Filtern
Erscheinungsjahr
- 2017 (3)
Dokumenttyp
Sprache
- Englisch (3)
Referierte Publikation
- ja (3)
Schlagworte
- SAXS (2)
- Iron oxide (1)
- Nanoparticle (1)
- Parameter Study (1)
- Post-welding Imperfections (1)
- Reference materials (1)
- Residual Stresses (1)
- Small-angle X-ray scattering (1)
- Small-angle x-ray scattering (1)
- Stability (1)
Welding is the most important joining technique and offers the advantage of customizable plate thicknesses. On the other hand, welding causes residual stresses and deformations influencing the load carrying capacity. Their consideration in the design requires simple and fast models. Though welding simulation has contributed to accurately access to these values nowadays, their application to large components remains still in a less practicable range. Nevertheless, many studies emphasized the need to make corrections in recently available simplified models. Especially the influence of residual stresses seems somewhat overestimated in many cases if comparing conventional structural steel S355 and high-strength steel S690. In the age of computer-aided design, an improved procedure to implement weld-inducted imperfections appears overdue. This will be presented in two parts. The first part illustrates the potential influence of post-welding imperfections exemplified for weak axis buckling in comparison with the general method in accordance with Eurocode 3. Residual stresses and initial crookedness were varied systematically in order to produce a scatter band of capacities. An approach to characterize the borders of these imperfections was untertaken before that. The excessive scattering of reduction factors for the load bearing capacity demonstrates the importance of these variables. Results were finally evaluated against advanced simulation models which will be further detailed in part two of this contribution.
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
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.