Lattice Softening Significantly Reduces Thermal Conductivity and Leads to High Thermoelectric Efficiency

The influence of micro/nanostructure on thermal conductivity is a topic of great scientific interest, particularly to thermoelectrics. The current understanding is that structural defects decrease thermal conductivity through phonon scattering where the phonon dispersion and speed of sound are assumed to remain constant. Experimental work on a PbTe model system is presented, which shows that the speed of sound linearly decreases with increased internal strain. This softening of the materials lattice completely accounts for the reduction in lattice thermal conductivity, without the introduction of additional phonon scattering mechanisms. Additionally, it is shown that a major contribution to the improvement in the thermoelectric figure of merit (zT > 2) of high‐efficiency Na‐doped PbTe can be attributed to lattice softening. While inhomogeneous internal strain fields are known to introduce phonon scattering centers, this study demonstrates that internal strain can modify phonon propagation speed as well. This presents new avenues to control lattice thermal conductivity, beyond phonon scattering. In practice, many engineering materials will exhibit both softening and scattering effects, as is shown in silicon. This work shines new light on studies of thermal conductivity in fields of energy materials, microelectronics, and nanoscale heat transfer.     

Metasurfaces Atop Metamaterials: Surface Morphology Induces Linear Dichroism in Gyroid Optical Metamaterials

Optical metamaterials offer the tantalizing possibility of creating extraordinary optical properties through the careful design and arrangement of subwavelength structural units. Gyroid‐structured optical metamaterials possess a chiral, cubic, and triply periodic bulk morphology that exhibits a redshifted effective plasma frequency. They also exhibit a strong linear dichroism, the origin of which is not yet understood. Here, the interaction of light with gold gyroid optical metamaterials is studied and a strong correlation between the surface morphology and its linear dichroism is found. The termination of the gyroid surface breaks the cubic symmetry of the bulk lattice and gives rise to the observed wavelength‐ and polarization‐dependent reflection. The results show that light couples into both localized and propagating plasmon modes associated with anisotropic surface protrusions and the gaps between such protrusions. The localized surface modes give rise to the anisotropic optical response, creating the linear dichroism. Simulated reflection spectra are highly sensitive to minute details of these surface terminations, down to the nanometer level, and can be understood with analogy to the optical properties of a 2D anisotropic metasurface atop a 3D isotropic metamaterial. This pronounced sensitivity to the subwavelength surface morphology has significant consequences for both the design and application of optical metamaterials.     

Computational homogenization of elasticity on a staggered grid

In this article, we propose to discretize the problem of linear elastic homogenization by finite differences on a staggered grid and introduce fast and robust solvers. Our method shares some properties with the FFT‐based homogenization technique of Moulinec and Suquet, which has received widespread attention recently because of its robustness and computational speed. These similarities include the use of FFT and the resulting performing solvers. The staggered grid discretization, however, offers three crucial improvements. Firstly, solutions obtained by our method are completely devoid of the spurious oscillations characterizing solutions obtained by Moulinec–Suquet's discretization. Secondly, the iteration numbers of our solvers are bounded independently of the grid size and the contrast. In particular, our solvers converge for three‐dimensional porous structures, which cannot be handled by Moulinec–Suquet's method. Thirdly, the finite difference discretization allows for algorithmic variants with lower memory consumption. More precisely, it is possible to reduce the memory consumption of the Moulinec–Suquet algorithms by 50%. We underline the effectiveness and the applicability of our methods by several numerical experiments of industrial scale. Copyright © 2015 John Wiley & Sons, Ltd.     

Influence of Temperature on the Colloidal Stability of Polymer‐Coated Gold Nanoparticles in Cell Culture Media

The temperature‐dependence of the hydrodynamic diameter and colloidal stability of gold‐polymer core‐shell particles with temperature‐sensitive (poly(N‐isopropylacrylamide)) and temperature‐insensitive shells (polyallylaminine hydrochloride/polystyrensulfonate, poly(isobutylene‐alt‐maleic anhydride)‐graft‐dodecyl) are investigated in various aqueous media. The data demonstrate that for all nanoparticle agglomeration, i.e., increase in effective nanoparticle size, the presence of salts or proteins in the dispersion media has to be taken into account. Poly(N‐isopropylacrylamide) coated nanoparticles show a reversible temperature‐dependent increase in size above the volume phase transition of the polymer shell when they are dispersed in phosphate buffered saline or in media containing protein. In contrast, the nanoparticles coated with temperature‐insensitive polymers show a time‐dependent increase in size in phosphate buffered saline or in medium containing protein. This is due to time‐dependent agglomeration, which is particularly strong in phosphate buffered saline, and induces a time‐dependent, irreversible increase in the hydrodynamic diameter of the nanoparticles. This demonstrates that one has to distinguish between temperature‐ and time‐induced agglomerations. Since the size of nanoparticles regulates their uptake by cells, temperature‐dependent uptake of thermosensitive and non‐thermosensitive nanoparticles by cells lines is compared. No temperature‐specific difference between both types of nanoparticles could be observed.     

An Overview of the Latest Metabolomics Studies on Atopic Eczema with New Directions for Study

Atopic eczema (AE) is an inflammatory skin disorder affecting approximately 20% of children worldwide and early onset can lead to asthma and allergies. Currently, the mechanisms of the disease are not fully understood. Metabolomics, the analysis of small molecules in the skin produced by the host and microbes, opens a window to observe the mechanisms of the disease which then may lead to new drug targets for AE treatment. Here, we review the latest advances in AE metabolomics, highlighting both the lipid and non-lipid molecules, along with reviewing the metabolites currently known to reside in the skin.     

Long COVID: Association of Functional Autoantibodies against G-Protein-Coupled Receptors with an Impaired Retinal Microcirculation

Long COVID (LC) describes the clinical phenotype of symptoms after infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnostic and therapeutic options are limited, as the pathomechanism of LC is elusive. As the number of acute SARS-CoV-2 infections was and is large, LC will be a challenge for the healthcare system. Previous studies revealed an impaired blood flow, the formation of microclots, and autoimmune mechanisms as potential factors in this complex interplay. Since functionally active autoantibodies against G-protein-coupled receptors (GPCR-AAbs) were observed in patients after SARS-CoV-2 infection, this study aimed to correlate the appearance of GPCR-AAbs with capillary microcirculation. The seropositivity of GPCR-AAbs was measured by an established cardiomyocyte bioassay in 42 patients with LC and 6 controls. Retinal microcirculation was measured by OCT–angiography and quantified as macula and peripapillary vessel density (VD) by the Erlangen-Angio Tool. A statistical analysis yielded impaired VD in patients with LC compared to the controls, which was accentuated in female persons. A significant decrease in macula and peripapillary VD for AAbs targeting adrenergic β2-receptor, MAS-receptor angiotensin-II-type-1 receptor, and adrenergic α1-receptor were observed. The present study might suggest that a seropositivity of GPCR-AAbs can be linked to an impaired retinal capillary microcirculation, potentially mirroring the systemic microcirculation with consecutive clinical symptoms.     

Automatic classifier selection for non-experts

Choosing a suitable classifier for a given dataset is an important part of developing a pattern recognition system. Since a large variety of classification algorithms are proposed in literature, non-experts do not know which method should be used in order to obtain good classification results on their data. Meta-learning tries to address this problem by recommending promising classifiers based on meta-features computed from a given dataset. In this paper, we empirically evaluate five different categories of state-of-the-art meta-features for their suitability in predicting classification accuracies of several widely used classifiers (including Support Vector Machines, Neural Networks, Random Forests, Decision Trees, and Logistic Regression). Based on the evaluation results, we have developed the first open source meta-learning system that is capable of accurately predicting accuracies of target classifiers. The user provides a dataset as input and gets an automatically created high-performance ready-to-use pattern recognition system in a few simple steps. A user study of the system with non-experts showed that the users were able to develop more accurate pattern recognition systems in significantly less development time when using our system as compared to using a state-of-the-art data mining software.     

Diverse nearest neighbors queries using linear skylines

k-nearest neighbor (k-NN) queries are well-known and widely used in a plethora of applications. However, in the original definition of k-NN queries there is no concern regarding diversity of the answer set with respect to the user’s interests. For instance, travelers may be looking for touristic sites that are close to where they are, but that would also lead them to see different parts of the city. Likewise, if one is looking for restaurants close by, it may be more interesting to learn about restaurants of different categories or ethnicities which are nonetheless relatively close. The interesting novel aspect of this type of query is that there are two competing criteria to be optimized: closeness and diversity. We propose two approaches that leverage the notion of linear skyline queries in order to find the k diverse nearest neighbors within a radius r from a given query point, or (k, r)-DNNs for short. Our proposed approaches return a relatively small set containing all optimal solutions for any linear combination of the weights a user could give to the two competing criteria, and we consider three different notions of diversity: spatial, categorical and angular. Our experiments, varying a number of parameters and exploring synthetic and real datasets, in both Euclidean space and road networks, respectively, show that our approaches are several orders of magnitude faster than a straightforward approach.     

Characterization of Micro-Powders for the Fabrication of Compression Molded THz Lenses

We investigate different micro-powders that can be used as base materials for THz lenses fabricated by compression molding. For this application materials with a very weak THz absorbance and low dispersion are required. By measuring the THz absorption coefficient and refractive index of pellets pressed from the different micro-powders, we identify several materials that are well suited for the fabrication of compression molded THz lenses (CMLs). In addition, a considerable range of the refractive index is covered by the samples, which will allow for the fabrication of CMLs with different focal lengths for one and the same lens design.     

Tuning the Properties of CZTS Films by Controlling the Process Parameters in Cost-Effective Non-vacuum Technique

Highly dispersive Cu₂ZnSnS₄ (CZTS) nanoparticles were successfully synthesized by a simple solvothermal route. A low cost, non-vacuum method was used to deposit CZTS nanoparticle ink on glass substrates by a doctor blade process followed by selenization in a tube furnace to form Cu₂ZnSn (S,Se)₄ (CZTSSe) layers. Different selenization conditions and particle concentrations were considered in order to improve the crystallinity and surface morphology; the annealing temperature was varied between 400°C and 550°C and the annealing time was varied between 5 min and 20 min in a selenium-nitrogen atmosphere. The influence of annealing conditions on structural, compositional, optical and electrical properties of CZTSSe thin films was studied. An improvement in the structural and surface morphology was observed with increasing of annealing temperature (up to 500°C). An enhancement in the crystallinity and surface morphology were observed for thin films annealed for 10–15 min. Absorption study revealed that the band gap energy of as-deposited CZTS thin film was approximately 1.43 eV, while for CZTSSe thin films it ranged from 1.15 eV to 1.34 eV at different annealing temperatures, and from 1.33 eV to 1.38 eV for different annealing times.