6 Materialchemie
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In this work, we describe a simple solvothermal route for the synthesis of Eu3+-doped gadolinium orthovanadate nanocrystals (Eu:GdVO4−PAA) functionalized with poly(acrylic)acid (PAA), that are applicable as cell labeling probes for multimodal cellular imaging. The Eu3+ doping of the vanadate matrix provides optical functionality, due to red photoluminescence after illumination with UV light. The Gd3+ ions of the nanocrystals reduce the T1 relaxation time of surrounding water protons, allowing these nanocrystals to act as a positive MRI contrast agent with a r1 relaxivity of 1.97 mM−1 s−1. Low background levels of Eu3+, Gd3+, and V5+ in biological systems make them an excellent label for elemental microscopy by Laser Ablation (LA)-ICP-MS. Synthesis resulted in polycrystalline nanocrystals with a hydrodynamic diameter of 55 nm and a crystal size of 36.7 nm, which were further characterized by X-ray diffraction (XRD), photoluminescence spectroscopy (PL) and transmission electron microscopy (TEM). The multifunctional nanocrystals were subsequently used for intracellular labeling of both human adipose-derived stem cells (MSCs) and A549 (adenocarcinomic human alveolar basal epithelial) cells.
Structural modularity of polymer frameworks is a key advantage of covalent organic polymers, however, only C, N, O, Si and S have found their way into their building blocks so far. Here, we expand the toolbox available to polymer and materials chemists by one additional nonmetal, phosphorus. Starting with a building block that contains a λ⁵‐phosphinine (C₅P) moiety, we evaluate a number of polymerisation protocols, finally obtaining a π‐conjugated, covalent phosphinine‐based framework (CPF‐1) via Suzuki‐Miyaura coupling. CPF‐1 is a weakly porous polymer glass (72.4 m2 g‐1 N2 BET at 77 K) with green fluorescence (λmax 546 nm) and extremely high thermal stability. The polymer catalyzes hydrogen evolution from water under UV and visible light irradiation without the need for additional co‐catalyst at a rate of 33.3 μmol h‐¹ g‐¹. Our results demonstrate for the first time the incorporation of the phosphinine motif into a complex polymer framework. Phosphinine‐based frameworks show promising electronic and optical properties that might spark future interest in their applications in light‐emitting devices and heterogeneous catalysis.
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.
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.
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 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.
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.
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.
Luminescent solar concentrators (LSC) allow to obtain renewable energy from building integrated photovoltaic systems. As promising efficient and long-term stable LSC fluorophores semiconductor nanocrystals like Quantum dots (QDs) with size and composition tunable optoelectronic properties have recently emerged. The most popular II/VI or IV/VI semiconductor QDs contain, however, potentially hazardous cadmium or lead ions, which is a bottleneck for commercial applications. A simple aqueous based, microwaveassisted synthesis for environmentally friendly and highly emissive AgInS2/ ZnS QDs is developed using 3-mercaptopropionic acid (MPA) and glutathione (GSH) and their incorporation into polylaurylmethacrylate (PLMA) polymer slabs integrable in LSC devices (10.4 × 10.4 × 0.2 cm3, G = 12.98).
With this simple approach, optical power efficiencies (OPE) of 3.8% and 3.6% and optical quantum efficiencies (OQE) of 24.1% and 27.4% are obtained, which are among the highest values yet reported.
Core–shell nanoparticles have attracted much attention in recent years due to their unique properties and their increasing importance in many technological and consumer products. However, the chemistry of nanoparticles is still rarely investigated in comparison to their size and morphology. In this review, the possibilities, limits, and challenges of X-ray photoelectron spectroscopy (XPS) for obtaining more insights into the composition, thickness, and homogeneity of nanoparticle coatings are discussed with four examples: CdSe/CdS quantum dots with a thick coating and a small core; NaYF4-based upconverting nanoparticles with a large Yb-doped core and a thin Er-doped coating; and two types of polymer nanoparticles with a poly(tetrafluoroethylene) core with either a poly(methyl methacrylate) or polystyrene coating. Different approaches for calculating the thickness of the coating are presented, like a simple numerical modelling or a more complex simulation of the photoelectron peaks. Additionally, modelling of the XPS background for the investigation of coating is discussed. Furthermore, the new possibilities to measure with varying excitation energies or with hard-energy X-ray sources (hard-energy X-ray photoelectron spectroscopy) are described. A discussion about the sources of uncertainty for the determination of the thickness of the coating completes this review.