English

Inelastic Neutron Scattering Analysis with Time-Dependent Gaussian-Field Models

Chemical Physics 2021-07-28 v1

Abstract

Converting neutron scattering data to real-space time-dependent structures can only be achieved through suitable models, which is particularly challenging for geometrically disordered structures. We address this problem by introducing time-dependent clipped Gaussian field models. General expressions are derived for all space- and time-correlation functions relevant to coherent inelastic neutron scattering, for multiphase systems and arbitrary scattering contrasts. Various dynamic models are introduced that enable one to add time-dependence to any given spatial statistics, as captured e.g. by small-angle scattering. In a first approach, the Gaussian field is decomposed into localised waves that are allowed to fluctuate in time or to move, either ballistically or diffusively. In a second approach, a dispersion relation is used to make the spectral components of the field time-dependent. The various models lead to qualitatively different dynamics, which can be discriminated by neutron scattering. The methods of the paper are illustrated with oil/water microemulsion studied by small-angle scattering and neutron spin-echo. All available data - in both film and bulk contrasts, over the entire range of qq and τ\tau- are analyzed jointly with a single model. The analysis points to static large-scale structure of the oil and water domains, while the interfaces are subject to thermal fluctuations. The fluctuations have an amplitude around 6 nm and contribute to 30 % of the total interface area.

Keywords

Cite

@article{arxiv.2106.13688,
  title  = {Inelastic Neutron Scattering Analysis with Time-Dependent Gaussian-Field Models},
  author = {Cedric J. Gommes and Reiner Zorn and Sebastian Jaksch and Henrich Frielinghaus and Olaf Holderer},
  journal= {arXiv preprint arXiv:2106.13688},
  year   = {2021}
}

Comments

The following article has been accepted by Journal of Chemical Physics. After it is published, it will be found at https://aip.scitation.org/journal/jcp/

R2 v1 2026-06-24T03:36:18.278Z