Probing spin waves in Co3O4 nanoparticles for magnonics applications.

The magnetic properties of spinel nanoparticles can be controlled by synthesizing particles of a specific shape and size. The synthesized nanorods, nanodots and cubic nanoparticles have different crystal planes selectively exposed on the surface. The surface effects on the static magnetic properties are well documented, while their influence on spin waves dispersion is still being debated. Our ability to manipulate spin waves using surface and defect engineering in magnetic nanoparticles is the key to designing magnonic devices. We synthesized cubic and spherical nanoparticles of a classical antiferromagnetic material Co3O4 to study the shape and size effects on their static and dynamic magnetic proprieties. Using a combination of experimental methods, we probed the magnetic and crystal structures of our samples and directly measured spin wave dispersions using inelastic neutron scattering. We found a weak, but unquestionable, increase in exchange interactions for the cubic nanoparticles as compared to spherical nanoparticle and bulk powder reference samples. Interestingly, the exchange interactions in spherical nanoparticles have bulk-like properties, despite a ferromagnetic contribution from canted surface spins.

Active learning-assisted neutron spectroscopy with log-Gaussian processes.

Neutron scattering experiments at three-axes spectrometers (TAS) investigate magnetic and lattice excitations by measuring intensity distributions to understand the origins of materials properties. The high demand and limited availability of beam time for TAS experiments however raise the natural question whether we can improve their efficiency and make better use of the experimenter's time. In fact, there are a number of scientific problems that require searching for signals, which may be time consuming and inefficient if done manually due to measurements in uninformative regions. Here, we describe a probabilistic active learning approach that not only runs autonomously, i.e., without human interference, but can also directly provide locations for informative measurements in a mathematically sound and methodologically robust way by exploiting log-Gaussian processes. Ultimately, the resulting benefits can be demonstrated on a real TAS experiment and a benchmark including numerous different excitations.

Understanding near-surface polymer dynamics by a combination of grazing-incidence neutron scattering and virtual experiments.

Neutron spin-echo spectroscopy is a unique experimental method for the investigation of polymer dynamics. The combination of neutron spin-echo spectroscopy with grazing-incidence geometry (GINSES) opens the possibility to probe the dynamics of soft-matter materials in the vicinity of the solid substrate in the time range up to 100 ns. However, the usage of the GINSES technique has some peculiarities and, due to the novelty of the method and complexity of the scattering geometry, difficulties in further data analysis occur. The current work discusses how virtual experiments within the distorted-wave Born approximation using the BornAgain software can improve GINSES data treatment and aid the understanding of polymer dynamics in the vicinity of the solid surface. With two examples, poly(N-isopropyl acrylamide) brushes and poly(ethylene glycol) microgels on Si surfaces, the simulation as well as the application of the simulation to the GINSES data analysis are presented. The approach allowed a deeper insight to be gained of the background effect and scattering contribution of different layers.

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

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 non-functional and functional requirements. The web site https://www.bornagainproject.org/ provides further documentation.

Self assembled monolayer of silica nanoparticles with improved order by drop casting.

This paper reports on the formation of large area, self assembled, highly ordered monolayers of stearyl alcohol grafted silica nanospheres of ≈50 nm diameter on a silicon substrate based on the drop-casting method. Our novel approach to achieve improved order uses stearyl alcohol as an assistant by adding it to the colloidal NanoParticle (NP) dispersion from which the monolayers are formed. Additionally, a heat treatment step is added, to melt the stearyl alcohol in the monolayer and thereby give the particles more time to further self-assemble, leading to additional improvement in the monolayer quality. The formation of the monolayers is significantly affected by the concentration of the NPs and the stearyl alcohol, the volume of the drop as well as the time of the heat treatment. A high surface coverage and uniform monolayer film of SiO2 NPs is achieved by appropriate control of the above-mentioned preparation parameters. Structural characterization of the obtained SiO2 NP monolayer was done locally by Scanning Electron Microscopy (SEM), and globally by X-ray reflectivity (XRR) and grazing incidence small-angle X-ray scattering (GISAXS), where the data was reproduced by simulation within the Distorted Wave Born Approximation (DWBA). In conclusion, our modified drop-casting method is a simple, inexpensive method, which provides highly ordered self-assembled monolayers of silica particles, if combined with a compatible additive and a heat treatment step. This method might be more general and also applicable to different particles after finding an appropriate additive.

Relationship between Structure and Fluctuations of Lipid Nonlamellar Phases Deposited at the Solid-Liquid Interface.

The structure and dynamics of nanostructure films formed by mixtures of soy phosphatidylcholine and glycerol dioleate at the silicon-aqueous interface were studied by grazing incidence neutron spin echo spectroscopy (GINSES), specular and off-specular neutron reflectometry, and small-angle X-ray diffraction. Reverse hexagonal (HII) and micellar cubic phase (Fd3m) layers at the solid-liquid interface have been identified with neutron reflectometry measurements. A preferred orientation of the liquid crystalline (LC) domains was observed only for the anisotropic HII phase. The size of the LC domains was found to be about 1 micrometer as estimated from the width of the diffraction peaks. GINSES revealed that the cubic phase forms rather rigid films. In comparison, the HII film was more flexible, appearing as a modified undulation spectrum of the cylinders due to the interaction with the substrate.

Development of metal nanocluster ion source based on dc magnetron plasma sputtering at room temperature.

A simple and cost effective nanocluster ion source for the deposition of size selected metal nanocluster has been developed based on the dc magnetron discharge (including pulsed dc discharge). The most important and interesting feature of this cluster source is that it is working at room temperature, cooled by chilled water during the experiment. There is no extraction unit in this device and the cluster streams flow only due to the pressure gradient from source chamber to substrate via quadrupole mass filter. It has provision of multiple substrate holders in the deposition chamber, which can be controlled manually. The facility consists of quadrupole mass filter (QMF 200), which can select masses in the range of 2-125 000 atoms depending on the target materials, with a constant mass resolution (M/DeltaM approximately 25). The dc magnetron discharge at a power of about 130 W with Ar as feed/buffer gas was used to produce the Cu nanocluster in an aggregation tube and deposited on Si (100) wafer temperature.