The exceptional magnetic properties of superparamagnetic iron oxide nanoparticles (SPIONs) make them promising materials for biomedical applications like hyperthermia, drug targeting and imaging. Easy preparation of SPIONs with the controllable, well-defined properties is a key factor of their practical application. In this work, we report a simple synthesis of Ho-doped SPIONs by the co-precipitation route, with controlled size, shape and magnetic properties. To investigate the influence of the ions ratio on the nanoparticles’ properties, multiple techniques were used. Powder X-ray diffraction (PXRD) confirmed the crystallographic structure, indicating formation of an Fe3O4 core doped with holmium. In addition, transmission electron microscopy (TEM) confirmed the correlation of the crystallites’ shape and size with the experimental conditions, pointing to critical holmium content around 5% for the preparation of uniformly shaped grains, while larger holmium content leads to uniaxial growth with a prism shape. Studies of the magnetic behaviour of nanoparticles show that magnetization varies with changes in the initial Ho3+ ions percentage during precipitation, while below 5% of Ho in doped Fe3O4 is relatively stable and sufficient for biomedicine applications. The characterization of prepared nanoparticles suggests that co-precipitation is a simple and efficient technique for the synthesis of superparamagnetic, Ho-doped SPIONs for hyperthermia application.

The multipole model (MM) uses an aspherical approach to describe electron density and can be used to interpret data from X-ray diffraction in a more accurate manner than using the spherical approximation. The MATTS (multipolar atom types from theory and statistical clustering) data bank gathers MM parameters specific for atom types in proteins, nucleic acids, and organic molecules. However, it was not fully understood how the electron density of particular atoms responds to their surroundings and which factors describe the electron density in molecules within the MM. In this work, by applying clustering using descriptors available in the MATTS data bank, that is, topology and multipole parameters, we found the topology features with the biggest impact on the multipole parameters: the element of the central atom, the number of first neighbors, and planarity of the group. The similarities in the spatial distribution of electron density between and within atom type classes revealed distinct and unique atom types. The quality of existing types can be improved by adding better parametrization, definitions, and local coordinate systems. Future development of the MATTS data bank should lead to a wider range of atom types necessary to construct the electron density of any molecule.

One of the kinds of information gained from high resolution (sub-atomic) structures is the observation that electron density parameters are transferable between atoms having similar chemical topology. This stimulated creation of databases of multipolar pseudoatoms (Invariom [1], ELMAM2 [2], MATTS -successor of UBDB [3], etc.) and their applications in (a) structure refinements on standard (atomic) resolution data for small-molecule crystals, and (b) electrostatic properties and non-covalent bonding characterisations for macromolecules.Transferable Aspherical Atom Model (TAAM) of scattering built from a pseudoatom database proved to be advantageous in refining the structure on X-ray diffraction (XRD) data compared to the Independent Atom model (IAM) [4], leading to better fit of the model to the data and improved localization of hydrogen atoms. We have recently showed [5] that also for small-molecule 3D electron diffraction (3D ED) data, a better model-to-data fit and more accurate structures should be expected from TAAM.To improve its usability, we further extended the MATTS bank to cover 98% of atoms found in all the structures deposited in the Cambridge Structural Database [6] composed of chemical elements like C, H, N, O, P, S, F, Cl and/or Br. It is planned that the remaining 1% will be covered by the more general atom types resulting from multidimensional cluster analysis. Some benefits of TAAM over IAM refinements were also reported for macromolecular XRD data of 0.9 Å resolution and better [7]. As most macromolecular crystals diffract to lower resolutions, we recently moved our investigation towards near-atomic resolutions. We quantified the differences between the macromolecular electron density Fourier maps obtained with TAAM and IAM, calculated with a resolution of 1.8 Å. We did the same for electrostatic potential maps, a key property in the context of 3D ED. TAAM refinements affect not only the positions of the atoms, but also the atomic displacement parameters (ADPs) [8]. ADPs appears to be less resolution dependent with TAAM than with IAM. With IAM, ADPs increased for XRD and decreased for 3D ED by about 30%, when the resolution was reduced from 0.6 Å to 0.8 Å [5]. From modified Wilson plots we recently predicted, and then verified by TAAM refinements on macromolecular XRD or 3D ED data, what will happen with ADPs (B-factors) with a further resolution worsening, up to 1.8 Å.All the above helps to understand if there will be any benefits of TAAM refinements on lower than atomic resolutions.