English
Related papers

Related papers: Capturing Subdiffusive Solute Dynamics and Predict…

200 papers

Generative models on discrete state-spaces have a wide range of potential applications, particularly in the domain of natural sciences. In continuous state-spaces, controllable and flexible generation of samples with desired properties has…

Machine Learning · Computer Science 2025-03-27 Hunter Nisonoff , Junhao Xiong , Stephan Allenspach , Jennifer Listgarten

We introduce the concept of Randomly Modulated Gaussian Processes as a unifying framework for modeling, analyzing and classifying anomalous diffusion models in heterogeneous media. This formulation incorporates correlations in the…

Biological Physics · Physics 2026-03-16 Yann Lanoiselée , Denis S. Grebenkov , Gianni Pagnini

Lithium diffusion in solid-state battery anodes occurs through thermally activated hops between metastable sites often separated by large energy barriers, making such events rare on ab initio molecular dynamics (AIMD) timescales. Here, we…

We propose a stochastic model for intracellular transport processes associated with the activity of molecular motors. This out-of-equilibrium model, based on a generalized Langevin equation, considers a particle immersed in a viscoelastic…

Biological Physics · Physics 2009-04-15 L. Bruno , M. A. Despósito

The diffusive transport of particles in anisotropic media is a fundamental phenomenon in computational, medical and biological disciplines. While deterministic models (partial differential equations) of such processes are well established,…

Computational Physics · Physics 2025-10-20 Luke P. Filippini , Adrianne L. Jenner , Elliot J. Carr

A variety of enhanced statistical and numerical methods are now routinely used to extract comprehensible and relevant thermodynamic information from the vast amount of complex, high-dimensional data obtained from intensive molecular…

Soft Condensed Matter · Physics 2020-10-14 Francois Sicard , Vladimir Koskin , Alessia Annibale , Edina Rosta

Mathematically modelling diffusive and advective transport of particles in heterogeneous layered media is important to many applications in computational, biological and medical physics. While deterministic continuum models of such…

Computational Physics · Physics 2024-09-16 Elliot J. Carr

Translational diffusion coefficients are routinely estimated from molecular dynamics simulations. Linear fits to mean squared displacement (MSD) curves have become the de facto standard, from simple liquids to complex biomacromolecules.…

Computational Physics · Physics 2020-11-20 Jakob Tómas Bullerjahn , Sören von Bülow , Gerhard Hummer

Monte Carlo (MC) simulations of transport in random porous networks indicate that for high variances of the log-normal permeability distribution, the transport of a passive tracer is non-Fickian. Here we model this non-Fickian dispersion in…

Computational Physics · Physics 2018-08-01 Amir H. Delgoshaie , Patrick Jenny , Hamdi A. Tchelepi

Conditional diffusion models provide a natural framework for probabilistic prediction of dynamical systems and have been successfully applied to fluid dynamics and weather prediction. However, in many settings, the available information at…

Porous materials are widely used for applications in gas storage and separation. The diffusive properties of a variety of gases in porous media can be modeled using molecular dynamics simulations that can be computationally demanding…

Chemical Physics · Physics 2023-09-19 Gastón González , Rubén A. Fritz , Yamil J. Colón , Felipe Herrera

When a fluid carrying a passive solute flows quickly through porous media, three key macroscale transport mechanisms occur. These mechanisms are diffusion, advection and dispersion, all of which depend on the microstructure of the porous…

Fluid Dynamics · Physics 2024-10-16 Lucy C Auton , Mohit P. Dalwadi , Ian M. Griffiths

A ubiquitous observation in cell biology is that diffusion of macromolecules and organelles is anomalous, and a description simply based on the conventional diffusion equation with diffusion constants measured in dilute solution fails. This…

Soft Condensed Matter · Physics 2013-03-14 Felix Höfling , Thomas Franosch

One of the most promising applications in nanoscience is the design of new materials to improve water permeability and selectivity of nanoporous membranes. Understanding the molecular architecture behind these fascinating structures and how…

Soft Condensed Matter · Physics 2021-09-10 João P. K. Abal , Rodrigo F. Dillenburg , Mateus H. Köhler , Marcia C. Barbosa

Understanding how colloids move in crowded environments is key for gaining control over their transport in applications such as drug delivery, filtration, contaminant/microplastic remediation and agriculture. The classical models of colloid…

Soft Condensed Matter · Physics 2026-04-15 Mobin Alipour , Yiran Li , Haoyu Liu , Amir A. Pahlavan

The influence of periodic and random surface textures on the flow structure and effective slip length in Newtonian fluids is investigated by molecular dynamics (MD) simulations. We consider a situation where the typical pattern size is…

Soft Condensed Matter · Physics 2011-11-24 Nikolai V. Priezjev

The silo discharge process is studied by molecular dynamics simulations. The development of the velocity profile and the probability density function for the displacements in the horizontal and vertical axis are obtained. The PDFs obtained…

Statistical Mechanics · Physics 2009-11-11 R. Arevalo , A. Garcimartin , D. Maza

The interaction of multiple fluids through a heterogeneous pore space leads to complex pore-scale flow dynamics, such as intermittent pathway flow. The non-local nature of these dynamics, and the size of the 4D datasets acquired to capture…

There have been increasing reports that the diffusion coefficient of macromolecules depends on time and fluctuates randomly. Here, a novel method to elucidate the fluctuating diffusivity from trajectory data is developed. The time-averaged…

Statistical Mechanics · Physics 2017-10-25 Tomoshige Miyaguchi

We model two time and space scales discrete observations by using a unique continuous diffusion process with time dependent coefficient. We define new parameters for the large scale model as functions of the small scale distribution…

Methodology · Statistics 2009-09-09 V. Calian , G. Stefansson , L. P. Folkow , A. S. Blix