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In this paper we review some recent results, obtained jointly with Stu Whittington, for a mathematical model describing a copolymer in an emulsion. The copolymer consists of hydrophobic and hydrophilic monomers, concatenated randomly with…

Probability · Mathematics 2007-06-14 F. den Hollander , N. Petrelis

A dielectric model of electrostatic solvation is applied to describe potentials of mean force in water along reaction paths for: a) formation of a sodium chloride ion pair; b) the symmetric SN2 exchange of chloride in methylchloride; and c)…

chem-ph · Physics 2008-02-03 Gregory J. Tawa , Lawrence R. Pratt

The hydrogen mean force from experimental neutron Compton profiles is derived using deep inelastic neutron scattering on amorphous and polycrystalline ice. The formalism of mean force is extended to probe its sensitivity to anharmonicity in…

The determination of potentials of mean force for solute insertion in a membrane by means of all-atom molecular dynamics simulations is often hampered by sampling issues. A multiscale approach to conformational sampling was recently…

Chemical Physics · Physics 2017-10-09 Roberto Menichetti , Kurt Kremer , Tristan Bereau

A homogenised model is developed to describe the interaction between aligned strings and an incompressible, viscous, Newtonian fluid. In the case of many strings, the ratio of string separation to domain width gives a small parameter which…

Fluid Dynamics · Physics 2022-02-15 A. Kent , S. L. Waters , J. Oliver , S. J. Chapman

A hallmark of meso-scale interfacial fluids is the multi-faceted, scale-dependent interfacial energy, which often manifests different characteristics across the molecular and continuum scale. The multi-scale nature imposes a challenge to…

Computational Physics · Physics 2023-02-22 Pei Ge , Linfeng Zhang , Huan Lei

Water's phase diagram remains one of the most intricate and challenging benchmarks in molecular modeling. In this study, we compute the phase diagram of water using an Atomic Cluster Expansion (ACE) potential trained on density-functional…

Materials Science · Physics 2026-01-21 Eslam Ibrahim , Yury Lysogorskiy , Ralf Drautz , Pablo Piaggi

We present a hydrodynamic theory describing pair diffusion in systems with periodic boundary conditions, thereby generalizing earlier work on self-diffusion [D\"unweg and Kremer, J. Chem. Phys. 1993, 99, 6983-6997; Yeh and Hummer, J. Phys.…

Soft Condensed Matter · Physics 2023-05-03 Diddo Diddens , Andreas Heuer

The present research proposes a new memory-efficient method using diffusion models to inject turbulent inflow conditions into Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) for various flow problems. A guided diffusion…

Application of integral equation theory to complex fluids is reviewed, with particular emphasis to the effects of polydispersity and anisotropy on their structural and thermodynamic properties. Both analytical and numerical solutions of…

Soft Condensed Matter · Physics 2011-12-23 Domenico Gazzillo , Achille Giacometti

In this paper we consider a mathematical model describing the two-phase interaction between water and mud in a water canal when the width of the canal is small compared to its depth. The mud is treated as a non-Netwonian fluid and the…

Analysis of PDEs · Mathematics 2015-10-28 Joachim Escher , Anca-Voichita Matioc

The effects of mid-range repulsion in Lattice Boltzmann models on the coalescence/breakup behaviour of single-component, non-ideal fluids are investigated. It is found that mid-range repulsive interactions allow the formation of spray-like,…

Fluid Dynamics · Physics 2015-05-19 S. Chibbaro , G. Falcucci , G. Chiatti , H. Chen , X. Shan , S. Succi

We discuss the role coarse-grained models play in the investigation of the structure and thermodynamics of bilayer membranes, and we place them in the context of alternative approaches. Because they reduce the degrees of freedom and employ…

Soft Condensed Matter · Physics 2009-11-11 Marcus Mueller , Kirill Katsov , Michael Schick

Coarse-grained molecular dynamics often sacrifices accuracy and transferability for computational efficiency, but the use of machine learned potentials is helping coarse-grained models attain performance on par with atomistic molecular…

Chemical Physics · Physics 2026-02-17 Abigail Park , Shriram Chennakesavalu , Grant M. Rotskoff

It is known that a finite-size homogeneous granular fluid develops an hydrodynamic-like instability when dissipation crosses a threshold value. This instability is analyzed in terms of modified hydrodynamic equations: first, a source term…

Statistical Mechanics · Physics 2009-10-31 R. Soto , M. Mareschal , M. Malek Mansour

We present efficient deep learning techniques for approximating flow and transport equations for both single phase and two-phase flow problems. The proposed methods take advantages of the sparsity structures in the underlying discrete…

Numerical Analysis · Mathematics 2020-01-08 Yating Wang , Guang Lin

With molecular simulation for water and a tunable hydrophobic substrate, we apply the instantaneous interface construction [A. P. Willard and D. Chandler, J. Phys. Chem. B, 114, 1954 (2010)] to examine the similarity between a water-vapor…

Soft Condensed Matter · Physics 2015-01-21 Adam P. Willard , David Chandler

A ubiquitous approach to obtain transferable machine learning-based models of potential energy surfaces for atomistic systems is to decompose the total energy into a sum of local atom-centred contributions. However, in many systems…

Computational Physics · Physics 2024-06-18 Jack Thomas , William J. Baldwin , Gábor Csányi , Christoph Ortner

A hybrid mesoscopic multi-particle collision model is used to study diffusion-influenced reaction kinetics. The mesoscopic particle dynamics conserves mass, momentum and energy so that hydrodynamic effects are fully taken into account.…

Chemical Physics · Physics 2007-05-23 Kay Tucci , Raymond Kapral

his article extends the fluctuation-dissipation analysis to generic complex fluids in confined geometries and to all the cases the hydromechanic fluid-interaction kernels may depend on the particle position. This represents a completely new…

Statistical Mechanics · Physics 2024-09-13 Massimiliano Giona , Giuseppe Procopo , Chiara Pezzotti
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