<i>refnx</i>: neutron and X-ray reflectometry analysis in Python

Nelson, Andrew; Prescott, Stuart W.

doi:10.1107/s1600576718017296

Cited by 137 publications

(155 citation statements)

References 23 publications

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“…For the specular case, BornAgain will compete with quite a number of other data analysis programs: Aurore (Gerelli, 2016), GenX (Bjö rck & Andersson, 2007), Motofit (Nelson, 2006(Nelson, , 2010, refnx (Nelson & Prescott, 2019), RasCAL (Hughes, 2014) and Refl1D . Against these, BornAgain stands out by its full support for neutron polarization, by its capability to derive scattering-length gradings from a rich and versatile particle decoration model, and not least by being institutionally supported.…”

Section: Reflectometry and Off-specular Scatteringmentioning

confidence: 99%

BornAgain: software for simulating and fitting grazing-incidence small-angle scattering

et al. 2020

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BornAgain is a free and open-source multi-platform software framework for simulating and fitting X-ray and neutron reflectometry, off-specular scattering, and grazing-incidence small-angle scattering (GISAS). This paper concentrates on GISAS. Support for reflectometry and off-specular scattering has been added more recently, is still under intense development and will be described in a later publication. BornAgain supports neutron polarization and magnetic scattering. Users can define sample and instrument models through Python scripting. A large subset of the functionality is also available through a graphical user interface. This paper describes the software in terms of the realized nonfunctional and functional requirements. The web site https://www. bornagainproject.org/ provides further documentation.

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Section: Reflectometry and Off-specular Scatteringmentioning

confidence: 99%

BornAgain: software for simulating and fitting grazing-incidence small-angle scattering

et al. 2020

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“…To compare with the simulation-derived reflectometry profiles, a modified version of the chemically-consistent surfactant monolayer model previously used in the group was applied [10,36]. This model is implemented as a class that is compatible with the Python package refnx [37,38] and is made up of two layers; the head-layer at the interface with the solvent and the tail-layer at the interface with the air. The head components have a calculated scattering length, b h , (found as a summation of the neutron scattering lengths of the individual atoms, see table S1 of the ESI) and a component volume, V h .…”

Section: Abelès Matrix Formalismmentioning

confidence: 99%

“…The ESI also includes a Python class that is compatible with refnx [37,38] allowing for simulation-derived reflectometry profiles to be obtained, using a similar method to that employed in previous work, such as Dabkowska et al [18]. The Abelès matrix formalism is applied to layers, the SLD of which is drawn directly from the simulation, and the thickness of which is defined.…”

Section: Simulation-derived Analysismentioning

confidence: 99%

Assessing molecular simulation for the analysis of lipid monolayer reflectometry

et al. 2019

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Using molecular simulation to aid in the analysis of neutron reflectometry measurements is commonplace. However, reflectometry is a tool to probe large-scale structures, and therefore the use of all-atom simulation may be irrelevant. This work presents the first direct comparison between the reflectometry profiles obtained from different all-atom and coarse-grained molecular dynamics simulations. These are compared with a traditional model layer structure analysis method to determine the minimum simulation resolution required to accurately reproduce experimental data. We find that systematic limits reduce the efficacy of the MARTINI potential model, while the Berger united-atom and Slipids all-atom potential models agree similarly well with the experimental data. The model layer structure gives the best agreement, however, the higher resolution simulationdependent methods produce an agreement that is comparable. Finally, we use the atomistic simulation to advise on possible improvements that may be offered to the model layer structures, creating a more realistic monolayer model. Usage: Electronic Supplementary Information (ESI) including all analysis/plotting scripts and figure files, allowing for a fully reproducible, and automated, analysis workflow for the work presented is available at https://github.com/arm61/sim_vs_trad A R McCluskey https:/ /orcid.org/0000-0003-3381-5911 J Grant https:/ /orcid.org/0000-0003-1362-2055 A J Smith https:/ /orcid.org/0000-0003-3745-7082 J L Rawle https:/ /orcid.org/0000-0001-8767-4443 D J Barlow https:/ /orcid.org/0000-0002-0094-5122 M J Lawrence https:/ /orcid.org/0000-0003-4738-4841 S C Parker https://orcid.org/0000-0003-3804-0975 K J Edler https:/ /orcid.org/0000-0001-5822-0127

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“…An angle of 0.8° was sufficiently shallow to capture the Si:D 2 O critical edge, allowing subsequent solvent contrasts to be correctly scaled. Data was reduced using the refnx reflectometry analysis package 51 using standard procedures, resulting in an overall Q resolution of approximately 5.1%.…”

Section: Methodsmentioning

confidence: 99%

“…Data were analyzed in the refnx reflectometry package 51 using a model constructed from a series of layers, each defined by a thickness, roughness, and SLD value as well as an optional solvent volume fraction. The layer roughness parameter describes the width of the Gaussian error function that blends consecutive layers.…”

Section: Methodsmentioning

confidence: 99%

Structure and Hydration of Asymmetric Polyelectrolyte Multilayers as Studied by Neutron Reflectometry: Connecting Multilayer Structure to Superior Membrane Performance

et al. 2020

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Porous membranes coated with so-called asymmetric polyelectrolyte multilayers (PEMs) have recently been shown to outperform commercial membranes for micropollutant removal. They consist of open support layers of poly(styrene sulfonate) (PSS)/poly(allylamine) (PAH) capped by denser and more selective layers of either PAH/poly(acrylic acid) (PAA) or PAH/Nafion. Unfortunately, the structure of these asymmetric PEMs, and thus their superior membrane performance, is poorly understood. In this work, neutron reflectometry (NR) is employed to elucidate the multilayered structure and hydration of these asymmetric PEMs. NR reveals that the multilayers are indeed asymmetric in structure, with distinct bottom and top multilayers when air-dried and when solvated. The low hydration of the top [PAH/Nafion] multilayer, together with the low water permeance of comparable [PAH/Nafion]-capped PEM membranes, demonstrate that it is a reduction in hydration that makes these separation layers denser and more selective. In contrast, the [PAH/PAA] capping multilayers are more hydrated than the support [PSS/PAH] layers, signifying that, here, densification of the separation layer occurs through a decrease in the mesh size (or effective pore size) of the top layer due to the higher charge density of the PAH/PAA couple compared to the PSS/PAH couple. The [PAH/PAA] and [PAH/Nafion] separation layers are extremely thin (∼4.5 and ∼7 nm, respectively), confirming that these asymmetric PEM membranes have some of the thinnest separation layers ever achieved.

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refnx: neutron and X-ray reflectometry analysis in Python

Abstract: The refnx Python modules for neutron and X-ray reflectometry data analysis are introduced. A sample analysis illustrates a Bayesian approach using a Markov-chain Monte Carlo algorithm to understand the confidence in the fit parameters.

Cited by 137 publications

References 23 publications

BornAgain: software for simulating and fitting grazing-incidence small-angle scattering

BornAgain: software for simulating and fitting grazing-incidence small-angle scattering

Assessing molecular simulation for the analysis of lipid monolayer reflectometry

Structure and Hydration of Asymmetric Polyelectrolyte Multilayers as Studied by Neutron Reflectometry: Connecting Multilayer Structure to Superior Membrane Performance

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