| 1. |
- Andersen, Henrik L., et al.
(författare)
-
Local and long-range atomic/magnetic structure of non-stoichiometric spinel iron oxide nanocrystallites
- 2021
-
Ingår i: IUCrJ. - 2052-2525. ; 8, s. 33-45
-
Tidskriftsartikel (refereegranskat)abstract
- Spinel iron oxide nanoparticles of different mean sizes in the range 10-25 nm have been prepared by surfactant-free up-scalable near- and super-critical hydrothermal synthesis pathways and characterized using a wide range of advanced structural characterization methods to provide a highly detailed structural description. The atomic structure is examined by combined Rietveld analysis of synchrotron powder X-ray diffraction (PXRD) data and time-of-flight neutron powder-diffraction (NPD) data. The local atomic ordering is further analysed by pair distribution function (PDF) analysis of both X-ray and neutron total-scattering data. It is observed that a non-stoichiometric structural model based on a tetragonal γ-Fe2O3 phase with vacancy ordering in the structure (space group P43212) yields the best fit to the PXRD and total-scattering data. Detailed peak-profile analysis reveals a shorter coherence length for the superstructure, which may be attributed to the vacancy-ordered domains being smaller than the size of the crystallites and/or the presence of anti-phase boundaries, faulting or other disorder effects. The intermediate stoichiometry between that of γ-Fe2O3 and Fe3O4 is confirmed by refinement of the Fe/O stoichiometry in the scattering data and quantitative analysis of Mössbauer spectra. The structural characterization is complemented by nano/micro-structural analysis using transmission electron microscopy (TEM), elemental mapping using scanning TEM, energy-dispersive X-ray spectroscopy and the measurement of macroscopic magnetic properties using vibrating sample magnetometry. Notably, no evidence is found of a Fe3O4/γ-Fe2O3 core-shell nanostructure being present, which had previously been suggested for non-stoichiometric spinel iron oxide nanoparticles. Finally, the study is concluded using the magnetic PDF (mPDF) method to model the neutron total-scattering data and determine the local magnetic ordering and magnetic domain sizes in the iron oxide nanoparticles. The mPDF data analysis reveals ferrimagnetic collinear ordering of the spins in the structure and the magnetic domain sizes to be ∼60-70% of the total nanoparticle sizes. The present study is the first in which mPDF analysis has been applied to magnetic nanoparticles, establishing a successful precedent for future studies of magnetic nanoparticles using this technique.
|
|
| 2. |
- Lo, Sheng-Han, et al.
(författare)
-
Rapid desolvation-triggered domino lattice rearrangement in a metal-organic framework
- 2020
-
Ingår i: Nature Chemistry. - : Springer Science and Business Media LLC. - 1755-4330 .- 1755-4349. ; 12:1, s. 90-97
-
Tidskriftsartikel (refereegranskat)abstract
- Topological transitions between considerably different phases typically require harsh conditions to collectively break chemical bonds and overcome the stress caused to the original structure by altering its correlated bond environment. In this work we present a case system that can achieve rapid rearrangement of the whole lattice of a metal-organic framework through a domino alteration of the bond connectivity under mild conditions. The system transforms from a disordered metal-organic framework with low porosity to a highly porous and crystalline isomer within 40s following activation (solvent exchange and desolvation), resulting in a substantial increase in surface area from 725 to 2,749m(2)g(-1). Spectroscopic measurements show that this counter-intuitive lattice rearrangement involves a metastable intermediate that results from solvent removal on coordinatively unsaturated metal sites. This disordered-crystalline switch between two topological distinct metal-organic frameworks is shown to be reversible over four cycles through activation and reimmersion in polar solvents. A disordered metal-organic framework converts into a more porous, crystalline phase within 40s following solvent exchange and desolvation. The rapid domino rearrangement of the whole lattice, which involves carboxylate migration on coordinatively unsaturated metal sites, is accompanied by a substantial increase in surface area.
|
|
| 3. |
- Anker, Andy S., et al.
(författare)
-
Extracting structural motifs from pair distribution function data of nanostructures using explainable machine learning
- 2022
-
Ingår i: npj Computational Materials. - : Springer Science and Business Media LLC. - 2057-3960. ; 8:1
-
Tidskriftsartikel (refereegranskat)abstract
- Characterization of material structure with X-ray or neutron scattering using e.g. Pair Distribution Function (PDF) analysis most often rely on refining a structure model against an experimental dataset. However, identifying a suitable model is often a bottleneck. Recently, automated approaches have made it possible to test thousands of models for each dataset, but these methods are computationally expensive and analysing the output, i.e. extracting structural information from the resulting fits in a meaningful way, is challenging. Our Machine Learning based Motif Extractor (ML-MotEx) trains an ML algorithm on thousands of fits, and uses SHAP (SHapley Additive exPlanation) values to identify which model features are important for the fit quality. We use the method for 4 different chemical systems, including disordered nanomaterials and clusters. ML-MotEx opens for a type of modelling where each feature in a model is assigned an importance value for the fit quality based on explainable ML.
|
|
