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Valuable emissive properties of organic fluorophores have become indispensable analytical tools in biophotonics, but frequently suffer from low solubilities and radiationless deactivation in aqueous media, that is, in biological ambience as well. In this report, nanoscaled dyeclay hybrids based on laponite, Na0.7{(Li0.3Mg5.5)[Si8O20(OH)4]}, are taken advantage of to solubilize neutral dyes, which are natively not encountered in water. Previously reported efficiency and solubility bottlenecks of such hybrids can to a large extent be overcome by comparably simple chemical measures, as demonstrated here for two prominent examples, the fluorescent dyes Nile Red and Coumarin 153. On controlled co-adsorption of small bifunctional quaternary ammonium ions (Me3N+C2H5OH and Me3N+C2H5NH2) we observed an outright efficiency boost by an order of magnitude, and a 30-fold brightness gain. Even at higher concentrations, transparency and stability of the hybrid dispersions are retained, rendering them useful for employment as optically functional nanoparticles in bioassays and beyond.
In this work, sample losses of silver nanoparticles (Ag NPs) in asymmetrical flow field-flow fractionation (AF4) have been systematically investigated with the main focus on instrumental conditions like focusing and cross-flow parameters as well as sample concentration and buffer composition. Special attention was drawn to the AF4 membrane. For monitoring possible silver depositions on the membrane, imaging laser ablation coupled to inductively coupled plasma mass spectrometry (LA-ICP-MS) was used. Our results show that the sample residue on the membrane was below 0.6% of the total injected amount and therefore could be almost completely avoided at low sample concentrations and optimized conditions. By investigation of the AF4 flows using inductively coupled plasma mass spectrometry (ICP-MS), we found the recovery rate in the detector flow under optimized conditions to be nearly 90%, while the cross-flow, slot-outlet flow and purge flow showed negligible amounts of under 0.5%. The analysis of an aqueous ionic Ag standard solution resulted in recovery rates of over 6% and the ionic Ag content in the sample was found to be nearly 8%. Therefore, we were able to indicate the ionic Ag content as the most important source of sample loss in this study.
A user-friendly open-source Monte Carlo regression package (McSAS) is presented, which structures the analysis of small-angle scattering (SAS) using uncorrelated shape-similar particles (or scattering contributions). The underdetermined problem is solvable, provided that sufficient external information is available. Based on this, the user picks a scatterer contribution model (or 'shape') from a comprehensive library and defines variation intervals of its model parameters. A multitude of scattering contribution models are included, including prolate and oblate nanoparticles, core-shell objects, several polymer models, and a model for densely packed spheres. Most importantly, the form-free Monte Carlo nature of McSAS means it is not necessary to provide further restrictions on the mathematical form of the parameter distribution; without prior knowledge, McSAS is able to extract complex multimodal or odd-shaped parameter distributions from SAS data. When provided with data on an absolute scale with reasonable uncertainty estimates, the software outputs model parameter distributions in absolute volume fraction, and provides the modes of the distribution (e.g. mean, variance etc.). In addition to facilitating the evaluation of (series of) SAS curves, McSAS also helps in assessing the significance of the results through the addition of uncertainty estimates to the result. The McSAS software can be integrated as part of an automated reduction and analysis procedure in laboratory instruments or at synchrotron beamlines.
We studied the magnetic resonance imaging liver contrast agent Resovist by a variety of magnetic measurement techniques, in order to understand the physical mechanism of their high magnetic particle imaging (MPI) performance, wirh a focus on the size-dependent contributions of the MPI signal. To this end, we used asymmetric flow field-flow fractionation to separate Resovist into a set of fractions with defined hydrodynamic diameters. The individual fractions were magnetically characterized by static magnetization and magnetorelaxometry measurements to obtain the corresponding effective magnetic anisotropy and effective size distribution parameters. In addition, the MPI performance of each fraction was assessed by magnetic particle spectroscopy. We observed an MPI signal gain of about 100% with respect to their iron amount for the best fraction. Relating these finding to the results from magnetic characterization provides more insight into mechanisms of MPI performance of Resovist. This knowledge may help to improve the design of novel MPI tracers.
Advances in scanning electron microscopy (SEM) enable the high-resolution imaging of single nanoparticles (NPs) with sizes well below 10 nm. The SEM analysis in transmission mode (T-SEM) of NPs on thin film supports has many benefits when compared to the analysis of NPs on bulk substrates. The enhanced material (mass - thickness) contrast of the T-SEM imaging mode is well suited for in-depth and, particularly valuable, to very accurate, traceable, lateral dimensional measurements of NPs. Compared to samples prepared on bulk substrates, T-SEM with energy dispersive X-ray spectroscopy (EDS) achieves a drastically improved spatial resolution of the emitted X-rays. The poor signal-to-noise ratio of the X-ray spectra emitted by a single nanoparticle (NP) can be improved by the use of high-sensitivity (high collection solid angle) silicon drift (SDD), energy-dispersive X-ray spectrometers (EDS). The EDS spectral imaging of a single NP with a spatial resolution below 10 nm has become possible. This is demonstrated by means of various examples of nanostructures. Advanced data processing of T-SEM/EDS results sets the stage for the automated classification of NPs by feature analysis. This method combines the detection of morphological structures of interest by image processing of T-SEM micrographs with the chemical classification by EDS.
Due to the recent widespread application of nanomaterials to biological systems, a careful consideration of their physiological impact is required. This demands an understanding of the complex processes at the bio–nano interface. Therefore, a comprehensive and accurate characterization of the material under physiological conditions is crucial to correlate the observed biological impact with defined colloidal properties. As promising candidates for biomedical applications, two SiO2-based nanomaterial systems were chosen for extensive size characterization to investigate the agglomeration behavior under physiological conditions. To combine the benefits of different characterization techniques and to compensate for their respective drawbacks, transmission electron microscopy, dynamic light scattering and asymmetric flow field-flow fractionation were applied. The investigated particle systems were (i) negatively charged silica particles and (ii) poly(organosiloxane) particles offering variable surface modification opportunities (positively charged, polymer coated). It is shown that the surface properties primarily determine the agglomeration state of the particles and therefore their effective size, especially under physiological conditions. Thus, the biological identity of a nanomaterial is clearly influenced by differentiating surface properties.
Particle size modality in bi-modal iron oxide suspensions was resolved by exploiting complex ac-susceptibility (ACS), small angle X-ray scattering (SAXS) and photon cross-correlation spectroscopy. To explain dynamic magnetic response of bi-modal suspensions, the Debye model was expanded to a linear superposition form allowing for the contribution of both particle fractions. This modified and adopted model is able to resolve the bi-modal particle size distributions. The SAXS curves of mono- and bi-modal suspensions were fitted well using a Monte Carlo simulation scheme, allowing the detection of bi-modal particle size distributions with high precision.
Resovist® originally developed as a clinical liver contrast agent for Magnetic Resonance Imaging exhibits also an outstanding performance as a tracer in Magnetic Particle Imaging (MPI). In order to study the physical mechanism of the high MPI performance of Resovist®, we applied asymmetric flow fieldflow fractionation (A4F) and static magnetic fractionation (SMF) to separate Resovist® into a set of fractions with defined size classes. As A4F based on an elution method separates MNP according to their hydrodynamic size, SMF fractionates a particle distribution by its magnetic moment. The obtained fractions of both separation techniques were then magnetically characterized by magnetorelaxometry measurements to extract the corresponding effective magnetic anisotropy and hydrodynamic size distribution parameters. Additionally, the MPI performance of each fraction was assessed using magnetic particle spectroscopy. With both separation techniques fractions (normalized to their iron amount) an MPI signal gain of a factor of two could be obtained, even though the distribution of effective anisotropy and hydrodynamic size were significantly different. Relating these findings to the results from magnetic characterization allows for a better understanding of the underlying mechanisms of MPI performance of Resovist®. This knowledge may help to improve the design of novel MPI tracers and development of separation methods.
The design of comparatively simple and modularly configurable artificial systems able to communicate through the exchange of chemical messengers is, to the best of our knowledge, an unexplored field. As a proof-of-concept, we present here a family of nanoparticles that have been designed to communicate with one another in a hierarchical manner. The concept involves the use of capped mesoporous silica supports in which the messenger delivered by a first type of gated nanoparticle is used to open a second type of nanoparticle, which delivers another messenger that opens a third group of gated nanoobjects. We believe that the conceptual idea that nanodevices can be designed to communicate with one another may result in novel applications and will boost further advances towards cooperative systems with complex behavior as a result of the communication between simple abiotic individual components.
High-priority industrial nanomaterials like SiO2, TiO2, and Ag are being characterized on a systematic basis within the framework of the EU FP7 research project NanoValid. Silica nanoparticles from an industrial source have been analyzed by Auger electron spectroscopy. Point, line, and map spectra were collected. Material specific and methodological aspects causing the special course of Auger line scan signals will be discussed.