Prof. Dr. Tobias Kraus

Non-polar magnetic nanoparticles agglomerate upon cooling. This process is followed by in situ small angle X-ray scattering to assess structural properties of the emerging agglomerates. On the length scale of a few particle diameters, no differences are found between the agglomerates of small (d = 12 nm) and large (d = 22 nm) nanoparticles. Hard-sphere like random packing with a local packing fraction of η = 0.4 is seen. On larger length scales, small particles form compact superstructures, while large particles arrange into agglomerates that resemble chain-like structures in SAXS. This can be explained by directed magnetic dipole interactions that dominate larger particles, while isotropic van der Waals interaction governs the agglomeration of smaller particles.

Abstract Different colloidal particle characterization methods are examined for their suitability to determine the particle size distribution of particles extracted from steels. Microalloyed steels are dissolved to extract niobium and titanium carbonitride particles that are important for the mechanical properties of these steels. Such particles have sizes ranging from several nanometers to hundreds of nanometers depending on the precipitation stage during the thermomechanically controlled rolling process. The size distribution of the particles is analyzed by dynamic light scattering (DLS), analytical ultracentrifugation (AUC), and hollow fiber flow field-flow fractionation (HF5) and compared to data obtained for reference particles as well as data from electron microscopy, the standard sizing technique used in metallurgy today. AUC and HF5 provide high-quality size distributions, average over large particle numbers that enables statistical analysis, and yield useful insights for alloy design; however, DLS fails due to a lack of resolution. Important aspects in the conversion and comparison of size distributions obtained for broadly distributed particle systems with different measurement principles and the role of surfactants used in sample preparation are discussed.

Charged nanoparticles can behave as large ions or as small colloids. Their interaction with multivalent ions has now been shown to reflect this dichotomy, providing new paths to large, self-assembled nanoparticle superstructures.

Transparent electronic devices are opening up unprecedented possibilities in display technology and virtual reality. For some of these applications, it would be advantageous if optical transparency could be combined with stretchability. Of course, all portable electronic devices need an energy source, which is ideally integrated in the form of a battery and must therefore fulfill the same physical properties. However, it is quite challenging to develop a battery in which all the components (electrodes, current collectors, separator/electrolyte, and packaging) are transparent and stretchable. Here we present the development of a transparent and stretchable full zinc ion battery comprising two electrodes deposited on a polydimethylsiloxane (PDMS) substrate and a polyacrylamide (PAM) hydrogel electrolyte. The resulting stretchable battery shows a high transmittance of 72.6% and 64.7% at 550 nm without and with 50% strain, respectively. The battery provides a capacity of 176.5 mA h g–1 after 120 cycles under varying strain conditions up to 50%. The battery’s multifunctionality, linking energy storage with stretchability and transparency, makes it attractive for powering future transparent and stretchable electronics.

Asymmetrical flow field-flow fractionation (AF4) hyphenated with inductively coupled plasma-mass spectrometry (ICP-MS) has been widely used to characterize metal containing particles. This study demonstrates the advantages of coupling AF4 with ICP-time-of-flight mass spectrometry (ICP-TOFMS) in standard and single particle modes to determine size distribution, elemental composition, and number concentration of composite particles. The coupled system was used to characterize two complex particle mixtures. The first mixture consisted of particles extracted from micro-alloyed steels with two size populations of different elemental composition. The second mixture consisted of particles extracted from soil spiked with various engineered nanoparticles (ENPs). The equivalent hydrodynamic sizes of individual micro-alloyed steel particles were up to 6 times larger than the sizes determined by single particle (sp)-ICP-TOFMS. The larger AF4 sizes were attributed to the presence of a surface coating, which is not reflected in the core size determined by sp-ICP-TOFMS. Two particle populations could not be separated by AF4 due to their broad size distributions but were resolved by sp-ICP-TOFMS using their unique elemental signatures. Multi-angle light scattering and ICP-TOFMS signals of soil suspensions increased with the spiked ENP concentrations. However, only after conducting full element screening and single particle fingerprinting by ICP-TOFMS could this increase be attributed to enhanced extraction efficiency of natural particles and the risk for false conclusions be eliminated. In this study, we describe how AF4 coupled to ICP-TOFMS can be applied to study complex samples of inorganic particles which contain organic compounds.

The controlled agglomeration of superparamagnetic iron oxide nanoparticles (SPIONs) was used to rapidly switch their magnetic properties. Small-angle X-ray scattering (SAXS) and dynamic light scattering showed that tailored iron oxide nanoparticles with phase-changing organic ligands shells agglomerate at temperatures between 5 °C and 20 °C. We observed the concurrent change in magnetic properties using magnetic particle spectroscopy (MPS) with a temporal resolution at the order of seconds and found reversible switching of magnetic properties of SPIONs by changing their agglomeration state. The non-linear correlation between magnetization amplitude from MPS and agglomeration degree from SAXS data indicated that the agglomerates’ size distribution affected magnetic properties.

Electro-physiological sensing devices are becoming increasingly common in diverse applications. However, designing such sensors in compact form factors and for high-quality signal acquisition is a challenging task even for experts, is typically done using heuristics, and requires extensive training. Our work proposes a computational approach for designing multi-modal electro-physiological sensors. By employing an optimization-based approach alongside an integrated predictive model for multiple modalities, compact sensors can be created which offer an optimal trade-off between high signal quality and small device size. The task is assisted by a graphical tool that allows to easily specify design preferences and to visually analyze the generated designs in real-time, enabling designer-in-the-loop optimization. Experimental results show high quantitative agreement between the prediction of the optimizer and experimentally collected physiological data. They demonstrate that generated designs can achieve an optimal balance between the size of the sensor and its signal acquisition capability, outperforming expert generated solutions.

Ionic liquids are modern liquid materials with potential and actual implementation in many advanced technologies. They combine many favourable and modifiable properties but have a major inherent drawback compared to molecular liquids – slower dynamics. In previous studies we found that the dynamics of ionic liquids are significantly accelerated by the introduction of multiple ether side chains into the cations. However, the origin of the improved transport properties, whether as a result of the altered cation conformation or due to the absence of nanostructuring within the liquid as a result of the higher polarity of the ether chains, remained to be clarified. Therefore, we prepared two novel sets of methylammonium based ionic liquids; one set with three ether substituents and another set with three butyl side chains, in order to compare their dynamic properties and liquid structures. Using a range of anions, we show that the dynamics of the ether-substituted cations are systematically and distinctly accelerated. Liquefaction temperatures are lowered and fragilities increased, while at the same time cation–anion distances are slightly larger for the alkylated samples. Furthermore, pronounced liquid nanostructures were not observed. Molecular dynamics simulations demonstrate that the origin of the altered properties of the ether substituted ionic liquids is primarily due to a curled ether chain conformation, in contrast to the alkylated cations where the alkyl chains retain a linear conformation. Thus, the observed structure–property relations can be explained by changes in the geometric shape of the cations, rather than by the absence of a liquid nanostructure. Application of quantum chemical calculations to a simplified model system revealed that intramolecular hydrogen-bonding is responsible for approximately half of the stabilisation of the curled ether-cations, whereas the other half stems from non-specific long-range interactions. These findings give more detailed insights into the structure–property relations of ionic liquids and will guide the development of ionic liquids that do not suffer from slow dynamics.

Atom probe tomography (APT) provides sub-nm resolution in the analysis of complex industrial steels. It can resolve the carbonitride precipitates in Nb-Ti microalloyed high-strength low-alloy (HSLA) steels that strongly affect material performance and illuminate the complex precipitation sequence before and during the thermo-mechanical controlled process (TMCP). However, the precipitate concentration is low in HSLA steels during austenite conditioning, especially at temperatures > 850 °C, so that the probability of detecting precipitates via APT is below 5%. Here, we demonstrate two encapsulation-based approaches that increase the precipitate concentration in the APT sample volume sufficiently to enable the analysis of sparse precipitates. The first method is based on metallographic etching and direct targeting of precipitates in the steel. A focused ion beam was used to mark precipitation sites. Encapsulation with nickel-phosphorus (Ni-P) enabled localized APT and increased the yield by a factor of 10. The second method relies on the chemical extraction of precipitates and subsequent encapsulation in a silicon oxide (SiOx) network at a very high particle density. Analysis of tips cut from the encapsulated particles increased the yield by a factor of >15. We discuss and compare the spatial and chemical accuracy obtained in the analysis of pure Nb-, Ti- and mixed Nb-Ti carbonitrides.

The organization of plasmonic nanoparticles (NPs) determines the strength and polarization dependence of coupling of their surface plasmons. In this study, plasmon coupling of spherical Au NPs with an average diameter of 15 nm was investigated in shape-memory polymer films before and after mechanical stretching and then after thermally driving shape recovery. Clusters of Au NPs form when preparing the films that exhibit strong plasmon coupling. During stretching, a significant polarization-dependent response develops, where the optical extinction maximum corresponding to the surface plasmon resonance is redshifted by 19 nm and blueshifted by 7 nm for polarization parallel and perpendicular to the stretching direction, respectively. This result can be explained by non-uniform stretching on the nanoscale, where plasmon coupling increases parallel to the shear direction as Au NPs are pulled into each other during stretching. The polarization dependence vanishes after shape recovery, and structural characterization confirms the return of isotropy consistent with complete nanoscale recovery of the initial arrangement of Au NPs. Simulations of the polarized optical responses of Au NP dimers at different interparticle spacings establish a plasmon ruler for estimating the average interparticle spacings within the experimental samples. An investigation of the temperature-dependent recovery behavior demonstrates an application of these materials as optical thermal history sensors.