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The quantitative analysis of microstructural features is a key to understanding the micromechanical behavior of metal matrix composites (MMCs), which is a premise for their use in practice. Herein, a 3D microstructural characterization of a five-phase MMC is performed by synchrotron X-ray computed tomography (SXCT). A workflow for advanced deep learning-based segmentation of all individual phases in SXCT data is shown using a fully convolutional neural network with U-net architecture. High segmentation accuracy is achieved with a small amount of training data. This enables extracting unprecedently precise microstructural parameters (e.g., volume fractions and particle shapes) to be input, e.g., in micromechanical models.
Alone but not lonely
(2020)
Context. Hot subdwarfs are core-helium burning stars that show lower masses and higher temperatures than canonical horizontal branch stars. They are believed to be formed when a red giant suffers an extreme mass-loss episode. Binary interaction is suggested to be the main formation channel, but the high fraction of apparently single hot subdwarfs (up to 30%) has prompted single star formation scenarios to be proposed.Aims. We investigate the possibility that hot subdwarfs could form without interaction by studying wide binary systems. If single formation scenarios were possible, there should be hot subdwarfs in wide binaries that have undergone no interaction.Methods. Angular momentum accretion during interaction is predicted to cause the hot subdwarf companion to spin up to the critical velocity. The effect of this should still be observable given the timescales of the hot subdwarf phase. To study the rotation rates of companions, we have analysed light curves from the Transiting Exoplanet Survey Satellite for all known hot subdwarfs showing composite spectral energy distributions indicating the presence of a main sequence wide binary companion. If formation without interaction were possible, that would also imply the existence of hot subdwarfs in very wide binaries that are not predicted to interact. To identify such systems, we have searched for common proper motion companions with projected orbital distances of up to 0.1 pc to all known spectroscopically confirmed hot subdwarfs using Gaia DR2 astrometry.Results. We find that the companions in composite hot subdwarfs show short rotation periods when compared to field main sequence stars. They display a triangular-shaped distribution with a peak around 2.5 days, similar to what is observed for young open clusters. We also report a shortage of hot subdwarfs with candidate common proper motion companions. We identify only 16 candidates after probing 2938 hot subdwarfs with good astrometry. Out of those, at least six seem to be hierarchical triple systems, in which the hot subdwarf is part of an inner binary.Conclusions. The observed distribution of rotation rates for the companions in known wide hot subdwarf binaries provides evidence of previous interaction causing spin-up. Additionally, there is a shortage of hot subdwarfs in common proper motion pairs, considering the frequency of such systems among progenitors. These results suggest that binary interaction is always required for the formation of hot subdwarfs.
Droughts in tropical South America have an imminent and severe impact on the Amazon rainforest and affect the livelihoods of millions of people. Extremely dry conditions in Amazonia have been previously linked to sea surface temperature (SST) anomalies in the adjacent tropical oceans. Although the sources and impacts of such droughts have been widely studied, establishing reliable multi-year lead statistical forecasts of their occurrence is still an ongoing challenge. Here, we further investigate the relationship between SST and rainfall anomalies using a complex network approach. We identify four ocean regions which exhibit the strongest overall SST correlations with central Amazon rainfall, including two particularly prominent regions in the northern and southern tropical Atlantic. Based on the time-dependent correlation between SST anomalies in these two regions alone, we establish a new early-warning method for droughts in the central Amazon basin and demonstrate its robustness in hindcasting past major drought events with lead-times up to 18 months.
The unidentified very-high-energy (VHE; E > 0.1 TeV) gamma -ray source, HESS J1826-130, was discovered with the High Energy Stereoscopic System (HESS) in the Galactic plane. The analysis of 215 h of HESS data has revealed a steady gamma -ray flux from HESS J1826-130, which appears extended with a half-width of 0.21 degrees +/- 0.02 <br /> (stat)degrees <br /> stat degrees +/- 0.05 <br /> (sys)degrees sys degrees . The source spectrum is best fit with either a power-law function with a spectral index Gamma = 1.78 +/- 0.10(stat) +/- 0.20(sys) and an exponential cut-off at 15.2 <br /> (+5.5)(-3.2) -3.2+5.5 TeV, or a broken power-law with Gamma (1) = 1.96 +/- 0.06(stat) +/- 0.20(sys), Gamma (2) = 3.59 +/- 0.69(stat) +/- 0.20(sys) for energies below and above E-br = 11.2 +/- 2.7 TeV, respectively. The VHE flux from HESS J1826-130 is contaminated by the extended emission of the bright, nearby pulsar wind nebula, HESS J1825-137, particularly at the low end of the energy spectrum. Leptonic scenarios for the origin of HESS J1826-130 VHE emission related to PSR J1826-1256 are confronted by our spectral and morphological analysis. In a hadronic framework, taking into account the properties of dense gas regions surrounding HESS J1826-130, the source spectrum would imply an astrophysical object capable of accelerating the parent particle population up to greater than or similar to 200 TeV. Our results are also discussed in a multiwavelength context, accounting for both the presence of nearby supernova remnants, molecular clouds, and counterparts detected in radio, X-rays, and TeV energies.
Concurrent observation technologies have made high-precision real-time data available in large quantities. Data assimilation (DA) is concerned with how to combine this data with physical models to produce accurate predictions. For spatial-temporal models, the ensemble Kalman filter with proper localisation techniques is considered to be a state-of-the-art DA methodology. This article proposes and investigates a localised ensemble Kalman Bucy filter for nonlinear models with short-range interactions. We derive dimension-independent and component-wise error bounds and show the long time path-wise error only has logarithmic dependence on the time range. The theoretical results are verified through some simple numerical tests.
We study populations of globally coupled noisy rotators (oscillators with inertia) allowing a nonequilibrium transition from a desynchronized state to a synchronous one (with the nonvanishing order parameter). The newly developed analytical approaches resulted in solutions describing the synchronous state with constant order parameter for weakly inertial rotators, including the case of zero inertia, when the model is reduced to the Kuramoto model of coupled noise oscillators. These approaches provide also analytical criteria distinguishing supercritical and subcritical transitions to the desynchronized state and indicate the universality of such transitions in rotator ensembles. All the obtained analytical results are confirmed by the numerical ones, both by direct simulations of the large ensembles and by solution of the associated Fokker-Planck equation. We also propose generalizations of the developed approaches for setups where different rotators parameters (natural frequencies, masses, noise intensities, strengths and phase shifts in coupling) are dispersed.
We study populations of globally coupled noisy rotators (oscillators with inertia) allowing a nonequilibrium transition from a desynchronized state to a synchronous one (with the nonvanishing order parameter). The newly developed analytical approaches resulted in solutions describing the synchronous state with constant order parameter for weakly inertial rotators, including the case of zero inertia, when the model is reduced to the Kuramoto model of coupled noise oscillators. These approaches provide also analytical criteria distinguishing supercritical and subcritical transitions to the desynchronized state and indicate the universality of such transitions in rotator ensembles. All the obtained analytical results are confirmed by the numerical ones, both by direct simulations of the large ensembles and by solution of the associated Fokker-Planck equation. We also propose generalizations of the developed approaches for setups where different rotators parameters (natural frequencies, masses, noise intensities, strengths and phase shifts in coupling) are dispersed.
Organic solar cells are currently experiencing a second golden age thanks to the development of novel non-fullerene acceptors (NFAs). Surprisingly, some of these blends exhibit high efficiencies despite a low energy offset at the heterojunction. Herein, free charge generation in the high-performance blend of the donor polymer PM6 with the NFA Y6 is thoroughly investigated as a function of internal field, temperature and excitation energy. Results show that photocurrent generation is essentially barrierless with near-unity efficiency, regardless of excitation energy. Efficient charge separation is maintained over a wide temperature range, down to 100 K, despite the small driving force for charge generation. Studies on a blend with a low concentration of the NFA, measurements of the energetic disorder, and theoretical modeling suggest that CT state dissociation is assisted by the electrostatic interfacial field which for Y6 is large enough to compensate the Coulomb dissociation barrier.
Bioinspired confinement of upconversion nanoparticles for improved performance in aqueous solution
(2020)
The resonance energy transfer (RET) from NaYF4:Yb,Er upconverting nanoparticles (UNCPs) to a dye (5-carboxytetramethylrhodamine (TAMRA)) was investigated by photoluminescence experiments and microscale thermophoresis (MST). The dye was excited via RET from the UCNPs which was excited in the near-infrared (NIR). The change of the dye diffusion speed (free vs coupled) was investigated by MST. RET shows significant changes in the decay times of the dye as well as of the UCNPs. MST reveals significant changes in the diffusion speed. A unique amphiphilic coating polymer (customized mussel protein (CMP) polymer) for UCNP surface coating was used, which mimics blood protein adsorption and mussel food protein adhesion to transfer the UCNP into the aqueous phase and to allow surface functionalization. The CMP provides very good water dispersibility to the UCNPs and minimizes ligand exchange and subsequent UCNP aging reactions because of the interlinkage of the CMP on the UCNP surface. Moreover, CMP provides N-3-functional groups for dick chemistry-based functionalization demonstrated with the dye 5-carboxytetramethylrhodamine (TAMRA). This establishes the principle coupling scheme for suitable biomarkers such as antibodies. The CMP provides very stable aqueous UCNP dispersions that are storable up to 3 years in a fridge at 5 degrees C without dissolution or coagulation. The outstanding properties of CMP in shielding the UCNP from unwanted solvent effects is reflected in the distinct increase of the photoluminescence decay times after UCNP functionalization. The UCNP-to-TAMRA energy transfer is also spectroscopically investigated at low temperatures (4-200 K), revealing that one of the two green Er(III) emission bands contributes the major part to the energy transfer. The TAMRA fluorescence decay time increases by a factor of 9500 from 2.28 ns up to 22 mu s due to radiationless energy transfer from the UCNP after NIR excitation of the latter. This underlines the unique properties of CMP as a versatile capping ligand for distinctly improving the UCNPs' performance in aqueous solutions, for coupling of biomolecules, and for applications for in vitro and in vivo experiments using UCNPs as optical probes in life science applications.
What is the optimal distribution of two types of crystalline phases on the surface of icosahedral shells, such as of many viral capsids? We here investigate the distribution of a thin layer of soft material on a crystalline convex icosahedral shell. We demonstrate how the shapes of spherical viruses can be understood from the perspective of elasticity theory of thin two-component shells. We develop a theory of shape transformations of an icosahedral shell upon addition of a softer, but still crystalline, material onto its surface. We show how the soft component "invades" the regions with the highest elastic energy and stress imposed by the 12 topological defects on the surface. We explore the phase diagram as a function of the surface fraction of the soft material, the shell size, and the incommensurability of the elastic moduli of the rigid and soft phases. We find that, as expected, progressive filling of the rigid shell by the soft phase starts from the most deformed regions of the icosahedron. With a progressively increasing soft-phase coverage, the spherical segments of domes are filled first (12 vertices of the shell), then the cylindrical segments connecting the domes (30 edges) are invaded, and, ultimately, the 20 flat faces of the icosahedral shell tend to be occupied by the soft material. We present a detailed theoretical investigation of the first two stages of this invasion process and develop a model of morphological changes of the cone structure that permits noncircular cross sections. In conclusion, we discuss the biological relevance of some structures predicted from our calculations, in particular for the shape of viral capsids.
The performance of the recently commissioned spectrometer PEAXIS for resonant inelastic soft X-ray scattering (RIXS) and X-ray photoelectron spectroscopy and its hosting beamline U41-PEAXIS at the BESSY II synchrotron are characterized. The beamline provides linearly polarized light from 180 eV to 1600 eV allowing for RIXS measurements in the range 200-1200 eV. The monochromator optics can be operated in different configurations to provide either high flux with up to 10(12) photons s(-1) within the focal spot at the sample or high energy resolution with a full width at half maximum of <40 meV at an incident photon energy of similar to 400 eV. The measured total energy resolution of the RIXS spectrometer is in very good agreement with theoretically predicted values obtained by ray-tracing simulations. PEAXIS features a 5 m-long RIXS spectrometer arm that can be continuously rotated about the sample position by 106 degrees within the horizontal photon scattering plane, thus enabling the study of momentum-transfer-dependent excitations. Selected scientific examples are presented to demonstrate the instrument capabilities, including measurements of excitations in single-crystalline NiO and in liquid acetone employing a fluid cell sample manipulator. Planned upgrades of the beamline and the RIXS spectrometer to further increase the energy resolution to similar to 100 meV at 1000 eV incident photon energy are discussed.
The contamination of barley by molds on the field or in storage leads to the spoilage of grain and the production of mycotoxins, which causes major economic losses in malting facilities and breweries. Therefore, on-site detection of hidden fungus contaminations in grain storages based on the detection of volatile marker compounds is of high interest. In this work, the volatile metabolites of 10 different fungus species are identified by gas chromatography (GC) combined with two complementary mass spectrometric methods, namely, electron impact (EI) and chemical ionization at atmospheric pressure (APCI)-mass spectrometry (MS). The APCI source utilizes soft X-radiation, which enables the selective protonation of the volatile metabolites largely without side reactions. Nearly 80 volatile or semivolatile compounds from different substance classes, namely, alcohols, aldehydes, ketones, carboxylic acids, esters, substituted aromatic compounds, alkenes, terpenes, oxidized terpenes, sesquiterpenes, and oxidized sesquiterpenes, could be identified. The profiles of volatile and semivolatile metabolites of the different fungus species are characteristic of them and allow their safe differentiation. The application of the same GC parameters and APCI source allows a simple method transfer from MS to ion mobility spectrometry (IMS), which permits on-site analyses of grain stores. Characterization of IMS yields limits of detection very similar to those of APCI-MS. Accordingly, more than 90% of the volatile metabolites found by APCI-MS were also detected in IMS. In addition to different fungus genera, different species of one fungus genus could also be differentiated by GC-IMS.
Bacterial chemotaxis-a fundamental example of directional navigation in the living world-is key to many biological processes, including the spreading of bacterial infections. Many bacterial species were recently reported to exhibit several distinct swimming modes-the flagella may, for example, push the cell body or wrap around it. How do the different run modes shape the chemotaxis strategy of a multimode swimmer? Here, we investigate chemotactic motion of the soil bacterium Pseudomonas putida as a model organism. By simultaneously tracking the position of the cell body and the configuration of its flagella, we demonstrate that individual run modes show different chemotactic responses in nutrition gradients and, thus, constitute distinct behavioral states. On the basis of an active particle model, we demonstrate that switching between multiple run states that differ in their speed and responsiveness provides the basis for robust and efficient chemotaxis in complex natural habitats.
Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm.
A comet is a highly dynamic object, undergoing a permanent state of change. These changes have to be carefully classified and considered according to their intrinsic temporal and spatial scales. The Rosetta mission has, through its contiguous in-situ and remote sensing coverage of comet 67P/Churyumov-Gerasimenko (hereafter 67P) over the time span of August 2014 to September 2016, monitored the emergence, culmination, and winding down of the gas and dust comae. This provided an unprecedented data set and has spurred a large effort to connect in-situ and remote sensing measurements to the surface. In this review, we address our current understanding of cometary activity and the challenges involved when linking comae data to the surface. We give the current state of research by describing what we know about the physical processes involved from the surface to a few tens of kilometres above it with respect to the gas and dust emission from cometary nuclei. Further, we describe how complex multidimensional cometary gas and dust models have developed from the Halley encounter of 1986 to today. This includes the study of inhomogeneous outgassing and determination of the gas and dust production rates. Additionally, the different approaches used and results obtained to link coma data to the surface will be discussed. We discuss forward and inversion models and we describe the limitations of the respective approaches. The current literature suggests that there does not seem to be a single uniform process behind cometary activity. Rather, activity seems to be the consequence of a variety of erosion processes, including the sublimation of both water ice and more volatile material, but possibly also more exotic processes such as fracture and cliff erosion under thermal and mechanical stress, sub-surface heat storage, and a complex interplay of these processes. Seasons and the nucleus shape are key factors for the distribution and temporal evolution of activity and imply that the heliocentric evolution of activity can be highly individual for every comet, and generalisations can be misleading.
We present a diffusion-based simulation and theoretical models for explanation of the photoluminescence (PL) emission intensity in semiconductor nanoplatelets. It is shown that the shape of the PL intensity curves can be reproduced by the interplay of recombination, diffusion and trapping of excitons. The emission intensity at short times is purely exponential and is defined by recombination. At long times, it is governed by the release of excitons from surface traps and is characterized by a power-law tail. We show that the crossover from one limit to another is controlled by diffusion properties. This intermediate region exhibits a rich behaviour depending on the value of diffusivity. The proposed approach reproduces all the features of experimental curves measured for different nanoplatelet systems.
This paper discusses the fitting of linear state space models to given multivariate time series in the presence of constraints imposed on the four main parameter matrices of these models. Constraints arise partly from the assumption that the models have a block-diagonal structure, with each block corresponding to an ARMA process, that allows the reconstruction of independent source components from linear mixtures, and partly from the need to keep models identifiable. The first stage of parameter fitting is performed by the expectation maximisation (EM) algorithm. Due to the identifiability constraint, a subset of the diagonal elements of the dynamical noise covariance matrix needs to be constrained to fixed values (usually unity). For this kind of constraints, so far, no closed-form update rules were available. We present new update rules for this situation, both for updating the dynamical noise covariance matrix directly and for updating a matrix square-root of this matrix. The practical applicability of the proposed algorithm is demonstrated by a low-dimensional simulation example. The behaviour of the EM algorithm, as observed in this example, illustrates the well-known fact that in practical applications, the EM algorithm should be combined with a different algorithm for numerical optimisation, such as a quasi-Newton algorithm.
Quasiuniversal relations between the tidal deformability and the quadrupole moment of neutron stars are predicted by theoretical computations, but have not been measured experimentally. We simulate 120 binary neutron star sources and find that Advanced LIGO and Advanced Virgo at design sensitivity could find possible deviations from predicted relations if the neutron stars are highly spinning. A network of envisaged third generation detectors will even allow extracting such relations, providing new tests of general relativity and nuclear physics predictions.
We consider the emerging dynamics of a separable continuous time random walk (CTRW) in the case when the random walker is biased by a velocity field in a uniformly growing domain. Concrete examples for such domains include growing biological cells or lipid vesicles, biofilms and tissues, but also macroscopic systems such as expanding aquifers during rainy periods, or the expanding Universe. The CTRW in this study can be subdiffusive, normal diffusive or superdiffusive, including the particular case of a Lévy flight. We first consider the case when the velocity field is absent. In the subdiffusive case, we reveal an interesting time dependence of the kurtosis of the particle probability density function. In particular, for a suitable parameter choice, we find that the propagator, which is fat tailed at short times, may cross over to a Gaussian-like propagator. We subsequently incorporate the effect of the velocity field and derive a bi-fractional diffusion-advection equation encoding the time evolution of the particle distribution. We apply this equation to study the mixing kinetics of two diffusing pulses, whose peaks move towards each other under the action of velocity fields acting in opposite directions. This deterministic motion of the peaks, together with the diffusive spreading of each pulse, tends to increase particle mixing, thereby counteracting the peak separation induced by the domain growth. As a result of this competition, different regimes of mixing arise. In the case of Lévy flights, apart from the non-mixing regime, one has two different mixing regimes in the long-time limit, depending on the exact parameter choice: in one of these regimes, mixing is mainly driven by diffusive spreading, while in the other mixing is controlled by the velocity fields acting on each pulse. Possible implications for encounter–controlled reactions in real systems are discussed.
We present an efficient technique for control of synchrony in a globally coupled ensemble by pulsatile action. We assume that we can observe the collective oscillation and can stimulate all elements of the ensemble simultaneously. We pay special attention to the minimization of intervention into the system. The key idea is to stimulate only at the most sensitive phase. To find this phase, we implement an adaptive feedback control. Estimating the instantaneous phase of the collective mode on the fly, we achieve efficient suppression using a few pulses per oscillatory cycle. We discuss the possible relevance of the results for neuroscience, namely, for the development of advanced algorithms for deep brain stimulation, a medical technique used to treat Parkinson's disease.