Dynamical Effective Field Model for Interacting Ferrofluids: II. The proper relaxation time and effects of dynamic correlations
Angbo Fang

TL;DR
This paper refines the dynamical effective field model for ferrofluids by clarifying the relation between relaxation times, introducing correlation factors, and validating predictions with simulations, enhancing understanding of ferrofluid dynamics.
Contribution
It establishes a quantitative link between dressed and bare particle relaxation times, introduces correlation factors for dynamic effects, and provides a parameter-free predictive framework validated by simulations.
Findings
Relaxation time of dressed particles equals long-time self-diffusion time.
Correlation factors effectively describe inter-particle effects.
Model predictions agree well with Brownian dynamics simulations.
Abstract
The recently proposed dynamical effective field model (DEFM) is quantitatively accurate for describing dynamical magnetic response of ferrofluids. In paper I it is derived under the framework of dynamical density functional theory, via which the original ensemble of bare Brownian particles is mapped to an ensemble of dressed particles. However, it remains to clarify how the characteristic rotational relaxation time of a dressed particle, denoted by , is quantitatively related to that of a bare particle, denoted by . By building macro-micro connections via two different routes, I reveal that under some gentle assumptions can be identified with the long-time rotational self-diffusion time. I further introduce two simple but useful integrated correlation factors, describing the effects of quasi-static (adiabatic) and dynamic (nonadiabatic) inter-particle…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCharacterization and Applications of Magnetic Nanoparticles · Geomagnetism and Paleomagnetism Studies · Microfluidic and Bio-sensing Technologies
