Learning effective SDEs from Brownian dynamic simulations of colloidal particles-Reference-Cited by-同舟云学术

Learning effective SDEs from Brownian dynamic simulations of colloidal particles

Published:2023 Issue:7 Volume:8 Page:887-901
ISSN:2058-9689
Container-title:Molecular Systems Design & Engineering
language:en
Short-container-title:Mol. Syst. Des. Eng.

Author:

Evangelou Nikolaos¹^ORCID,Dietrich Felix²^ORCID,Bello-Rivas Juan M.¹,Yeh Alex J.¹,Hendley Rachel S.¹^ORCID,Bevan Michael A.¹^ORCID,Kevrekidis Ioannis G.¹

Affiliation:

1. Department of Chemical and Biomolecular Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, 21218, MD, USA

2. Department of Informatics, Technical University of Munich, 3 Boltzmannstr, Munich, 85748, Germany

Abstract

We construct a reduced, data-driven, parameter dependent effective Stochastic Differential Equation (eSDE) for electric-field mediated colloidal crystallization using data obtained from Brownian dynamics simulations.

Funder

National Science Foundation

Air Force Office of Scientific Research

U.S. Department of Energy

Publisher

Royal Society of Chemistry (RSC)

Subject

Materials Chemistry,Industrial and Manufacturing Engineering,Process Chemistry and Technology,Energy Engineering and Power Technology,Biomedical Engineering,Chemical Engineering (miscellaneous),Chemistry (miscellaneous)

Link

http://pubs.rsc.org/en/content/articlepdf/2023/ME/D2ME00086E

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