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The onset of plasticity in a single crystal C60 fullerite was investigated by nanoindentation on the (111) crystallographic plane. The transition from elastic to plastic deformation in a contact was observed as pop-in events on loading curves. The respective resolved shear stresses were computed for the octahedral slip systems ⟨011¯¯¯⟩{111}, supposing that their activation resulted in the onset of plasticity. A finite element analysis was applied, which reproduced the elastic loading until the first pop-in, using a realistic geometry of the Berkovich indenter blunt tip. The obtained estimate of the C60 theoretical shear strength was about 1/11 of the shear modulus on {111} planes.
A detailed calorimetric study on an epoxy-based nanocomposite system was performed employing bisphenol A diglycidyl ether (DGEBA) cured with diethylenetriamine (DETA) as the polymer matrix and taurine-modified MgAL layered double hydroxide (T-LDH) as nanofiller. The -NH2 group of taurine can react with DGEBA improving the interaction of the polymer with the filler. The combined X-ray scattering, and electron microscopy data showed that the nanocomposite has a partially exfoliated morphology. Calorimetric studies were performed with conventional DSC, temperature modulated DSC (TMDSC) and fast scanning calorimetry (FSC) in the temperature modulated approach (TMFSC) to investigate the vitrification and molecular mobility in dependence of the filler concentration. First, TMDSC and NMR were used to estimate the amount of the rigid amorphous fraction which consists of immobilized polymer segments at the nanoparticle surface. It was found to be 40 wt% for the highest filler concentration, indicating that the interface dominates the overall macroscopic properties and behavior of the material to a great extent. Second, the relaxation rates of the α-relaxation obtained by TMDSC and TMFSC were compared with the thermal and dielectric relaxation rates measured by static FSC. The investigation revealed that the system shows two distinct α-relaxation processes. Furthermore, also two separate vitrification mechanisms were found for a bulk network-former without geometrical confinement as also confirmed by NMR. This was discussed in terms of the intrinsic spatial heterogeneity on a molecular scale, which becomes more pronounced with increasing nanofiller content.
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.
The minimum information requirements needed to guarantee high-quality surface Analysis data of nanomaterials are described with the aim to provide reliable and traceable Information about size, shape, elemental composition and surface chemistry for risk assessment approaches.
The widespread surface analysis methods electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectrometry (SIMS) were considered. The complete analysis sequence from sample preparation, over measurements, to data analysis and data format for reporting and archiving is outlined. All selected methods are used in surface analysis since many years so that many aspects of the analysis (including (meta)data formats) are already standardized. As a practical analysis use case, two coated TiO2 reference nanoparticulate samples, which are available on the Joint Research Centre (JRC) repository, were selected. The added value of the complementary analysis is highlighted based on the minimum information requirements, which are well-defined for the analysis methods selected. The present paper is supposed to serve primarily as a source of understanding of the high standardization level already available for the high-quality data in surface analysis of nanomaterials as reliable input for the nanosafety community.
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.
The fluorolytic sol–gel synthesis is applied with the intention to obtain two different types of core–shell nanoparticles, namely, SrF2–CaF2 and CaF2–SrF2. In two separate fluorination steps for core and shell formation, the corresponding metal lactates are reacted with anhydrous HF in ethylene glycol. Scanning transmission electron microscopy (STEM) and dynamic light scattering (DLS) confirm the formation of particles with mean dimensions between 6.4 and 11.5 nm. The overall chemical composition of the particles during the different reaction steps is monitored by quantitative Al Kα excitation X-ray photoelectron spectroscopy (XPS). Here, the formation of stoichiometric metal fluorides (MF2) is confirmed, both for the core and the final core–shell particles. Furthermore, an in-depth analysis by synchrotron radiation XPS (SR-XPS) with tunable excitation energy is performed to confirm the core–Shell character of the nanoparticles. Additionally, Ca2p/Sr3d XPS intensity ratio in-Depth profiles are simulated using the software Simulation of Electron Spectra for Surface Analysis (SESSA). In principle, core–shell like particle morphologies are formed but without a sharp interface between calcium and strontium containing phases.
Surprisingly, the in-depth chemical distribution of the two types of nanoparticles is equal within the error of the experiment. Both comprise a SrF2-rich core domain and CaF2-rich shell domain with an intermixing zone between them. Consequently, the internal morphology of the final nanoparticles seems to be independent from the synthesis chronology.
Iron oxide nanoparticles gain increasing attention due to their broad industrial use. However, safety concerns exist since their effects on human cells are still under investigation. The presence of iron oxide nanoparticles in the food pigment E172 has been shown recently. Here, we studied four iron oxide nanoparticles, one food pigment E172 and the ionic control FeSO4 regarding dissolution in biological media, uptake and transport, and cellular effects in vitro in human intestinal Caco-2 and HepaRG hepatocarcinoma cells. The iron oxide nanoparticles passed the gastrointestinal passage without dissolution and reached the intestine in the form of particles. Minor uptake was seen into Caco-2 cells but almost no transport to the basolateral site was detected for any of the tested particles. HepaRG cells showed higher particle uptake. Caco-2 cells showed no alterations in reactive oxygen species production, apoptosis, or mitochondrial membrane potential, whereas two particles induced apoptosis in HepaRG cells, and one altered mitochondrial membrane potential at non-cytotoxic concentrations. No correlation between physicochemical particle characteristics and cellular effects was observed, thus emphasizing the Need for case-by-case assessment of iron oxide nanoparticles.
Nanomaterials and nanoparticles are finding applications across a wide range of technology sectors, from medicine and food to transportation and construction. In order to assess these new materials for potential risks to health and the environment, they need to be well-characterised. The measurement of constituent nanoparticle size, shape, and size distribution are important factors for the risk evaluation process.
EMPIR project Improved traceability chain of nanoparticle size measurements (17NRM04, nPSize) is working to assess a range of traceable nanoparticle measurement approaches, including Scanning Electron Microscopy (also in Transmission Mode), Atomic Force Microscopy and Small Angle X-ray Scattering, and deliver improved calibration methods to users. For the techniques under investigation, physical models of their response to a range of nanoparticle types are developed. Validated reference materials will also be used for an inter-comparison of measurement systems, with an evaluation of the associated measurement uncertainty. With project contributions to standards development work, manufacturers will be better placed to assess the human and environmental risks posed by nanomaterials across a whole range of products.
We demonstrate the potential of time-resolved luminescence spectroscopy for the straightforward assessment and in situ monitoring of the stability of upconversion nanocrystals (UCNPs). Therefore, we prepared hexagonal NaYF4:Yb3+,Er3+ UCNPs with various coatings with a focus on phosphonate ligands of different valency, using different ligand exchange procedures, and studied their dissolution behaviour in phosphate-buffered saline (PBS) dispersions at 20 °C and 37 °C with various analytical methods. The amount of the released UCNPs constituting fluoride ions was quantified by potentiometry using a Fluoride ion-sensitive electrode and particle disintegration was confirmed by transmission electron microscopy studies of the differently aged UCNPs. In parallel, the luminescence features of the UCNPs were measured with special emphasis on the lifetime of the sensitizer emission to demonstrate its suitability as Screening parameter for UCNP stability and changes in particle composition. The excellent correlation between the changes in luminescence lifetime and fluoride concentration highlights the potential of our luminescence lifetime method for UCNP stability screening and thereby indirect monitoring of the release of potentially hazardous fluoride ions during uptake and dissolution in biological systems. Additionally, the developed in situ optical method was used to distinguish the dissolution dynamics of differently sized and differently coated UCNPs.