacy is its residence time in the binding pocket of the host protein. Using atomistic computer simulation to predict this residence time and the associated dissociation process is a desirable but…

Soft Condensed Matter · Physics 2015-10-08 Pratyush Tiwary , Jagannath Mondal , Joseph A. Morrone , B. J. Berne

Coarse-graining (CG) enables molecular dynamics (MD) simulations of larger systems and longer timescales that are otherwise infeasible with atomistic models. Machine learning potentials (MLPs), with their capacity to capture many-body…

Chemical Physics · Physics 2025-12-01 Weilong Chen , Franz Görlich , Paul Fuchs , Julija Zavadlav

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…

Soft Condensed Matter · Physics 2011-11-01 Takahiro Murashima , Takashi Taniguchi

We study random walks on the dilute hypercube using an exact enumeration Master equation technique, which is much more efficient than Monte Carlo methods for this problem. For each dilution $p$ the form of the relaxation of the memory…

Disordered Systems and Neural Networks · Physics 2009-10-31 R. M. C. de Almeida , N. Lemke , I. A. Campbell

While the power stroke of myosin and the release of inorganic phosphate (Pi) play crucial roles in transforming ATP's chemical energy into mechanical work across diverse biological systems, the exact temporal relationship between these…

Biological Physics · Physics 2025-06-03 Jiaxiang Xu , Jiangke Tao , Bin Chen

Multiscale simulation methods have been developed based on the local stress sampling strategy and applied to three flow problems with different difficulty levels: (a) general flow problems of simple fluids, (b) parallel (one-dimensional)…

Soft Condensed Matter · Physics 2011-01-07 Takahiro Murashima , Takashi Taniguchi , Ryoichi Yamamoto , Shugo Yasuda

An extended volume of fluid method is developed for two-phase direct numerical simulations of systems with one viscoelastic and one Newtonian phase. A complete set of governing equations is derived by conditional volume-averaging of the…

Fluid Dynamics · Physics 2020-12-08 Matthias Niethammer , Günter Brenn , Holger Marschall , Dieter Bothe

Optimising discrete data for a desired characteristic using gradient-based methods involves projecting the data into a continuous latent space and carrying out optimisation in this space. Carrying out global optimisation is difficult as…

Machine Learning · Computer Science 2019-05-27 Omar Mahmood , José Miguel Hernández-Lobato
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