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Optical anapoles are intriguing charge-current distributions characterized by a strong suppression of electromagnetic radiation. They originate from the destructive interference of the radiation produced by electric and toroidal multipoles. Although anapoles in dielectric structures have been probed and mapped with a combination of near- and far-field optical techniques, their excitation using fast electron beams has not been explored so far. Here, we theoretically and experimentally analyze the excitation of optical anapoles in tungsten disulfide (WS$_2$) nanodisks using Electron Energy Loss Spectroscopy (EELS) in Scanning Transmission Electron Microscopy (STEM). We observe prominent dips in the electron energy loss spectra and associate them with the excitation of optical anapoles and anapole-exciton hybrids. We are able to map the anapoles excited in the WS$_2$ nanodisks with subnanometer resolution and find that their excitation can be controlled by placing the electron beam at different positions on the nanodisk. Considering current research on the anapole phenomenon, we envision EELS in STEM to become a useful tool for accessing optical anapoles appearing in a variety of dielectric nanoresonators., 4 figures

The article addresses the local system of national assessment of foreign languages in Sweden, a contextually specific, large-scale system with a summative aim, but also a system aimed to support teachers in their continuous assessment and grading of their students’ competences. In the text, the educational context and the multifaceted nature of national assessment are described and discussed. Furthermore, based on a broad view of validity with use and consequences in focus, different, and partly interwoven, aspects of collaboration in test development are exemplified and discussed, including policy, stakeholders, and research. Special attention is given to contributions by stakeholders, in particular students and teachers. Their involvement is regarded as a central component in the test development process, not only because it widens, deepens, and further develops the competences needed, but also because it increases the possibility to affect and enhance the use of the materials for the justice and beneficence of test-takers and society at large—aspects at the heart of validity. It is emphasized that collaboration requires sensitivity and sensibility from those involved to optimize overall quality and generate reciprocal benefits for all parties.

Porous phase-separated ethylcellulose/hydroxypropylcellulose (EC/HPC) films are used to control drug transport out of pharmaceutical pellets. The films are applied on the pellets using fluidized bed spraying. The drug transport rate is determined by the structure of the porous films that are formed as the water-soluble HPC leaches out. However, a detailed understanding of the evolution of the phase-separated structure during production is lacking. Here, we have investigated EC/HPC films produced by spin-coating, which mimics the industrial manufacturing process. This work aimed to understand the structure formation and film shrinkage during solvent evaporation. The cross-sectional structure evolution was characterized using confocal laser scanning microscopy (CLSM), profilometry and image analysis. The effect of the EC/HPC ratio on the cross-sectional structure evolution was investigated. During shrinkage of the film, the phase-separated structure undergoes a transition from 3D to nearly 2D structure evolution along the surface. This transition appears when the typical length scale of the phase-separated structure is on the order of the thickness of the film. This was particularly pronounced for the bicontinuous systems. The shrinkage rate was found to be independent of the EC/HPC ratio, while the initial and final film thickness increased with increasing HPC fraction. A new method to estimate part of the binodal curve in the ternary phase diagram for EC/HPC in ethanol has been developed. The findings of this work provide a good understanding of the mechanisms responsible for the morphology development and allow tailoring of thin EC/HPC films structure for controlled drug release.

While molecular doping is ubiquitous in all branches of organic electronics, little is known about the spatial distribution of dopants, especially at molecular length scales. Moreover, a homogeneous distribution is often assumed when simulating transport properties of these materials, even though the distribution is expected to be inhomogeneous. In this study, electron tomography is used to determine the position of individual molybdenum dithiolene complexes and their three-dimensional distribution in a semiconducting polymer at the sub-nanometre scale. A heterogeneous distribution is observed, the characteristics of which depend on the dopant concentration. At 5 mol% of the molybdenum dithiolene complex, the majority of the dopant species are present as isolated molecules or small clusters up to five molecules. At 20 mol% dopant concentration and higher, the dopant species form larger nanoclusters with elongated shapes. Even in case of these larger clusters, each individual dopant species is still in contact with the surrounding polymer. The electrical conductivity first strongly increases with dopant concentration and then slightly decreases for the most highly doped samples, even though no large aggregates can be observed. The decreased conductivity is instead attributed to the increased energetic disorder and lower probability of electron transfer that originates from the increased size and size variation in dopant clusters. This study highlights the importance of detailed information concerning the dopant spatial distribution at the sub-nanometre scale in three dimensions within the organic semiconductor host. The information acquired using electron tomography may facilitate more accurate simulations of charge transport in doped organic semiconductors. Funding Agencies|Swedish Research Council [2016-06146, 2018-03824]; National Science Foundation through the DMREF program [DMR-1729737]

Vanadium oxide on anatase nanoparticles develop atomic scale differences in structure and oxidation state, revealed by in situ transmission electron microscopy.

III–V compound nanowires have electrical and optical properties suitable for a wide range of applications, including photovoltaics and photodetectors. Furthermore, their elastic nature allows the use of strain engineering to enhance their performance. Here we have investigated the effect of mechanical strain on the photocurrent and the electrical properties of single GaAs nanowires with radial p-i-n junctions, using a nanoprobing setup. A uniaxial tensile strain of 3% resulted in an increase in photocurrent by more than a factor of 4 during NIR illumination. This effect is attributed to a decrease of 0.2 eV in nanowire bandgap energy, revealed by analysis of the current–voltage characteristics as a function of strain. This analysis also shows how other properties are affected by the strain, including the nanowire resistance. Furthermore, electron-beam-induced current maps show that the charge collection efficiency within the nanowire is unaffected by strain measured up to 0.9%.

Two-dimensional nanomaterials, as one of the most widely used substrates for energy storage devices, have achieved great success in terms of the overall capacity. Despite the extensive research effort dedicated to this field, there are still major challenges concerning capacitance modulation and stability of the 2D materials that need to be overcome. Doping of the crystal structures, pillaring methods and 3D structuring of electrodes have been proposed to improve the material properties. However, these strategies are usually accompanied by a significant increase in the cost of the entire material preparation process and also a lack of the versatility for modification of the various types of the chemical structures. Hence in this work, versatile, cheap, and environmentally friendly method for the enhancement of the electrochemical parameter of various MXene-based supercapacitors (Ti

Semiconductor–superconductor hybrids are widely used to realize complex quantum phenomena, such as topological superconductivity and spins coupled to Cooper pairs. Accessing new, exotic regimes at high magnetic fields and increasing operating temperatures beyond the state-of-the-art requires new, epitaxially matched semiconductor–superconductor materials. One challenge is the generation of favourable conditions for heterostructural formation between materials with the desired properties. Here we harness an increased knowledge of metal-on-semiconductor growth to develop InAs nanowires with epitaxially matched, single-crystal, atomically flat Pb films with no axial grain boundaries. These highly ordered heterostructures have a critical temperature of 7 K and a superconducting gap of 1.25 meV, which remains hard at 8.5 T, and therefore they offer a parameter space more than twice as large as those of alternative semiconductor–superconductor hybrids. Additionally, InAs/Pb island devices exhibit magnetic field-driven transitions from a Cooper pair to single-electron charging, a prerequisite for use in topological quantum computation. Semiconductor–Pb hybrids potentially enable access to entirely new regimes for a number of different quantum systems. Semiconductor–superconductor hybrids are used for realizing complex quantum phenomena but are limited in the accessible magnetic field and temperature range. Now, hybrid devices made from InAs nanowires and epitaxially matched, single-crystal, atomically flat Pb films present superior characteristics, doubling the available parameter space.

Phase-separated polymer films are commonly used as coatings around pharmaceutical oral dosage forms (tablets or pellets) to facilitate controlled drug release. A typical choice is to use ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. When an EC/HPC film is in contact with water, the leaching out of the water-soluble HPC phase produces an EC film with a porous network through which the drug is transported. The drug release can be tailored by controlling the structure of this porous network. Imaging and characterization of such EC porous films facilitates understanding of how to control and tailor film formation and ultimately drug release. Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography is a well-established technique for high-resolution imaging, and suitable for this application. However, for segmenting image data, in this case to correctly identify the porous network, FIB-SEM is a challenging technique to work with. In this work, we implement convolutional neural networks for segmentation of FIB-SEM image data. The data are acquired from three EC porous films where the HPC phases have been leached out. The three data sets have varying porosities in a range of interest for controlled drug release applications. We demonstrate very good agreement with manual segmentations. In particular, we demonstrate an improvement in comparison to previous work on the same data sets that utilized a random forest classifier trained on Gaussian scale-space features. Finally, we facilitate further development of FIB-SEM segmentation methods by making the data and software used open access.Drug release from pharmaceutical tablets or pellets is often controlled by applying a phase-separated polymer film coating. Ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends are commonly used. The HPC phase leaches out when in contact with water and the result is a porous EC matrix coating, with mass transport properties that can be controlled by tailoring the structure of the porous network. High-resolution 3D imaging is necessary to characterize such materials, and the resolution of e.g. X-ray computed tomography is simply insufficient. Combined focused ion beam and scanning electron microscope (FIB-SEM) tomography on the other hand is a suitable technique, but segmentation of FIB-SEM data, in this case to separate the solid matrix and the porous network, is challenging. In this work, we develop a method for segmentation of FIB-SEM image data acquired from three different EC porous films where the HPC phases have been leached out. The segmentation is based on convolutional neural networks (CNNs). CNNs is a well-established machine learning paradigm and has demonstrated state-of-the-art performance in many image analysis and segmentation tasks. CNNs are inspired from biological processes in the visual cortex and act similarly, at least conceptually. In contrast to most conventional machine learning algorithms, CNNs learn by themselves which features to extract from the images. The features are extracted at different spatial scales and may constitute e.g. edge and contrast detectors. These features are subsequently used for classification. In this work, CNNs are used for image segmentation. The goal is to identify which regions in the images that contain either pore (empty space) or solid (material), hence a binary classification task. For the CNN to learn how to perform such a task, a ground truth is needed. This is achieved by letting an expert manually segment parts of the data. This is a very time-consuming endeavor, hence only a small random subset of the full dataset is manually segmented. The CNN is trained for the task using the manually segmented data, after which automatic segmentation of the full dataset is performed. We obtain very good agreement with manual segmentations in terms of accuracy and porosity, and a clear improvement in comparison to an earlier developed random forest classifier trained on Gaussian scale-space features on the same data. The development of accurate segmentation methods is a crucial step toward better understanding and tailoring of coatings for controlled drug release.

Strain engineering provides an effective way of tailoring the electronic and optoelectronic properties of semiconductor nanomaterials and nanodevices, giving rise to novel functionalities. Here, we present direct experimental evidence of strain-induced modifications of hole mobility in individual gallium arsenide (GaAs) nanowires, using in situ transmission electron microscopy (TEM). The conductivity of the nanowires varied with applied uniaxial tensile stress, showing an initial decrease of ∼5–20% up to a stress of 1–2 GPa, subsequently increasing up to the elastic limit of the nanowires. This is attributed to a hole mobility variation due to changes in the valence band structure caused by stress and strain. The corresponding lattice strain in the nanowires was quantified by in situ four dimensional scanning TEM and showed a complex spatial distribution at all stress levels. Meanwhile, a significant red shift of the band gap induced by the stress and strain was unveiled by monochromated electron energy loss spectroscopy.

This study presents the synthesis of monodisperse Pd nanoparticles (NPs) stabilized by sodium oleate (NaOL) and hexadecyltrimethylammonium chloride (CTAC). The synthesis was conducted without traditional reductants and Pd-precursors are reduced by NaOL. It was confirmed that the alkyl double bond in NaOL is not the only explanation for the reduction of Pd-precursors since Pd NPs could be synthesized with CTAC and the saturated fatty acid sodium stearate (NaST). A quantitative evaluation of the reduction kinetics using UV-Vis spectroscopy shows that Pd NPs synthesized with both stabilizer combinations follow pseudo first-order reaction kinetics, where NaOL provides a faster and more effective reduction of Pd-precursors. The colloidal stabilization of the NP surface by CTAC and NaOL is confirmed by Fourier transform infrared (FTIR) and nuclear magnetic resonance (NMR) analysis.

Redox processes of oxide materials are fundamental in catalysis. These processes depend on the surface structure and stoichiometry of the oxide and are therefore expected to vary between surface facets. However, there is a lack of direct measurements of redox properties on the nanoscale for analysing the importance of such faceting effects in technical materials. Here, we address the facet-dependent redox properties of vanadium-oxide-covered anatase nanoparticles of relevance to, e.g., selective catalytic reduction of nitrogen oxides. The vanadium oxidation states at individual nanoscale facets are resolved in situ under catalytically relevant conditions by combining transmission electron microscopy imaging and electron energy loss spectroscopy. The measurements reveal that vanadium on {001} facets consistently retain higher oxidation states than on {10l} facets. Insight into such structure-sensitivity of surface redox processes opens prospects of tailoring oxide nanoparticles with enhanced catalytic functionalities.

Porous phase-separated films made of ethylcellulose (EC) and hydroxypropylcellulose (HPC) are commonly used for controlled drug release. The structure of these thin films is controlling the drug transport from the core to the surrounding liquids in the stomach or intestine. However, detailed understanding of the time evolution of these porous structures as they are formed remains elusive. In this work, spin-coating, a widely applied technique for making thin uniform polymer films, was used to mimic the industrial manufacturing process. The focus of this work was on understanding the structure evolution of phase-separated spin-coated EC/HPC films. The structure evolution was determined using confocal laser scanning microscopy (CLSM) and image analysis. In particular, we determined the influence of spin-coating parameters and EC : HPC ratio on the final phase-separated structure and the film thickness. The film thickness was determined by profilometry and it influences the ethanol solvent evaporation rate and thereby the phase separation kinetics. The spin speed was varied between 1000 and 10 000 rpm and the ratio of EC : HPC in the polymer blend was varied between 78 : 22 wt% and 40 : 60 wt%. The obtained CLSM micrographs showed phase separated structures, typical for the spinodal decomposition phase separation mechanism. By using confocal laser scanning microscopy combined with Fourier image analysis, we could extract the characteristic length scale of the phase-separated final structure. Varying spin speed and EC : HPC ratio gave us precise control over the characteristic length scale and the thickness of the film. The results showed that the characteristic length scale increases with decreasing spin speed and with increasing HPC ratio. The thickness of the spin-coated film decreases with increasing spin speed. It was found that the relation between film thickness and spin speed followed the Meyerhofer equation with an exponent close to 0.5. Furthermore, good correlations between thickness and spin speed were found for the compositions 22 wt% HPC, 30 wt% HPC and 45 wt% HPC. These findings give a good basis for understanding the mechanisms responsible for the morphology development and increase the possibilities to tailor thin EC/HPC film structures.

Porous phase-separated ethylcellulose/hydroxypropylcellulose (EC/HPC) films are used to control drug transport from pharmaceutical pellets. The drug transport rate is determined by the structure of the porous films that are formed as water-soluble HPC leaches out. However, a detailed understanding of the evolution of the phase-separated structure in the films is lacking. In this work, we have investigated EC/HPC films produced by spin-coating, mimicking the industrial fluidized bed spraying. The aim was to investigate film structure evolution and coarsening kinetics during solvent evaporation. The structure evolution was characterized using confocal laser scanning microscopy and image analysis. The effect of the EC:HPC ratio (15 to 85 wt% HPC) on the structure evolution was determined. Bicontinuous structures were found for 30 to 40 wt% HPC. The growth of the characteristic length scale followed a power law

Vulnerability to stress-induced inflammation has been linked to a dysfunctional hypothalamus–pituitary–adrenal (HPA) axis. In the present study, patients with known or suspected coronary artery disease (CAD) were assessed with respect to inflammatory and HPA axis response to acute physical exercise. An exercise stress test was combined with SPECT myocardial perfusion imaging. Plasma and saliva samples were collected before and 30 min after exercise. Interleukin (IL)-6 and adrenocorticotropic hormone (ACTH) were measured in plasma, while cortisol was measured in both plasma and saliva. In total, 124 patients were included of whom 29% had a prior history of CAD and/or a myocardial perfusion deficit. The levels of exercise intensity and duration were comparable in CAD and non-CAD patients. However, in CAD patients, IL-6 increased after exercise (p = 0.019) while no differences were seen in HPA axis variables. Conversely, patients without CAD exhibited increased levels of ACTH (p = 0.003) and cortisol (p = 0.004 in plasma, p = 0.006 in saliva), but no change in IL-6. We conclude that the IL-6 response to acute physical exercise is exaggerated in CAD patients and may be out of balance due to HPA axis hypoactivity. It remains to be further investigated whether this imbalance is a potential diagnostic and therapeutic target in CAD.

Summary Combined focused ion beam and scanning electron microscope (FIB‐SEM) tomography is a well‐established technique for high resolution imaging and reconstruction of the microstructure of a wide range of materials. Segmentation of FIB‐SEM data is complicated due to a number of factors; the most prominent is that for porous materials, the scanning electron microscope image slices contain information not only from the planar cross‐section of the material but also from underlying, exposed subsurface pores. In this work, we develop a segmentation method for FIB‐SEM data from ethyl cellulose porous films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. These materials are used for coating pharmaceutical oral dosage forms (tablets or pellets) to control drug release. We study three samples of ethyl cellulose and hydroxypropyl cellulose with different volume fractions where the hydroxypropyl cellulose phase has been leached out, resulting in a porous material. The data are segmented using scale‐space features and a random forest classifier. We demonstrate good agreement with manual segmentations. The method enables quantitative characterization and subsequent optimization of material structure for controlled release applications. Although the methodology is demonstrated on porous polymer films, it is applicable to other soft porous materials imaged by FIB‐SEM. We make the data and software used publicly available to facilitate further development of FIB‐SEM segmentation methods. Lay Description For imaging of very fine structures in materials, the resolution limits of, e.g. X‐ray computed tomography quickly become a bottleneck. Scanning electron microscopy (SEM) provides a way out, but it is essentially a two‐dimensional imaging technique. One manner in which to extend it to three dimensions is to use a focused ion beam (FIB) combined with a scanning electron microscopy and acquire tomography data. In FIB‐SEM tomography, ions are used to perform serial sectioning and the electron beam is used to image the cross section surface. This is a well‐established method for a wide range of materials. However, image analysis of FIB‐SEM data is complicated for a variety of reasons, in particular for porous media. In this work, we analyse FIB‐SEM data from ethyl cellulose porous films made from ethyl cellulose and hydroxypropyl cellulose (EC/HPC) polymer blends. These films are used as coatings for controlled drug release. The aim is to perform image segmentation, i.e. to identify which parts of the image data constitute the pores and the solid, respectively. Manual segmentation, i.e. when a trained operator manually identifies areas constituting pores and solid, is too time‐consuming to do in full for our very large data sets. However, by performing manual segmentation on a set of small, random regions of the data, we can train a machine learning algorithm to perform automatic segmentation on the entire data sets. The method yields good agreement with the manual segmentations and yields porosities of the entire data sets in very good agreement with expected values. The method facilitates understanding and quantitative characterization of the geometrical structure of the materials, and ultimately understanding of how to tailor the drug release.

Surfactants are used widely to control the synthesis of shaped noble-metal nanoparticles. In this work, a mixture of hexadecyltrimethylammonium bromide (CTAB), a cationic surfactant; sodium oleate (NaOL), an anionic surfactant; palladium chloride; and a reducing agent were used in the seed-mediated synthesis of palladium nanoparticles. By controlling the surfactant mixture ratio, we initially discovered that palladium nanodendrites with narrow size distribution were formed instead of the traditional nanocubes, synthesized with only CTAB. In order to investigate the optimal ratio to produce Pd nanodendrites with a high yield and narrow size distribution, samples synthesized with multiple molar ratios of the two surfactants were prepared and studied by transmission electron microscopy, dynamic light scattering, conductance, and ultraviolet-visible spectroscopy. We propose that the addition of NaOL alters the arrangement of surfactants on the Pd seed surface, leading to a new pattern of growth and aggregation. By studying the nanodendrite growth over time, we identified the reduction period of Pd2+ ions and the formation period of the nanodendrites. Our further experiments, including the replacement of CTAB with hexadecyltrimethylammonium chloride (CTAC) and the replacement of NaOL with sodium stearate, showed that CTA+ ions in CTAB and OL- ions in NaOL play the main roles in the formation of nanodendrites. The formation of palladium nanodendrites was robust and achieved with a range of temperatures, pH and mixing speeds.

The ability to tune the localized surface plasmon resonance (LSPR) of nanostructures is desirable for surface enhanced Raman spectroscopy (SERS), plasmon-assisted chemistry and other nanophotonic applications. Although historically the LSPR is mainly studied by optical techniques, with the recent advancement in electron monochromators and correctors, it has attracted considerable attention in transmission electron microscopy (TEM). Here, we use electron energy loss spectroscopy (EELS) in a scanning TEM to study individual gold nanodiscs and bowties in lithographic arrays with variable LSPRs by adjusting the size, interspacing, shape and dielectric environment during the nanofabrication process. We observe the strongest Raman signal enhancement when the LSPR frequency is close to the incident laser frequency in Raman spectroscopy. A simplified harmonic oscillator model is used to estimate SERS enhancement factor (EF) from EELS, bridging the connection between electron and photon excitation of plasmonic arrays. This work demonstrates that STEM-EELS shows promise for revealing the contributions of specific LSPR modes to SERS EF. Our results provide guidelines to fine-tune nanoparticle parameters to deliver the maximum signal enhancement in biosensing applications, such as early cancer detection.

Porous polymer coatings are used to control drug release from pharmaceutical products. The coating covers a drug core and depending on the porous structure, different drug release rates are obtained. This work presents mass transport simulations performed on porous ethyl cellulose films with different porosities. The simulations were performed on high spatial resolution 3D data obtained using a focused ion beam scanning electron microscope. The effective diffusion coefficient of water was determined using a diffusion chamber. Lattice Boltzmann simulations were used to simulate water diffusion in the 3D data. The simulated coefficient was in good agreement with the measured coefficient. From the results it was concluded that the tortuosity and constrictivity of the porous network increase with decreasing amount of added hydroxypropyl cellulose, resulting in a sharp decrease in effective diffusion. This work shows that high spatial resolution 3D data is necessary, and that 2D data is insufficient, in order to predict diffusion through the porous structure with high accuracy.

Inversion-symmetry breaking for second-harmonic generation in centrosymmetric Si and Ge is artificially realized with a pair of asymmetric-coupled SiGe quantum wells. Laser spectroscopy experiments demonstrate a nonlinear susceptibility four orders of magnitude larger than that of natural nonlinear materials in the visible range.