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SASfit: a tool for small-angle scattering data analysis using a library of analytical expressions
(2015)
SASfit is one of the mature programs for small-angle scattering data analysis and has been available for many years. This article describes the basic data processing and analysis workflow along with recent developments in the SASfit program package (version 0.94.6). They include (i) advanced algorithms for reduction of oversampled data sets, (ii) improved confidence assessment in the optimized model parameters and (iii) a flexible plug-in system for custom user-provided models. A scattering function of a mass fractal model of branched polymers in solution is provided as an example for implementing a plug-in. The new SASfit release is available for major platforms such as Windows, Linux and MacOS. To facilitate usage, it includes comprehensive indexed documentation as well as a web-based wiki for peer collaboration and online videos demonstrating basic usage. The use of SASfit is illustrated by interpretation of the small-angle X-ray scattering curves of monomodal gold nanoparticles (NIST reference material 8011) and bimodal silica nanoparticles (EU reference material ERM-FD-102).
A user-friendly open-source Monte Carlo regression package (McSAS) is presented, which structures the analysis of small-angle scattering (SAS) using uncorrelated shape-similar particles (or scattering contributions). The underdetermined problem is solvable, provided that sufficient external information is available. Based on this, the user picks a scatterer contribution model (or 'shape') from a comprehensive library and defines variation intervals of its model parameters. A multitude of scattering contribution models are included, including prolate and oblate nanoparticles, core-shell objects, several polymer models, and a model for densely packed spheres. Most importantly, the form-free Monte Carlo nature of McSAS means it is not necessary to provide further restrictions on the mathematical form of the parameter distribution; without prior knowledge, McSAS is able to extract complex multimodal or odd-shaped parameter distributions from SAS data. When provided with data on an absolute scale with reasonable uncertainty estimates, the software outputs model parameter distributions in absolute volume fraction, and provides the modes of the distribution (e.g. mean, variance etc.). In addition to facilitating the evaluation of (series of) SAS curves, McSAS also helps in assessing the significance of the results through the addition of uncertainty estimates to the result. The McSAS software can be integrated as part of an automated reduction and analysis procedure in laboratory instruments or at synchrotron beamlines.
Healable materials could play an important role in reducing the environmental footprint of our
modern technological society through extending the life cycles of consumer products and constructions. However, as most healing processes are carried out by heat alone, the ability to heal damage generally kills the parent material’s thermal and mechanical properties. Here we
present a dynamic covalent polymer network whose thermal healing ability can be switched ‘on’ and ‘off’ on demand by light, thereby providing local control over repair while retaining the advantageous macroscopic properties of static polymer networks. We employ a photoswitchable furan-based crosslinker, which reacts with short and mobile maleimidesubstituted poly(lauryl methacrylate) chains forming strong covalent bonds while simultaneously allowing the reversible, spatiotemporally resolved control over thermally induced de- and re-crosslinking. We reason that our system can be adapted to more complex materials and has the potential to impact applications in responsive coatings, photolithography and microfabrication.
The mechanism of nanotriangle formation in multivesicular vesicles (MMV) is investigated by using time-dependent SAXS measurements in combination with UV−vis spectroscopy, light, and transmission electron microscopy. In the first time period 6.5 nm sized spherical gold nanoparticles are formed inside of the vesicles, which build up soft nanoparticle aggregates. In situ SAXS experiments show a linear increase of the volume and molar mass of nanotriangles in the second time period. The volume growth rate of the triangles is 16.1 nm3/min, and the growth rate in the vertical direction is only 0.02 nm/min. Therefore, flat nanotriangles with a thickness of 7 nm and a diameter of 23 nm are formed. This process can be described by a diffusionlimited Ostwald ripening growth mechanism. TEM micrographs visualize soft coral-like structures with thin nanoplatelets at the periphery of the aggregates, which disaggregate in the third time period into nanotriangles and spherical particles. The 16 times faster growth of nanotriangles in the lateral than that in the vertical direction is related to the adsorption of symmetry breaking components, i.e., AOT and the polyampholyte PalPhBisCarb, on the {111} facets of the gold nanoplatelets in combination with confinement effects of the vesicular template phase.
In the present study, we applied a regularized inversion method to extract the particle size, magnetic moment and relaxation-time distribution of magnetic nanoparticles from small-angle x-ray scattering (SAXS), DC magnetization (DCM) and AC susceptibility (ACS) measurements. For the measurements the particles were colloidally dispersed in water. At first approximation the particles could be assumed to be spherically shaped and homogeneously magnetized single-domain particles. As model functions for the inversion, we used the particle form factor of a sphere (SAXS), the Langevin function (DCM) and the Debye model (ACS). The extracted distributions exhibited features/peaks that could be distinctly attributed to the individually dispersed and non-interacting nanoparticles. Further analysis of these peaks enabled, in combination with a prior characterization of the particle ensemble by electron microscopy and dynamic light scattering, a detailed structural and magnetic characterization of the particles. Additionally, all three extracted distributions featured peaks, which indicated deviations of the scattering (SAXS), magnetization (DCM) or relaxation (ACS) behavior from the one expected for individually dispersed, homogeneously magnetized nanoparticles. These deviations could be mainly attributed to partial agglomeration (SAXS, DCM, ACS), uncorrelated surface spins (DCM) and/or intra-well relaxation processes (ACS). The main advantage of the numerical inversion method is that no ad hoc assumptions regarding the line shape of the extracted distribution functions are required, which enabled the detection of these contributions. We highlighted this by comparing the results with the results obtained by standard model fits, where the functional form of the distributions was a priori assumed to be log-normal shaped.
Data correction is probably the least favourite activity amongst users experimenting with small-angle X-ray scattering: if it is not done sufficiently well, this may become evident only during the data analysis stage, necessitating the repetition of the data corrections from scratch. A recommended comprehensive sequence of elementary data correction steps is presented here to alleviate the difficulties associated with data correction, both in the laboratory and at the synchrotron. When applied in the proposed order to the raw signals, the resulting absolute scattering cross section will provide a high degree of accuracy for a very wide range of samples, with its values accompanied by uncertainty estimates. The method can be applied without modification to any pinhole-collimated instruments with photon-counting direct-detection area detectors.
This paper presents the first worldwide inter-laboratory comparison of small-angle X-ray scattering (SAXS) for nanoparticle sizing. The measurands in this comparison are the mean particle radius, the width of the size distribution and the particle concentration. The investigated sample consists of dispersed silver nanoparticles, surrounded by a stabilizing polymeric shell of poly(acrylic acid). The silver cores dominate the X-ray scattering pattern, leading to the determination of their radius size distribution using (i) the generalized indirect Fourier transformation method, (ii) classical model fitting using SASfit and (iii) a Monte Carlo fitting approach using McSAS. The application of these three methods to the collected data sets from the various laboratories produces consistent mean number- and volume-weighted core radii of Rn = 2.76 (6) nm and Rv = 3.20 (4) nm, respectively. The corresponding widths of the lognormal radius distribution of the particles were σn = 0.65 (1) nm and σv = 0.71 (1) nm. The particle concentration determined using this method was 3.0 (4) g l−1 or 4.2 (7) × 10−6 mol l−1. These results are affected slightly by the choice of data evaluation procedure, but not by the instruments: the participating laboratories at synchrotron SAXS beamlines, commercial and in-house-designed instruments were all able to provide highly consistent data. This demonstrates that SAXS is a suitable method for revealing particle size distributions in the sub-20 nm region (at minimum), out of reach for most other analytical methods.
This article reports on the characterization of four superparamagnetic iron oxide nanoparticles stabilized with dimercaptosuccinic acid, which are suitable candidates for reference materials for magnetic properties. Particles p1 and p2 are single-core particles, while p3 and p4 are multi-core particles. Small-angle X-ray scattering analysis reveals a lognormal type of size distribution for the iron oxide cores of the particles. Their mean radii are 6.9 nm (p1), 10.6 nm (p2), 5.5 nm (p3) and 4.1 nm (p4), with narrow relative distribution widths of 0.08, 0.13, 0.08 and 0.12. The cores are arranged as a clustered network in the form of dense mass fractals with a fractal dimension of 2.9 in the multi-core particles p3 and p4, but the cores are well separated from each other by a protecting organic shell. The radii of gyration of the mass fractals are 48 and 44 nm, and each network contains 117 and 186 primary particles, respectively. The radius distributions of the primary particle were confirmed with transmission electron microscopy. All particles contain purely maghemite, as shown by X-ray absorption fine structure spectroscopy
The report on the results of an in vitro digestion study of silver nanoparticles in presence and absenceof food. The particles were poly(acrylic acid) stabilized ultra-small silver nanoparticles with a radius of 3.1 nm and a relative size distribution width of 0.2. As food components oil, starch, skimmed milk powderand a mixture thereof were chosen. Aggregation of the particles was quantified with small-angle X-rayscattering in terms of log-normal radii distributions. Complete aggregation of the primary particles wasdetermined in the absence of food. In contrast, the presence of oil and starch initiates a disaggregationin the intestine. Only small aggregates of 6 nm radii and aggregation numbers of 7 were found in thepresence of milk powder. It prevents primary particles from etching in the gastric and intestinal juice.Our results indicate that the silver nanoparticles can pass the digestion process in a nanoscale form butundergo a strong and food-dependent transformation in their state of aggregation.
The application of appropriate analytical techniques is essential for nanomaterial (NM) characterization. In this study, we compared different analytical techniques for NM analysis. Regarding possible adverse health effects, ionic and particulate NM effects have to be taken into account. As NMs behave quite differently in physiological media, special attention was paid to techniques which are able to determine the biosolubility and complexation behavior of NMs. Representative NMs of similar size were selected: aluminum (Al0) and aluminum oxide (Al2O3), to compare the behavior of metal and metal oxides. In addition, titanium dioxide (TiO2) was investigated. Characterization techniques such as dynamic light scattering (DLS) and nanoparticle tracking analysis (NTA) were evaluated with respect to their suitability for fast characterization of nanoparticle dispersions regarding a particle's hydrodynamic diameter and size distribution. By application of inductively coupled plasma mass spectrometry in the single particle mode (SP-ICP-MS), individual nanoparticles were quantified and characterized regarding their size. SP-ICP-MS measurements were correlated with the information gained using other characterization techniques, i.e. transmission electron microscopy (TEM) and small angle X-ray scattering (SAXS). The particle surface as an important descriptor of NMs was analyzed by X-ray diffraction (XRD). NM impurities and their co-localization with biomolecules were determined by ion beam microscopy (IBM) and confocal Raman microscopy (CRM). We conclude advantages and disadvantages of the different techniques applied and suggest options for their complementation. Thus, this paper may serve as a practical guide to particle characterization techniques.