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Large-scale nanoimprinted metasurfaces based on silicon photonic crystal slabs were produced and coated with a NaYF4:Yb3+/Er3+ upconversion nanoparticle (UCNP) layer. UCNPs on these metasurfaces yield a more than 500-fold enhanced upconversion emission compared to UCNPs on planar surfaces. It is also demonstrated how the optical response of the UCNPs can be used to estimate the local field energy in the coating layer. Optical simulations using the finite element method validate the experimental results and the calculated spatial three-dimensional field Energy distribution helps us to understand the emission enhancement mechanism of the UCNPs closely attached to the metasurface. In addition, we analyzed the spectral shifts of the resonances for uncoated and coated metasurfaces and metasurfaces submerged in water to enable a prediction of the optimum layer thicknesses for different excitation wavelengths, paving the way to applications such as electromagnetic field sensors or bioassays.
In the blossoming field of Cd-free semiconductor quantum dots (QDs), ternary I–III–VI QDs have received increasing attention due to the ease of the environmentally friendly synthesis of high-quality materials in water, their high photoluminescence (PL) Quantum yields (QYs) in the red and near infrared (NIR) region, and their inherently low toxicity. Moreover, their oxygen-insensitive long PL lifetimes of up to several hundreds of nanoseconds close a gap for applications exploiting the compound-specific parameter PL lifetime. To overcome the lack of reproducible synthetic methodologies and to enable a design-based control of their PL properties, we assessed and modelled the synthesis of high-quality MPA-capped AgInS2/ZnS (AIS/ZnS) QDs. Systematically refined Parameters included reaction time, temperature, Ag:In ratio, S:In ratio, Zn:In ratio, MPA:In ratio, and pH using a design-of-experiment approach.
Guidance for the optimization was provided by mathematical models developed for the application-relevant PL parameters, maximum PL wavelength, QY, and PL lifetime as well as the elemental composition in terms of Ag:In:Zn ratio. With these experimental data-based models, MPA:In and Ag:In ratios and pH values were identified as the most important synthesis parameters for PL Control and an insight into the connection of these parameters could be gained. Subsequently, the experimental conditions to synthetize QDs with tunable emission and high QY were predicted. The excellent agreement between the predicted and experimentally found PL features confirmed the reliability of our methodology for the rational design of high quality AIS/ZnS QDs with defined PL features.
This approach can be straightforwardly extended to other ternary and quaternary QDs and to doped QDs.
Aqueous Dispersions of Polypropylene: Toward Reference Materials for Characterizing Nanoplastics
(2023)
Microplastics and nanoplastics pollute the natural environment all over the world, but the full extent of the hazards posed by this waste is unclear. While research on microplastics is well advanced, little work has been done on nanoplastics. This discrepancy is mainly due to the lacking ability to detect nanoplastics in biologically and environmentally relevant matrices. Nanoplastics reference materials can help the development of suitable methods for identifying and quantifying nanoplastics in nature. The aim is to synthesize nanoplastics made from one of the most commonly used plastics, namely polypropylene. An easy way to produce long-term stable aqueous dispersions of polypropylene nanoparticles (nano polypropylene) is reported. The nanoplastic particles, prepared by mechanical breakdown, show a mean hydrodynamic diameter of D h = 180.5 ± 5.8 nm and a polydispersity index of PDI = 0.084 ± 0.02. No surfactant is needed to obtain dispersion which is stable for more than 6 months. The colloidal stability of the surfactant-free nano polypropylene dispersions is explained by their low zeta potential of 𝜻 = −43 ± 2 mV.
The complex effects of nanoparticles on a thermosetting material based on an anhydride cured DGEBA/Boehmite nanocomposite with different particle concentrations is considered. A combination of X-ray scattering, calorimetry, including fast scanning calorimetry as well as temperature modulated calorimetry and dielectric spectroscopy, was employed to study the structure, the vitrification kinetics and the molecular dynamics of the nanocomposites. For the first time in the literature for an epoxy-based composite a detailed analysis of the X-ray data was carried out. Moreover, the unfilled polymer was found to be intrinsically heterogeneous, showing regions with different crosslinking density, indicated by two separate dynamic glass transitions. The glass transition temperature decreases with increasing nanoparticle concentration, resulting from a change in the crosslinking density. Moreover, on the one hand, for nanocomposites the incorporation of nanofiller increased the number of mobile segments for low nanoparticle concentrations, due to the altered crosslinking density. On the other hand, for higher loading degrees the number of mobile segments decreased, resulting from the formation of an immobilized interphase (RAF). The simultaneous mobilization and immobilization of the segmental dynamics cannot be separated unambiguously. Taking the sample with highest number of mobile segments as reference state it was possible to estimate the amount of RAF.
MIKE III apparatus tests were conducted to investigate the minimum ignition energy (MIE) of coal dusts in air and O2/CO2 atmospheres with and without small amount of CH4/H2. The O2 mole fraction (XO2) in the gas mixtures varied from 21% to 50% with the CH4/H2 mole fraction from 0 to 2%. Experimental result showed that MIE of coal dusts significantly decreases even by three orders of magnitude in mJ with increasing XO2 and the addition of CH4/H2. Compared with CH4, H2 had a relatively strong promotion effect on the spark ignition of coal dusts. The inhibiting effect of CO2 was found to be much stronger than N2, but this inhibiting effect of CO2 could be eliminated by 9% increment of XO2. The effect on MIE of coal dusts thus followed by the order: 9% increment of XO2 > CO2 replacing N2 > 2% CH4 or H2 addition. Moreover, two empirical models were used to estimate the MIE of hybrid dust-gas mixture (HMIE), and the results showed that calculated data can well reflect the promoting effect of elevated XO2 and flammable gas addition, and the inhibiting effect of inert gas
Modern life and global communication would not be possible without technologically tailored thin films; they are omnipresent in daily life applications. In most cases, the films are deposited entirely at the carrying substrates in a specific processing step of the device or sample. In some cases, however, removal or modification must be performed locally, i.e., site-controlled and material selective through an additional laser processing step. For that ultrashort laser pulses with durations in the femtosecond and picosecond range can provide unique advantages and capabilities in industrially scalable schemes. This article reviews the current state of the research and corresponding industrial transfer related to the structuring of thin films by ultrashort pulsed lasers. It focuses on the pertinent historic developments, reveals the relevant physical and chemical effects, explores the ultimate limits, and discusses selected industrial and scientific applications.
The application and benefits of Semantic Web Technologies (SWT) for managing, sharing, and (re-)using of research data are demonstrated in implementations in the field of Materials Science and Engineering (MSE). However, a compilation and classification are needed to fully recognize the scattered published works with its unique added values. Here, the primary use of SWT at the interface with MSE is identified using specifically created categories. This overview highlights promising opportunities for the application of SWT to MSE, such as enhancing the quality of experimental processes, enriching data with contextual information in knowledge graphs, or using ontologies to perform specific queries on semantically structured data. While interdisciplinary work between the two fields is still in its early stages, a great need is identified to facilitate access for nonexperts and develop and provide user-friendly tools and workflows. The full potential of SWT can best be achieved in the long term by the broad acceptance and active participation of the MSE community. In perspective, these technological solutions will advance the field of MSE by making data FAIR. Data-driven approaches will benefit from these data structures and their connections to catalyze knowledge generation in MSE.
The development of the microbiologically influenced corrosion ( MIC ) -specific inductively coupled plasma-time of flight-mass spectrometry ( ICP-ToF-MS ) analytical method presented here, in combination with the investigation of steel-MIC interactions, contributes significantly to progress in instrumental MIC analysis. For this, a MIC-specific staining procedure was developed, which ensures the analysis of intact cells. It allows the analysis of archaea at a single cell level, which is extremely scarce compared to other well-characterized organisms. The detection method revealed elemental selectivity for the corrosive methanogenic strain Methanobacterium -affiliated IM1. Hence, the possible uptake of individual elements from different steel samples was investigated and results showed the cells responded at a single-cell level to the different types of supplemented elements and displayed the abilities to uptake chromium, vanadium, titanium, cobalt, and molybdenum from solid metal surfaces. The methods developed and information obtained will be used in the future to elucidate underlying mechanisms, compliment well-developed methods, such as SEM-EDS, and develop novel material protection concepts.
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 early stages of corrosion of Fe-Cr-model alloys (2 and 9 % Cr) were investigated after exposure at 650 °C in0.5 % SO2containing gas by electron backscattered diffraction (EBSD) and transmission electron microscopy(TEM). The impact of the grain orientation of the base alloy on the orientation relations of the corrosion productsis presented. After 2 min–5 min exposure the formation of a multi-layered corrosion zone was discovered. Aclear orientation relationship between ferrite and the (Fe,Cr)3O4 spinel could be demonstrated. The obtainedresults show the importance of the grain orientation on oxidation resistance.