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Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorporate thermodynamic structure into neural networks have recently shown strong performance…

Machine Learning · Computer Science 2026-03-17 Karim K. Ben Hicham , Moreno Ascani , Jan G. Rittig , Alexander Mitsos

Interacting-Particle Reaction Dynamics (iPRD) simulates the spatiotemporal evolution of particles that experience interaction forces and can react with one another. The combination of interaction forces and reactions enable a wide range of…

Chemical Physics · Physics 2018-07-20 Christoph Fröhner , Frank Noé

This article presents an entropy stability analysis of smoothed dissipative particle dynamics (SDPD) to review the validity of particle discretization of entropy equations. First, we consider the simplest SDPD system: a simulation of…

Statistical Mechanics · Physics 2026-02-26 Satori Tsuzuki

Many-body dissipative particle dynamics is constructed to exhibit vapour-liquid coexistence, with a sharp interface, and a vapour phase of vanishingly small density. In this form, the model is an unusual example of a soft-sphere liquid with…

Statistical Mechanics · Physics 2009-11-10 P. B. Warren

The discrete-dipole approximation (DDA) is a flexible technique for computing scattering and absorption by targets of arbitrary geometry. In this paper we perform systematic study of various non-stationary iterative (conjugate gradient)…

Atmospheric and Oceanic Physics · Physics 2007-05-23 Piotr J. Flatau

A new time discretization scheme for the numerical simulation of two-phase flow governed by a thermodynamically consistent diffuse interface model is presented. The scheme is consistent in the sense that it allows for a discrete in time…

Analysis of PDEs · Mathematics 2014-02-27 Harald Garcke , Michael Hinze , Christian Kahle

Temperature plays a pivotal role in moderating label softness in the realm of knowledge distillation (KD). Traditional approaches often employ a static temperature throughout the KD process, which fails to address the nuanced complexities…

Machine Learning · Computer Science 2024-04-22 Yukang Wei , Yu Bai

We present a direct numerical simulation method for investigating the dynamics of dispersed particles in a compressible solvent fluid. The validity of the simulation is examined by calculating the velocity relaxation of an impulsively…

Soft Condensed Matter · Physics 2015-06-04 Rei Tatsumi , Ryoichi Yamamoto

Emergent phenomena share the fascinating property of not being obvious consequences of the design of the system in which they appear. This characteristic is no less relevant when attempting to simulate such phenomena, given that the outcome…

Soft Condensed Matter · Physics 2014-11-26 D. C. Rapaport

We present a local detection method for dissipative particle dynamics (DPD) involving arbitrarily shaped geometric three-dimensional domains. By introducing an indicator variable of boundary volume fraction (BVF) for each fluid particle,…

Computational Physics · Physics 2020-05-12 Zhen Li , Xin Bian , Yu-Hang Tang , George Em Karniadakis

One considers the motion of a test particle in an homogeneous fluid in equilibrium at temperature $T$, undergoing dissipative collisions with the fluid particles. It is shown that the corresponding linear Boltzmann equation still posseses a…

Statistical Mechanics · Physics 2007-05-23 Ph. A. Martin , J. Piasecki

We perform molecular dynamic simulations of liquid nanoparticles deposited on a disordered substrate. The motion of the nanoparticle is characterised by a 'stick and roll' diffusive process. Long simulation times ($\simeq \mu s$), analysis…

Materials Science · Physics 2009-11-10 F. Celestini

We introduce a dissipative particle dynamics scheme for the dynamics of non-ideal fluids. Given a free-energy density that determines the thermodynamics of the system, we derive consistent conservative forces. The use of these effective,…

Soft Condensed Matter · Physics 2009-11-07 I. Pagonabarraga , D. Frenkel

In this work we compare and characterize the behavior of Langevin and Dissipative Particle Dynamics (DPD) thermostats in a broad range of non-equilibrium simulations of polymeric systems. Polymer brushes in relative sliding motion,…

Soft Condensed Matter · Physics 2007-08-31 C. Pastorino , T. Kreer , M. Mueller , K. Binder

Dynamic Mode Decomposition (DMD) is an equation-free method that aims at reconstructing the best linear fit from temporal datasets. In this paper, we show that DMD does not provide accurate approximation for datasets describing oscillatory…

Numerical Analysis · Mathematics 2023-03-14 Alessandro Alla , Angela Monti , Ivonne Sgura

We present a class of new explicit and stable numerical algorithms to solve the spatially discretized linear heat or diffusion equation. After discretizing the space and the time variables like conventional finite difference methods, we do…

Numerical Analysis · Mathematics 2021-04-27 Endre Kovács

We present a comprehensive analysis of effective temperatures based on fluctuation-dissipation relations in a model of an active fluid composed of self-propelled hard disks. We first investigate the relevance of effective temperatures in…

Statistical Mechanics · Physics 2015-10-20 Demian Levis , Ludovic Berthier

Thermodynamics and dynamics of a classical two-dimensional system with dipole-like isotropic repulsive interactions are studied systematically using extensive molecular dynamics (MD) simulations supplemented by appropriate theoretical…

Soft Condensed Matter · Physics 2018-03-02 Sergey Khrapak , Nikita Kryuchkov , Stanislav Yurchenko

Microscopic dynamics reveal the origin of the bulk rheological response in complex fluids. In model systems particle motion can be tracked, but for industrially relevant samples this is often impossible. Here we adapt differential dynamic…

Soft Condensed Matter · Physics 2022-02-23 James A. Richards , Vincent A. Martinez , Jochen Arlt

Distribution matching distillation (DMD) facilitates few-step image generation by aligning a distilled student with a reference multi-step teacher. In practice, however, optimizing DMD can reduce sample diversity in few-step synthesis, and…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Tianhe Wu , Ruibin Li , Lei Zhang , Kede Ma
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