Superadiabatic dynamical density functional study of Brownian hard-spheres in time-dependent external potentials

  • Superadiabatic dynamical density functional theory (superadiabatic-DDFT), a first-principles approach based on inhomogeneous two-body correlation functions, is employed to investigate the response of interacting Brownian particles to time-dependent external driving. Predictions for the superadiabatic dynamics of the one-body density are made directly from the underlying interparticle interactions without the need for either adjustable fit parameters or simulation input. The external potentials we investigate have been chosen to probe distinct aspects of structural relaxation in dense, strongly interacting liquid states. Nonequilibrium density profiles predicted by the superadiabatic theory are compared with those obtained from both adiabatic DDFT and event-driven Brownian dynamics simulation. Our findings show that superadiabatic-DDFT accurately predicts the time-evolution of the one-body density.

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Metadaten
Author:S. M. Tschopp, Hidde D. VuijkORCiDGND, J. M. Brader
URN:urn:nbn:de:bvb:384-opus4-1063297
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/106329
ISSN:0021-9606OPAC
ISSN:1089-7690OPAC
Parent Title (English):The Journal of Chemical Physics
Publisher:AIP Publishing
Place of publication:Melville, NY
Type:Article
Language:English
Year of first Publication:2023
Publishing Institution:Universität Augsburg
Release Date:2023/07/25
Tag:Physical and Theoretical Chemistry; General Physics and Astronomy
Volume:158
Issue:23
First Page:234904
DOI:https://doi.org/10.1063/5.0155856
Institutes:Mathematisch-Naturwissenschaftlich-Technische Fakultät
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik
Mathematisch-Naturwissenschaftlich-Technische Fakultät / Institut für Physik / Lehrstuhl für Theoretische Physik II
Dewey Decimal Classification:5 Naturwissenschaften und Mathematik / 53 Physik / 530 Physik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)