6 Materialchemie
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Two sets of polystyrene nanoparticles (PSNPs) with comparable core sizes but different carboxyl group densities were made and separated using asymmetric flow field flow fractionation (AF4), capillary electrophoresis (CE), and the off-line hyphenation of both methods. Our results revealed the significant potential of two-dimensional off-line AF4-CE hyphenation to improve the separation and demonstrated for the first time, the applicability of CE to determine the functional group density of nanoparticles (NPs). Compared to the result acquired with conductometric titration, the result obtained with synthesized 100 nm sized PSNPs revealed only a slight deviation of 1.7%. Commercial 100 nm sized PSNPs yielded a deviation of 4.6 %. For 60 nm sized PSNPs, a larger deviation of 10.6 % between both methods was observed, which is attributed to the lower separation resolution.
Controlling thickness and tightness of surface passivation shells is crucial for many applications of core–shell nanoparticles (NP). Usually, to determine shell thickness, core and core/shell particle are measured individually requiring the availability of both nanoobjects. This is often not fulfilled for functional nanomaterials such as many photoluminescent semiconductor quantum dots (QD) used for bioimaging, solid state lighting, and display technologies as the core does not show the applicationrelevant functionality like a high photoluminescence (PL) quantum yield, calling for a whole nanoobject approach. By combining high-resolution transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS), a novel whole nanoobject approach is developed representatively for an ultrabright oleic acid-stabilized, thick shell CdSe/CdS QD with a PL quantum yield close to unity. The size of this spectroscopically assessed QD, is in the range of the information depth of usual laboratory XPS. Information on particle size and monodispersity were validated with dynamic light scattering (DLS) and small angle X-ray scattering (SAXS) and compared to data derived from optical measurements. In addition to demonstrating the potential of this novel whole nanoobject approach for determining architectures of small nanoparticles, the presented results also highlight challenges faced by different sizing and structural analysis methods and method-inherent uncertainties.
Outer membrane lipopolysaccharides (LPS) play a crucial role in determining attachment behavior and pathogenicity of bacteria. The aim of this study was to develop a simple procedure for anchoring bacterial lipopolysaccharides to polystyrene (PS) microparticles as a model system for in situ attachment studies. By using a swellcapture methodology, commercially available LPS of Pseudomonas aeruginosa (strain ATCC 27316 serotype 10.22) was anchored onto PS microparticles in a proof-of-concept study. A detailed chemical and morphological characterization has proven the success of LPS incorporation. It was shown that the coverage and structure of the LPS film was concentration dependent. The procedure can easily be adapted to LPS of other bacterial strains to generate a synthetic model toolkit for attachment studies.
Polyether and -ester urethanes (PU) were exposed to artificial weathering at 40 °C and artificial UV radiation in a weathering chamber. In 3 parallel exposures, humidity was varied between dry, humid, and wet conditions. Material alteration was investigated by various analytical techniques like size exclusion chromatography
(SEC), liquid chromatography-infrared spectroscopy (LC-FTIR), thermal-desorption gas chromatography-mass spectrometry (TD-GC-MS), fluorescence mapping and dynamic mechanical analysis (DMA). Our results show that depending on the weathering conditions, different degradation effects can be observed. By means of SEC an initial strong decrease of the molar masses and a broadening of the mass distributions was found. After a material dependent time span this was followed by a plateau where molar mass changes were less significant. A minor moisture-dependent degradation effect was only found for polyester PU. Fluorescence measurements on two materials revealed an increase in the luminescence intensity upon weathering process reaching a saturation level after about 500 h. The changes in the optical properties observed after different exposure conditions and times were very similar. The TD-GC-MS data showed the fate of the stabilizers and antioxidant in the course of weathering. LC-FTIR measurements revealed a change in peak intensities and the ratio of urethane and carbonyl bands.
Surface-functionalized polymer beads encoded with molecular luminophores and nanocrystalline emitters such as semiconductor nanocrystals, often referred to as quantum dots (QDs), or magnetic nanoparticles are broadly used in the life sciences as reporters and carrier beads. Many of these applications require a profound knowledge of the chemical nature and total number of their surface functional groups (FGs), that control bead charge, colloidal stability, hydrophobicity, and the interaction with the environment and biological systems. For bioanalytical applications, also the
number of groups accessible for the subsequent functionalization with, e.g., biomolecules or targeting ligands is relevant. In this study, we explore the influence of QD encoding on the amount of carboxylic acid (COOH) surface FGs of 2 μm polystyrene microparticles (PSMPs). This is done for frequently employed oleic acid and oleylamine stabilized, luminescent core/shell CdSe QDs and two commonly used encoding procedures. This included QD addition during bead formation by a thermally induced polymerization reaction and a post synthetic swelling procedure. The accessible number of COOH groups on the surface of QD-encoded and pristine beads was quantified by two colorimetric assays, utilizing differently sized reporters and electrostatic and covalent interactions. The results were compared to the total number of FGs obtained by a conductometric titration and Fourier transform infrared spectroscopy (FTIR). In addition, a comparison of the impact of QD and dye encoding on the bead surface chemistry was performed. Our results demonstrate the influence of QD encoding and the QD-encoding strategy on the number of surface FG that is ascribed to an interaction of the QDs with the carboxylic acid groups on the bead surface. These findings are of considerable relevance for applications of nanoparticle-encoded beads and safe-by-design concepts for nanomaterials.
We studied the dissolution behavior of β NaYF4:Yb(20%), Er(2%) UCNP of two different sizes in biologically relevant media i.e., water (neutral pH), phosphate buffered saline (PBS), and Dulbecco’s modified Eagle medium (DMEM) at different temperatures and particle concentrations. Special emphasis was dedicated to assess the influence of different surface functionalizations, particularly the potential of mesoporous and microporous silica shells of different thicknesses for UCNP stabilization and protection. Dissolution was quantified electrochemically using a fluoride ion selective electrode (ISE) and by inductively coupled plasma optical emission spectrometry (ICP OES). In addition, dissolution was monitored fluorometrically. These experiments revealed that a thick microporous silica shell drastically decreased dissolution. Our results also underline the critical influence of the chemical composition of the aqueous environment on UCNP dissolution. In DMEM, we observed the formation of a layer of adsorbed molecules on the UCNP surface that protected the UCNP from dissolution and enhanced their fluorescence. Examination of this layer by X ray photoelectron spectroscopy (XPS) and mass spectrometry (MS) suggested that mainly phenylalanine, lysine, and glucose are adsorbed from DMEM. These findings should be considered in the future for cellular toxicity studies with UCNP and other nanoparticles and the design of new biocompatible surface coatings.
In der klinischen Diagnostik werden für zytometrische Messverfahren bereits eine Reihe von Reagenzien eingesetzt zur Markierung von Antikörper eingesetzt, um die Detektion von Biomarkern mittels Fluoreszenz- oder Flugzeitmassenspektrometrie zu ermöglichen.
Seit kurzem ist auch eine Imaging Mass Cytometry Kombination direkt erhältlich, wodurch der Nachweis von Biomarkern in Gewebeschnitten erreicht werden kann. Dazu wird eine Kopplung von Laser Ablation und induktiv gekoppeltem Plasma Massenspektrometrie eingesetzt, wobei ähnlich der Massenzytometrie, zuvor Antikörper mit Metallen markiert, und im Anschluss mit dem Gewebeschnitt inkubiert werden. Durch die hohe Ortsauflösung können die Biomarker lokalisiert, und zukünftig vielleicht auch quantifiziert werden.
Insbesondere Lanthanide eignen sich als Markierungsmetalle, da sie einen niedrigen Untergrund und chemisch ähnliches Verhalten zueinander aufweisen. Allein durch diese Elemente können bereits etwa 15 Parameter unterschieden werden, was durch isotopenreine Standards weiter gesteigert werden kann.
Vom Markierungsgrad abhängig werden unterschiedlich viele Metalle am Antikörper gebunden, und beeinflussen so die Sichtbarkeit im ICP-MS. Nanopartikel könnten daher eine deutliche Steigerung der Sensitivität bewirken. GdVO4 Nanokristalle scheinen bisher sehr vielversprechend und bieten neben multiparametrischen Anwendungen auch Multimodalität.
Die Synthese der Nanokristalle zeigte hohe Homogenität und Reproduzierbarkeit in Partikelgröße in der Zusammensetzung. Ein erstes Experiment mit einer Zellkultur konnte bereits die effiziente Markierung der Zellen unter Beweis stellen, wobei durch hohe Signalstärke auch subzelluläre Auflösung in der LA-ICP-MS erreicht werden konnte.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from scanning electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. We compare the segmentation masks obtained with our suggested workflow qualitatively and quantitatively to state-of-the-art methods using various metrics. Finally, we used the segmentation masks for automatically extracting particle size distributions from the SEM images of TiO2 particles, which were in excellent agreement with particle size distributions obtained manually but could be obtained in a fraction of the time.
This dataset accompanies the following publication, first published in Scientific Reports (www.nature.com/articles/s41598-021-84287-6):
B. Ruehle, J. Krumrey, V.-D. Hodoroaba, Scientific Reports, Workflow towards Automated Segmentation of Agglomerated, Non-Spherical Particles from Electron Microscopy Images using Artificial Neural Networks, DOI: 10.1038/s41598-021-84287-6
It contains electron microscopy micrographs of TiO2 particles, the corresponding segmentation masks, and their classifications into different categories depending on their visibility/occlusion. Please refer to the publication and its supporting information for more details on the acquisition and contents of the dataset, as well as the GitHub repository at https://github.com/BAMresearch/automatic-sem-image-segmentation
In this contribution different ways are explored with the aim to generate suitable training data for ‘non-ideal’ samples using various approaches, e.g., computer-generated images or unsupervised learning algorithms such as generative adversarial networks (GANs). We used these data to train simple CNNs to produce segmentation masks of SEM images and tested the trained networks on real SEM images of complex nanoparticle samples. The novel use of CNN for the automated analysis of the size of nanoparticles of complex shape and with a high degree of agglomeration has proved to be a promising tool for the evaluation of particle size distribution on a large number of constituent particles. Further development and validation of the preliminary model, respectively larger training and validation data sets are necessary.
We present a workflow for obtaining fully trained artificial neural networks that can perform automatic particle segmentations of agglomerated, non-spherical nanoparticles from electron microscopy images “from scratch”, without the need for large training data sets of manually annotated images. This is achieved by using unsupervised learning for most of the training dataset generation, making heavy use of generative adversarial networks and especially unpaired image-to-image translation via cycle-consistent adversarial networks. The whole process only requires about 15 minutes of hands-on time by a user and can typically be finished within less than 12 hours when training on a single graphics card (GPU). After training, SEM image analysis can be carried out by the artificial neural network within seconds, and the segmented images can be used for automatically extracting and calculating various other particle size and shape descriptors.
Neuartige Materialien, die bekannte (Werk-)Stoffe mit neuen Funktionalitäten ausstatten, spielen eine zunehmend wichtige Rolle im Bereich der Materialforschung und -prüfung. Das Spektrum neuartiger Materialien reicht von der gezielten Oberflächenfunktionalisierung und -strukturierung makroskopischer Materialien, dünnen Beschichtungen bis hin zu mikro- und nanoskaligen Kompositmaterialien und funktionalen Materialien an der Schnittstelle zur Biologie, Biotechnologie, nachhaltige Energiespeicherung und Sensorik. Dabei bieten neuartige Materialien die Chance, Werkstoffe und Produkte mit erweiterter oder verbesserter Funktionalität zu erhalten und Sicherheit bereits im Designprozess zu berücksichtigen. Durch dieses breite Anwendungsspektrum und die Herausforderungen, die solche Materialien für die Sicherheit in Chemie und Technik mit sich bringen, sind diese in allen Themenfeldern der BAM repräsentiert (Material, Analytical Sciences, Energie, Infrastruktur und Umwelt).
Die Aufgaben der BAM erstrecken sich dabei von der Herstellung von Referenzmaterialien für Industrie, Forschung und Regulation, über die Erstellung von standardisierten Referenzverfahren für nachhaltige Messungen im Umwelt- und Lebenswissenschaftsbereich bis hin zur Bereitstellung von belastbaren und zitierbaren Referenzdaten. Durch die genaue Charakterisierung neuartiger Materialien können potentiell problematische Substanzen identifiziert und deren Risiken besser abgeschätzt werden. In diesem Beitrag werden einige aktuelle Beispiele aus diesen Bereichen vorgestellt.
The use of inorganic lanthanide-doped upconversion nanoparticles (UCNP) in bioimaging and cellular studies requires biocompatible particles. One possible cause of UCNP toxicity is the release of potentially harmful fluoride and lanthanide ions as revealed by dilution studies in aqueous environments, particularly under high dilution conditions. To address this issue, suitable surface coatings preventing such effects in combination with fast screening methods suited for online monitoring and in situ analyses are desired.
Here we present systematic studies of differently sized β-NaYF4:Yb,Er UCNP stabilized with different surface coatings and hydrophilic ligands varying in binding strength to the particle surface in various aqueous environments at different temperatures and UCNP concentrations. The concentration of the fluoride and lanthanide ions released upon particle dissolution was quantified electrochemically with a fluoride ion-sensitive electrode and inductively coupled plasma optical emission spectrometry (ICP-OES) and monitored fluorometrically, thereby exploiting the sensitivity of the upconversion luminescence to changes in size and surface chemistry. Moreover, changes in surface chemistry were determined with X-Ray photoelectron spectroscopy (XPS). Based upon our results, we could derive optimum screening parameters for UCNP stability studies and determine conditions and coating procedures and ligands for enhancing UCNP stability in aqueous environments.
A brief perspective of BAM on nanocarriers is presented including examples with special emphasis on the characterization of such materials and underlying challenges. In this respect, also ongoing activities at BAM on different types of core/shell nanomaterials and related systems are briefly summarized.
Engineered nanoparticles (NPs) with various chemical compositions and surface functionalities are routinely fabricated for industrial applications such as medical diagnostics, drug delivery, sensing, catalysis, energy conversion and storage, opto-electronics, and information storage which improve the quality of life and European prosperity. NP function, performance, interaction with biological species, and environmental fate are largely determined by their surface functionalities. Standardized repeatable surface characterization methods are therefore vital for quality control of NPs, and to meet increasing concerns regarding their safety. Therefore, industry, regulatory agencies, and policymakers need validated traceable measurement methods and reference materials. This calls for fit-for-purpose, validated, and standardized methods, and reference data and materials on the surface chemistry of engineered NPs. Here, we present a concept for the development of such standardized measurement protocols utilizing method cross-validation and interlaboratory comparisons (ILCs) with emphasis on both advanced measurement methods such as quantitative Nuclear Magnetic Resonance (qNMR), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) and cost-efficient, non-surface specific methods like optical assays and electrochemical titration methods.
Quaternary semiconductor nanocrystals like AgInS2-ZnS solid solution quantum dots (QDs) are a highly promising material for material science and biomedical applications due to their tunable photoluminescence (PL), their high quantum yields (QY), and their low cytotoxicity1. A red shift of the PL into the NIR and SWIR region could further increase their application potential. Copper doping has been proven to be a suitable approach for bathochromically shifting the PL of QDs2. The synthesis of copper doped AgInS2-ZnS QDs from a single-source-precursor should enable an easily scalable synthesis with high reproducibility.
Organic/inorganic mixtures were prepared from ordinary Portland cement (OPC), water (w/c 0.22), a fluorescent dye in aqueous solution (stable at alkaline pH; BAM-I), and two different comb shape polycarboxylates (PCEs), i.e., high charge (PCE-HC) and low charge (PCE-LC), respectively. Rheological and calorimetric measurements were performed prior to optical studies in order to select PCE concentrations. Absorption and fluorescence spectroscopy of the system OPC + BAM-I (CBAM-I) revealed maxima of dye BAM-I located at 645 nm and 663 nm, respectively. In presence of PCE-HC and PCE-LC, these mixtures displayed a small red shift in reflectance and a faster decrease in intensity compared to studies with CBAM-I; however, only slight differences were observed between the different PCEs. With time, all systems exhibited a decrease in intensity of BAM-I in absorption/reflectance and emission. This could be caused by dye adsorption and possibly decomposition when in contact with cement particles or hydration products.