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Tailoring the secondary surface morphology of electro-spun nanofibers has been highly desired, as such delicate structures equip nanofibers with distinct functions. Here, we report a simple strategy to directly reconstruct the surface of polyvinyl alcohol/polyvinylpyrrolidone (PVA/PVP) nanofibers by water evaporation. The roughness and diameter of the nanofibers depend on the temperature during vacuum drying. Surface changes of the nanofibers from smooth to rough were observed at 55 degrees C, with a significant drop in nanofiber diameter. We attribute the formation of the secondary surface morphology to the intermolecular forces in the water vapor, including capillary and the compression forces, on the basis of the results from the Fourier-transform infrared (FTIR) and X-ray photoelectron (XPS) spectroscopy. The strategy is universally effective for various electro-spun polymer nanofibers, thus opening up avenues toward more detailed and sophisticated structure design and implementation for nanofibers.
We formulate a linear phase and frequency response theory for hyperbolic flows, which generalizes phase response theory for autonomous limit cycle oscillators to hyperbolic chaotic dynamics. The theory is based on a shadowing conjecture, stating the existence of a perturbed trajectory shadowing every unperturbed trajectory on the system attractor for any small enough perturbation of arbitrary duration and a corresponding unique time isomorphism, which we identify as phase such that phase shifts between the unperturbed trajectory and its perturbed shadow are well defined. The phase sensitivity function is the solution of an adjoint linear equation and can be used to estimate the average change of phase velocity to small time dependent or independent perturbations. These changes in frequency are experimentally accessible, giving a convenient way to define and measure phase response curves for chaotic oscillators. The shadowing trajectory and the phase can be constructed explicitly in the tangent space of an unperturbed trajectory using co-variant Lyapunov vectors. It can also be used to identify the limits of the regime of linear response.
Computer-based analysis of preservice teachers' written reflections could enable educational scholars to design personalized and scalable intervention measures to support reflective writing. Algorithms and technologies in the domain of research related to artificial intelligence have been found to be useful in many tasks related to reflective writing analytics such as classification of text segments. However, mostly shallow learning algorithms have been employed so far. This study explores to what extent deep learning approaches can improve classification performance for segments of written reflections. To do so, a pretrained language model (BERT) was utilized to classify segments of preservice physics teachers' written reflections according to elements in a reflection-supporting model. Since BERT has been found to advance performance in many tasks, it was hypothesized to enhance classification performance for written reflections as well. We also compared the performance of BERT with other deep learning architectures and examined conditions for best performance. We found that BERT outperformed the other deep learning architectures and previously reported performances with shallow learning algorithms for classification of segments of reflective writing. BERT starts to outperform the other models when trained on about 20 to 30% of the training data. Furthermore, attribution analyses for inputs yielded insights into important features for BERT's classification decisions. Our study indicates that pretrained language models such as BERT can boost performance for language-related tasks in educational contexts such as classification.
We present observations of three-dimensional magnetic power spectra in wavevector space to investigate the anisotropy and scalings of sub-Alfvenic solar wind turbulence at magnetohydrodynamic (MHD) scale using the Magnetospheric Multiscale spacecraft. The magnetic power distributions are organized in a new coordinate determined by wavevectors ((kappa) over cap) and background magnetic field ((b) over cap (0)) in Fourier space. This study utilizes two approaches to determine wavevectors: the singular value decomposition method and multispacecraft timing analysis. The combination of the two methods allows an examination of the properties of magnetic field fluctuations in terms of mode compositions without any spatiotemporal hypothesis. Observations show that fluctuations (delta B-perpendicular to 1) in the direction perpendicular to (kappa) over cap and (b) over cap (0) prominently cascade perpendicular to (b) over cap (0), and such anisotropy increases with wavenumbers. The reduced power spectra of 6.8 11 follow Goldreich-Sridhar scalings: (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-5/3) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-2). In contrast, fluctuations within the (k) over cap(b) over cap (0) plane show isotropic behaviors: perpendicular power distributions are approximately the same as parallel distributions. The reduced power spectra of fluctuations within the (k) over cap(b) over cap (0) plane follow the scalings (P) over cap (k(perpendicular to)) proportional to k(perpendicular to)(-3/2) and (P) over cap (k(parallel to)) proportional to k(parallel to)(-3/2). Comparing frequency-wavevector spectra with theoretical dispersion relations of MHD modes, we find that delta B-perpendicular to 1 are probably associated with Alfven modes. On the other hand, magnetic field fluctuations within the (k) over cap(b) over cap (0) plane more likely originate from fast modes based on their isotropic behaviors. The observations of anisotropy and scalings of different magnetic field components are consistent with the predictions of current compressible MHD theory. Moreover, for the Alfvenic component, the ratio of cascading time to the wave period is found to be a factor of a few, consistent with critical balance in the strong turbulence regime. These results are valuable for further studies of energy compositions of plasma turbulence and their effects on energetic particle transport.
We quantitatively address the conjecture that magnetic helicity must be shed from the Sun by eruptions launching coronal mass ejections in order to limit its accumulation in each hemisphere. By varying the ratio of guide and strapping field and the flux rope twist in a parametric simulation study of flux rope ejection from approximately marginally stable force-free equilibria, different ratios of self- and mutual helicity are set and the onset of the torus or helical kink instability is obtained. The helicity shed is found to vary over a broad range from a minor to a major part of the initial helicity, with self helicity being largely or completely shed and mutual helicity, which makes up the larger part of the initial helicity, being shed only partly. Torus-unstable configurations with subcritical twist and without a guide field shed up to about two-thirds of the initial helicity, while a highly twisted, kink-unstable configuration sheds only about one-quarter. The parametric study also yields stable force-free flux rope equilibria up to a total flux-normalized helicity of 0.25, with a ratio of self- to total helicity of 0.32 and a ratio of flux rope to external poloidal flux of 0.94. These results numerically demonstrate the conjecture of helicity shedding by coronal mass ejections and provide a first account of its parametric dependence. Both self- and mutual helicity are shed significantly; this reduces the total initial helicity by a fraction of ∼0.4--0.65 for typical source region parameters.
High-energy irradiation is a driver for atmospheric evaporation and mass loss in exoplanets. This work is based on data from eROSITA, the soft X-ray instrument on board the Spectrum Roentgen Gamma mission, as well as on archival data from other missions. We aim to characterise the high-energy environment of known exoplanets and estimate their mass-loss rates. We use X-ray source catalogues from eROSITA, XMM-Newton, Chandra, and ROSAT to derive X-ray luminosities of exoplanet host stars in the 0.2–2 keV energy band with an underlying coronal, that is, optically thin thermal spectrum. We present a catalogue of stellar X-ray and EUV luminosities, exoplanetary X-ray and EUV irradiation fluxes, and estimated mass-loss rates for a total of 287 exoplanets, 96 of which are characterised for the first time based on new eROSITA detections. We identify 14 first-time X-ray detections of transiting exoplanets that are subject to irradiation levels known to cause observable evaporation signatures in other exoplanets. This makes them suitable targets for follow-up observations.
Designing gentle sinusoidal nanotextures enables the realization of high-efficiency perovskite-silicon solar cells <br /> Perovskite-silicon tandem solar cells offer the possibility of overcoming the power conversion efficiency limit of conventional silicon solar cells. Various textured tandem devices have been presented aiming at improved optical performance, but optimizing film growth on surface-textured wafers remains challenging. Here we present perovskite-silicon tandem solar cells with periodic nanotextures that offer various advantages without compromising the material quality of solution-processed perovskite layers. We show a reduction in reflection losses in comparison to planar tandems, with the new devices being less sensitive to deviations from optimum layer thicknesses. The nanotextures also enable a greatly increased fabrication yield from 50% to 95%. Moreover, the open-circuit voltage is improved by 15 mV due to the enhanced optoelectronic properties of the perovskite top cell. Our optically advanced rear reflector with a dielectric buffer layer results in reduced parasitic absorption at near-infrared wavelengths. As a result, we demonstrate a certified power conversion efficiency of 29.80%.
Different modeling methodologies possess different strengths and weakness. For instance, data based models may provide superior accuracy but have a limited spatial coverage while physics based models may provide lower accuracy but provide greater spatial coverage. This study investigates the coupling of a data based model of the electron fluxes at geostationary orbit (GEO) with a numerical model of the radiation belt region to improve the resulting forecasts/pastcasts of electron fluxes over the whole radiation belt region. In particular, two coupling methods are investigated. The first assumes an average value for L* for GEO, namely LGEO* L-GEO* = 6.2. The second uses a value of L* that varies with geomagnetic activity, quantified using the Kp index. As the terrestrial magnetic field responds to variations in geomagnetic activity, the value of L* will vary for a specific location. In this coupling method, the value of L* is calculated using the Kp driven Tsyganenko 89c magnetic field model for field line tracing. It is shown that this addition can result in changes in the initialization of the parameters at the Versatile Electron Radiation Belt model outer boundary. Model outputs are compared to Van Allen Probes MagEIS measurements of the electron fluxes in the inner magnetosphere for the March 2015 geomagnetic storm. It is found that the fixed LGEO* L-GEO* coupling method produces a more realistic forecast.
We revisit the Haake-Lewenstein-Wilkens approach to Edwards-Anderson (EA) model of Ising spin glass (SG) (Haake et al 1985 Phys. Rev. Lett. 55 2606). This approach consists in evaluation and analysis of the probability distribution of configurations of two replicas of the system, averaged over quenched disorder. This probability distribution generates squares of thermal copies of spin variables from the two copies of the systems, averaged over disorder, that is the terms that enter the standard definition of the original EA order parameter, qEA 0 0
Poly(vinylidenefluoride-trifluoroethylene)-based (P(VDF-TrFE)-based) terpolymers represent a new class of electroactive polymer materials that are relaxor-ferroelectric (RF) polymers and that offer unique and attractive property combinations in comparison with conventional ferroelectric polymers. The RF state is achieved by introducing a fluorine-containing termonomer as a "defect" into the ferroelectric P(VDF-TrFE) copolymer, which reduces the interaction between the VDF/TrFE dipoles. The resulting terpolymer exhibits a low Curie transition temperature and small remanent and coercive fields yielding a slim hysteresis loop that is typical for RF materials. Though the macroscopic behavior is similar to RF ceramics, the mechanisms of relaxor ferroelectricity in semi-crystalline polymers are different and not fully understood yet. Structure-property relationships play an important role in RF terpolymers, as they govern the final RF properties. Hence, a review of important characteristics, previous studies and relevant developments of P(VDF-TrFE)-based terfluoropolymers with either chlorofluoroethylene (CFE) or chlorotrifluoroethylene (CTFE) as the termonomer is deemed useful. The role of the termonomer and of its composition, as well as the effects of the processing conditions on the semi-crystalline structure which in turn affects the final RF properties are discussed in detail. In addition, the presence of noteworthy transition(s) in the mid-temperature range and the influence of preparation conditions on those transitions are reviewed. A better understanding of the fundamental aspects affecting the semi-crystalline structures will help to elucidate the nature of RF activity in VDF-based terpolymers and also help to further improve their applications-relevant electroactive properties.
In this study, we present an empirical model of the equatorial electron pitch angle distributions (PADs) in the outer radiation belt based on the full data set collected by the Magnetic Electron Ion Spectrometer (MagEIS) instrument onboard the Van Allen Probes in 2012-2019. The PADs are fitted with a combination of the first, third and fifth sine harmonics. The resulting equation resolves all PAD types found in the outer radiation belt (pancake, flat-top, butterfly and cap PADs) and can be analytically integrated to derive omnidirectional flux. We introduce a two-step modeling procedure that for the first time ensures a continuous dependence on L, magnetic local time and activity, parametrized by the solar wind dynamic pressure. We propose two methods to reconstruct equatorial electron flux using the model. The first approach requires two uni-directional flux observations and is applicable to low-PA data. The second method can be used to reconstruct the full equatorial PADs from a single uni- or omnidirectional measurement at off-equatorial latitudes. The model can be used for converting the long-term data sets of electron fluxes to phase space density in terms of adiabatic invariants, for physics-based modeling in the form of boundary conditions, and for data assimilation purposes.
Controlling the magnetization dynamics at the fastest speed is a major issue of fundamental condensed matter physics and its applications for data storage and processing technologies. It requires a deep understanding of the interactions between the degrees of freedom in solids, such as spin, electron, and lattice as well as their responses to external stimuli. In this paper, we systematically investigate the fluence dependence of ultrafast magnetization dynamics induced by below-bandgap ultrashort laser pulses in the ferrimagnetic insulators BixY3-xFe5O12 with 1 xBi 3. We demonstrate subpicosecond demagnetization dynamics in this material followed by a very slow remagnetization process. We prove that this demagnetization results from an ultrafast heating of iron garnets by two-photon absorption (TPA), suggesting a phonon-magnon thermalization time of 0.6 ps. We explain the slow remagnetization timescale by the low phonon heat conductivity in garnets. Additionally, we show that the amplitudes of the demagnetization, optical change, and lattice strain can be manipulated by changing the ellipticity of the pump pulses. We explain this phenomenon considering the TPA circular dichroism. These findings open exciting prospects for ultrafast manipulation of spin, charge, and lattice dynamics in magnetic insulators by ultrafast nonlinear optics.
The fluctuating hydrogen bridge bonded network of liquid water at ambient conditions entails a varied ensemble of the underlying constituting H2O molecular moieties. This is mirrored in a manifold of the H2O molecular potentials. Subnatural line width resonant inelastic X-ray scattering allowed us to quantify the manifold of molecular potential energy surfaces along the H2O symmetric normal mode and the local asymmetric O-H bond coordinate up to 1 and 1.5 angstrom, respectively. The comparison of the single H2O molecular potentials and spectroscopic signatures with the ambient conditions liquid phase H2O molecular potentials is done on various levels. In the gas phase, first principles, Morse potentials, and stepwise harmonic potential reconstruction have been employed and benchmarked. In the liquid phase the determination of the potential energy manifold along the local asymmetric O-H bond coordinate from resonant inelastic X-ray scattering via the bound state oxygen ls to 4a(1) resonance is treated within these frameworks. The potential energy surface manifold along the symmetric stretch from resonant inelastic X-ray scattering via the oxygen 1 s to 2b(2) resonance is based on stepwise harmonic reconstruction. We find in liquid water at ambient conditions H2O molecular potentials ranging from the weak interaction limit to strongly distorted potentials which are put into perspective to established parameters, i.e., intermolecular O-H, H-H, and O-O correlation lengths from neutron scattering.
Manipulating spin waves is highly required for the development of innovative data transport and processing technologies. Recently, the possibility of triggering high-frequency standing spin waves in magnetic insulators using femtosecond laser pulses was discovered, raising the question about how one can manipulate their dynamics. Here we explore this question by investigating the ultrafast magnetiza-tion and spin-wave dynamics induced by double-pulse laser excitation. We demonstrate a suppression or enhancement of the amplitudes of the standing spin waves by precisely tuning the time delay between the two pulses. The results can be understood as the constructive or destructive interference of the spin waves induced by the first and second laser pulses. Our findings open exciting perspectives towards generating single-mode standing spin waves that combine high frequency with large amplitude and low magnetic damping.
Organic photovoltaics (PV) is an energy-harvesting technology that offers many advantages, such as flexibility, low weight and cost, as well as environmentally benign materials and manufacturing techniques. Despite growth of power conversion efficiencies to around 19 % in the last years, organic PVs still lag behind inorganic PV technologies, mainly due to high losses in open-circuit voltage. Understanding and improving open circuit voltage in organic solar cells is challenging, as it is controlled by the properties of a donor-acceptor interface where the optical excitations are separated into charge carriers. Here, we provide an electrostatic model of a rough donor-acceptor interface and test it experimentally on small molecule PV materials systems. The model provides concise relationships between the open-circuit voltage, photovoltaic gap, charge-transfer state energy, and interfacial morphology. In particular, we show that the electrostatic bias generated across the interface reduces the photovoltaic gap. This negative influence on open-circuit voltage can, however, be circumvented by adjusting the morphology of the donor-acceptor interface.
Organic solar cells, despite their high power conversion efficiencies, suffer from open circuit voltage losses making them less appealing in terms of applications. Here, the authors, supported with experimental data on small molecule photovoltaic cells, relate open circuit voltage to photovoltaic gap, charge-transfer state energy, and donor-acceptor interfacial morphology.
The next observing runs of advanced gravitational-wave detectors will lead to a variety of binary neutron star detections and numerous possibilities for multimessenger observations of binary neutron star systems. In this context a clear understanding of the merger process and the possibility of prompt black hole formation after merger is important, as the amount of ejected material strongly depends on the merger dynamics. These dynamics are primarily affected by the total mass of the binary, however, the mass ratio also influences the postmerger evolution. To determine the effect of the mass ratio, we investigate the parameter space around the prompt-collapse threshold with a new set of fully relativistic simulations. The simulations cover three equations of state and seven mass ratios in the range of 1.0 <= q <= 1.75, with five to seven simulations of binary systems of different total mass in each case. The threshold mass is determined through an empirical relation based on the collapse time, which allows us to investigate effects of the mass ratio on the threshold mass and also on the properties of the remnant system. Furthermore, we model effects of mass ratio and equation of state on tidal parameters of threshold configurations.
Context:
About a third of the hot subdwarfs of spectral type B (sdBs), which are mostly core-helium-burning objects on the extreme horizontal branch, are found in close binaries with cool, low-mass stellar, substellar, or white dwarf companions. They can show light variations due to di fferent phenomena.
Aims:
Many hot subdwarfs now have space-based light curves with a high signal-to-noise ratio available. We used light curves from the Transiting Exoplanet Survey Satellite and the K2 space mission to look for more sdB binaries. Their light curves can be used to study the hot subdwarf primaries and their companions, and obtained orbital, atmospheric, and absolute parameters for those systems, when combined with other analysis methods.
Methods:
By classifying the light variations and combining these with the fit of the spectral energy distribution, the distance derived by the parallaxes obtained by Gaia, and the atmospheric parameters, mainly from the literature, we could derive the nature of the primaries and secondaries in 122 (75%) of the known sdB binaries and 82 newly found reflection e ffect systems. We derived absolute masses, radii, and luminosities for a total of 39 hot subdwarfs with cool, low-mass companions, as well 29 known and newly found sdBs with white dwarf companions.
Results:
The mass distribution of hot subdwarfs with cool, low-mass stellar and substellar companions, di ffers from those with white dwarf companions, implying they come from di fferent populations. By comparing the period and minimum companion mass distributions, we find that the reflection e ffect systems all have M dwarf or brown dwarf companions, and that there seem to be several di fferent populations of hot subdwarfs with white dwarf binaries - one with white dwarf minimum masses around 0.4 M-circle dot, one with longer periods and minimum companion masses up to 0.6 M-circle dot, and at the shortest period, another with white dwarf minimum masses around 0.8 M-circle dot. We also derive the first orbital period distribution for hot subdwarfs with cool, low-mass stellar or substellar systems selected from light variations instead of radial velocity variations. It shows a narrower period distribution, from 1.5 h to 35 h, compared to the distribution of hot subdwarfs with white dwarfs, which ranges from 1 h to 30 days. These period distributions can be used to constrain the previous common-envelope phase.
Accurately predicting total electron content (TEC) during geomagnetic storms is still a challenging task for ionospheric models. In this work, a neural-network (NN)-based model is proposed which predicts relative TEC with respect to the preceding 27-day median TEC, during storm time for the European region (with longitudes 30 degrees W-50 degrees E and latitudes 32.5 degrees N-70 degrees N). The 27-day median TEC (referred to as median TEC), latitude, longitude, universal time, storm time, solar radio flux index F10.7, global storm index SYM-H and geomagnetic activity index Hp30 are used as inputs and the output of the network is the relative TEC. The relative TEC can be converted to the actual TEC knowing the median TEC. The median TEC is calculated at each grid point over the European region considering data from the last 27 days before the storm using global ionosphere maps (GIMs) from international GNSS service (IGS) sources. A storm event is defined when the storm time disturbance index Dst drops below 50 nanotesla. The model was trained with storm-time relative TEC data from the time period of 1998 until 2019 (2015 is excluded) and contains 365 storms. Unseen storm data from 33 storm events during 2015 and 2020 were used to test the model. The UQRG GIMs were used because of their high temporal resolution (15 min) compared to other products from different analysis centers. The NN-based model predictions show the seasonal behavior of the storms including positive and negative storm phases during winter and summer, respectively, and show a mixture of both phases during equinoxes. The model's performance was also compared with the Neustrelitz TEC model (NTCM) and the NN-based quiet-time TEC model, both developed at the German Aerospace Agency (DLR). The storm model has a root mean squared error (RMSE) of 3.38 TEC units (TECU), which is an improvement by 1.87 TECU compared to the NTCM, where an RMSE of 5.25 TECU was found. This improvement corresponds to a performance increase by 35.6%. The storm-time model outperforms the quiet-time model by 1.34 TECU, which corresponds to a performance increase by 28.4% from 4.72 to 3.38 TECU. The quiet-time model was trained with Carrington averaged TEC and, therefore, is ideal to be used as an input instead of the GIM derived 27-day median. We found an improvement by 0.8 TECU which corresponds to a performance increase by 17% from 4.72 to 3.92 TECU for the storm-time model using the quiet-time-model predicted TEC as an input compared to solely using the quiet-time model.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C-60 interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C-60 interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110mV, and retain >97% of the initial efficiency after 400h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells. Effective transport layers are essential to suppress non-radiative recombination losses. Here, the authors introduce phenylamino-functionalized ortho-carborane as an interfacial layer, and realise inverted perovskite solar cells with efficiency of over 23% and operational stability of T97=400h.
The motility of adherent eukaryotic cells is driven by the dynamics of the actin cytoskeleton. Despite the common force-generating actin machinery, different cell types often show diverse modes of locomotion that differ in their shape dynamics, speed, and persistence of motion. Recently, experiments in Dictyostelium discoideum have revealed that different motility modes can be induced in this model organism, depending on genetic modifications, developmental conditions, and synthetic changes of intracellular signaling. Here, we report experimental evidence that in a mutated D. discoideum cell line with increased Ras activity, switches between two distinct migratory modes, the amoeboid and fan-shaped type of locomotion, can even spontaneously occur within the same cell. We observed and characterized repeated and reversible switchings between the two modes of locomotion, suggesting that they are distinct behavioral traits that coexist within the same cell. We adapted an established phenomenological motility model that combines a reaction-diffusion system for the intracellular dynamics with a dynamic phase field to account for our experimental findings.
The coupling of the internal mechanisms of cell polarization to cell shape deformations and subsequent cell crawling poses many interdisciplinary scientific challenges. Several mathematical approaches have been proposed to model the coupling of both processes, where one of the most successful methods relies on a phase field that encodes the morphology of the cell, together with the integration of partial differential equations that account for the polarization mechanism inside the cell domain as defined by the phase field. This approach has been previously employed to model the motion of single cells of the social amoeba Dictyostelium discoideum, a widely used model organism to study actin-driven motility and chemotaxis of eukaryotic cells. Besides single cell motility, Dictyostelium discoideum is also well-known for its collective behavior. Here, we extend the previously introduced model for single cell motility to describe the collective motion of large populations of interacting amoebae by including repulsive interactions between the cells. We performed numerical simulations of this model, first characterizing the motion of single cells in terms of their polarity and velocity vectors. We then systematically studied the collisions between two cells that provided the basic interaction scenarios also observed in larger ensembles of interacting amoebae. Finally, the relevance of the cell density was analyzed, revealing a systematic decrease of the motility with density, associated with the formation of transient cell clusters that emerge in this system even though our model does not include any attractive interactions between cells. This model is a prototypical active matter system for the investigation of the emergent collective dynamics of deformable, self-driven cells with a highly complex, nonlinear coupling of cell shape deformations, self-propulsion and repulsive cell-cell interactions. Understanding these self-organization processes of cells like their autonomous aggregation is of high relevance as collective amoeboid motility is part of wound healing, embryonic morphogenesis or pathological processes like the spreading of metastatic cancer cells.
Effective professional development programs (PDPs) rely on well-defined goals. However, recent studies on PDPs have not explored the goals from a multi-stakeholder perspective. This study identifies the most important learning goals of PDPs at science research institutions as perceived by four groups of stakeholders, namely teachers, education researchers, government representatives, and research scientists. Altogether, over 100 stakeholders from 42 countries involved in PDPs at science research institutions in Europe and North America participated in a three-round Delphi study. In the first round, the stakeholders provided their opinions on what they thought the learning goals of PDPs should be through an open-ended questionnaire. In the second and third rounds, the stakeholders assessed the importance of the learning goals that emerged from the first round by rating and ranking them, respectively. The outcome of the study is a hierarchical list of the ten most important learning goals of PDPs at particle physics laboratories. The stakeholders identified enhancing teachers' knowledge of scientific concepts and models and enhancing their knowledge of the curricula as the most important learning goals. Furthermore, the results show strong agreement between all the stakeholder groups regarding the defined learning goals. Indeed, all groups ranked the learning goals by their perceived importance almost identically. These outcomes could help policymakers establish more specific policies for PDPs. Additionally, they provide PDP practitioners at science research institutions with a solid base for future research and planning endeavors.
How do near-bankruptcy events in the past affect the dynamics of stock-market prices in the future? Specifically, what are the long-time properties of a time-local exponential growth of stock-market prices under the influence of stochastically occurring economic crashes? Here, we derive the ensemble- and time-averaged properties of the respective "economic" or geometric Brownian motion (GBM) with a nonzero drift exposed to a Poissonian constant-rate price-restarting process of "resetting." We examine-based both on thorough analytical calculations and on findings from systematic stochastic computer simulations-the general situation of reset GBM with a nonzero [positive] drift and for all special cases emerging for varying parameters of drift, volatility, and reset rate in the model. We derive and summarize all short- and long-time dependencies for the mean-squared displacement (MSD), the variance, and the mean time-averaged MSD (TAMSD) of the process of Poisson-reset GBM under the conditions of both rare and frequent resetting. We consider three main regions of model parameters and categorize the crossovers between different functional behaviors of the statistical quantifiers of this process. The analytical relations are fully supported by the results of computer simulations. In particular, we obtain that Poisson-reset GBM is a nonergodic stochastic process, with generally MSD(Delta) not equal TAMSD(Delta) and Variance(Delta) not equal TAMSD(Delta) at short lag times Delta and for long trajectory lengths T. We investigate the behavior of the ergodicity-breaking parameter in each of the three regions of parameters and examine its dependence on the rate of reset at Delta/T << 1. Applications of these theoretical results to the analysis of prices of reset-containing options are pertinent.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusion model and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a well-calibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output. <br /> Diffusive motions in complex environments such as living biological cells or soft matter systems can be analyzed with single-particle-tracking approaches, where accuracy of output may vary. The authors involve a machine-learning technique for decoding anomalous-diffusion data and provide an uncertainty estimate together with predicted output.
Spin precession in magnetic materials is commonly modelled with the classical phenomenological Landau-Lifshitz-Gilbert (LLG) equation. Based on a quantized three-dimensional spin + environment Hamiltonian, we here derive a spin operator equation of motion that describes precession and includes a general form of damping that consistently accounts for memory, coloured noise and quantum statistics. The LLG equation is recovered as its classical, Ohmic approximation. We further introduce resonant Lorentzian system-reservoir couplings that allow a systematic comparison of dynamics between Ohmic and non-Ohmic regimes. Finally, we simulate the full non-Markovian dynamics of a spin in the semi-classical limit. At low temperatures, our numerical results demonstrate a characteristic reduction and flattening of the steady state spin alignment with an external field, caused by the quantum statistics of the environment. The results provide a powerful framework to explore general three-dimensional dissipation in quantum thermodynamics.
The Antarctic ice sheet is the largest freshwater reservoir worldwide. If it were to melt completely, global sea levels would rise by about 58 m. Calculation of projections of the Antarctic contribution to sea level rise under global warming conditions is an ongoing effort which
yields large ranges in predictions. Among the reasons for this are uncertainties related to the physics of ice sheet modeling. These
uncertainties include two processes that could lead to runaway ice retreat: the Marine Ice Sheet Instability (MISI), which causes rapid grounding line retreat on retrograde bedrock, and the Marine Ice Cliff Instability (MICI), in which tall ice cliffs become unstable and calve off, exposing even taller ice cliffs.
In my thesis, I investigated both marine instabilities (MISI and MICI) using the Parallel Ice Sheet Model (PISM), with a focus on MICI.
Collective synchronization in a large population of self-sustained units appears both in natural and engineered systems. Sometimes this effect is in demand, while in some cases, it is undesirable, which calls for control techniques. In this paper, we focus on pulsatile control, with the goal to either increase or decrease the level of synchrony. We quantify this level by the entropy of the phase distribution. Motivated by possible applications in neuroscience, we consider pulses of a realistic shape. Exploiting the noisy Kuramoto-Winfree model, we search for the optimal pulse profile and the optimal stimulation phase. For this purpose, we derive an expression for the change of the phase distribution entropy due to the stimulus. We relate this change to the properties of individual units characterized by generally different natural frequencies and phase response curves and the population's state. We verify the general result by analyzing a two-frequency population model and demonstrating a good agreement of the theory and numerical simulations.
X-ray observations of star-planet systems are important to grow our understanding of exoplanets; these observations allow for studies of photoevaporation of the exoplanetary atmosphere, and in some cases even estimations of the size of the outer planetary atmosphere. The German-Russian eROSITA instrument onboard the SRG (Spectrum Roentgen Gamma) mission is performing the first all-sky X-ray survey since the 1990s, and provides X-ray fluxes and spectra of exoplanet host stars over a much larger volume than was accessible before. Using new eROSITA data as well as archival data from XMM-Newton, Chandra, and ROSAT, we estimate mass-loss rates of exoplanets under an energy-limited escape scenario and identify several exoplanets with strong X-ray irradiation and expected mass loss that are amenable to follow-up observations at other wavelengths. We model sample spectra using a toy model of an exoplanetary atmosphere to predict what exoplanet transit observations with future X-ray missions such as Athena will look like and estimate the observable X-ray transmission spectrum for a typical hot Jupiter-type exoplanet.
Stars are uniform spheres, but only to first order. The way in which stellar rotation and magnetism break this symmetry places important observational constraints on stellar magnetic fields, and factors in the assessment of the impact of stellar activity on exoplanet atmospheres. The spatial distribution of flares on the solar surface is well known to be nonuniform, but elusive on other stars. We briefly review the techniques available to recover the loci of stellar flares, and highlight a new method that enables systematic flare localization directly from optical light curves. We provide an estimate of the number of flares we may be able to localize with the Transiting Exoplanet Survey Satellite, and show that it is consistent with the results obtained from the first full sky scan of the mission. We suggest that nonuniform flare latitude distributions need to be taken into account in accurate assessments of exoplanet habitability.
We consider a ring network of theta neurons with non-local homogeneous coupling. We analyse the corresponding continuum evolution equation, analytically describing all possible steady states and their stability. By considering a number of different parameter sets, we determine the typical bifurcation scenarios of the network, and put on a rigorous footing some previously observed numerical results.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
We present a systematic study on the properties of Na(Y,Gd)F-4-based upconverting nanoparticles (UCNP) doped with 18% Yb3+, 2% Tm3+, and the influence of Gd3+ (10-50 mol% Gd3+). UCNP were synthesized via the solvothermal method and had a range of diameters within 13 and 50 nm. Structural and photophysical changes were monitored for the UCNP samples after a 24-month incubation period in dry phase and further redispersion. Structural characterization was performed by means of X-ray diffraction (XRD), transmission electron microscopy (TEM) as well as dynamic light scattering (DLS), and the upconversion luminescence (UCL) studies were executed at various temperatures (from 4 to 295 K) using time-resolved and steady-state spectroscopy. An increase in the hexagonal lattice phase with the increase of Gd3+ content was found, although the cubic phase was prevalent in most samples. The Tm3+-luminescence intensity as well as the Tm3+-luminescence decay times peaked at the Gd3+ concentration of 30 mol%. Although the general upconverting luminescence properties of the nanoparticles were preserved, the 24-month incubation period lead to irreversible agglomeration of the UCNP and changes in luminescence band ratios and lifetimes.
Sprache
Englisch
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
Modern single-particle-tracking techniques produce extensive time-series of diffusive motion in a wide variety of systems, from single-molecule motion in living-cells to movement ecology. The quest is to decipher the physical mechanisms encoded in the data and thus to better understand the probed systems. We here augment recently proposed machine-learning techniques for decoding anomalous-diffusion data to include an uncertainty estimate in addition to the predicted output. To avoid the Black-Box-Problem a Bayesian-Deep-Learning technique named Stochastic-Weight-Averaging-Gaussian is used to train models for both the classification of the diffusionmodel and the regression of the anomalous diffusion exponent of single-particle-trajectories. Evaluating their performance, we find that these models can achieve a wellcalibrated error estimate while maintaining high prediction accuracies. In the analysis of the output uncertainty predictions we relate these to properties of the underlying diffusion models, thus providing insights into the learning process of the machine and the relevance of the output.
In recent years, the search for more efficient and environmentally friendly materials to be employed in the next generation of thin film solar cell devices has seen a shift towards hybrid halide perovskites and chalcogenide materials crystallising in the kesterite crystal structure. Prime examples for the latter are Cu2ZnSnS4, Cu2ZnSnSe4, and their solid solution Cu2ZnSn(SxSe1-x)(4), where actual devices already demonstrated power conversion efficiencies of about 13 %. However, in their naturally occurring kesterite crystal structure, the so-called Cu-Zn disorder plays an important role and impacts the structural, electronic, and optical properties. To understand the influence of Cu-Zn disorder, we perform first-principles calculations based on density functional theory combined with special quasirandom structures to accurately model the cation disorder. Since the electronic band gaps and derived optical properties are severely underestimated by (semi)local exchange and correlation functionals, supplementary hybrid functional calculations have been performed. Concerning the latter, we additionally employ a recently devised technique to speed up structural relaxations for hybrid functional calculations. Our calculations show that the Cu-Zn disorder leads to a slight increase in the unit cell volume compared to the conventional kesterite structure showing full cation order, and that the band gap gets reduced by about 0.2 eV, which is in very good agreement with earlier experimental and theoretical findings. Our detailed results on structural, electronic, and optical properties will be discussed with respect to available experimental data, and will provide further insights into the atomistic origin of the disorder-induced band gap lowering in these promising kesterite type materials.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
Following excited-state chemical shifts in molecular ultrafast x-ray photoelectron spectroscopy
(2022)
The conversion of photon energy into other energetic forms in molecules is accompanied by charge moving on ultrafast timescales. We directly observe the charge motion at a specific site in an electronically excited molecule using time-resolved x-ray photoelectron spectroscopy (TR-XPS). We extend the concept of static chemical shift from conventional XPS by the excited-state chemical shift (ESCS), which is connected to the charge in the framework of a potential model. This allows us to invert TR-XPS spectra to the dynamic charge at a specific atom. We demonstrate the power of TR-XPS by using sulphur 2p-core-electron-emission probing to study the UV-excited dynamics of 2-thiouracil. The method allows us to discover that a major part of the population relaxes to the molecular ground state within 220–250 fs. In addition, a 250-fs oscillation, visible in the kinetic energy of the TR-XPS, reveals a coherent exchange of population among electronic states.
The aim of this work is the study of silica Arrayed Waveguide Gratings (AWGs) in the context of applications in astronomy. The specific focus lies on the investigation of the feasibility and technology limits of customized silica AWG devices for high resolution near-infrared spectroscopy. In a series of theoretical and experimental studies, AWG devices of varying geometry, foot-print and spectral resolution are constructed, simulated using a combination of a numerical beam propagation method and Fraunhofer diffraction and fabricated devices are characterized with respect to transmission efficiency, spectral resolution and polarization sensitivity. The impact of effective index non-uniformities on the performance of high-resolution AWG devices is studied numerically. Characterization results of fabricated devices are used to extrapolate the technology limits of the silica platform. The important issues of waveguide birefringence and defocus aberration are discussed theoretically and addressed experimentally by selection of an appropriate aberration-minimizing anastigmatic AWG layout structure. The drawbacks of the anastigmatic AWG geometry are discussed theoretically. From the results of the experimental studies, it is concluded that fabrication-related phase errors and waveguide birefringence are the primary limiting factors for the growth of AWG spectral resolution. It is shown that, without post-processing, the spectral resolving power is phase-error-limited to R < 40, 000 and, in the case of unpolarized light, birefringence-limited to R < 30, 000 in the AWG devices presented in this work. Necessary measures, such as special waveguide geometries and post-fabrication phase error correction are proposed for future designs. The elimination of defocus aberration using an anastigmatic AWG geometry is successfully demonstrated in experiment. Finally, a novel, non-planar dispersive in-fibre waveguide structure is proposed, discussed and studied theoretically.
In this thesis, I present my contributions to the field of ultrafast molecular spectroscopy. Using the molecule 2-thiouracil as an example, I use ultrashort x-ray pulses from free- electron lasers to study the relaxation dynamics of gas-phase molecular samples. Taking advantage of the x-ray typical element- and site-selectivity, I investigate the charge flow and geometrical changes in the excited states of 2-thiouracil.
In order to understand the photoinduced dynamics of molecules, knowledge about the ground-state structure and the relaxation after photoexcitation is crucial. Therefore, a part of this thesis covers the electronic ground-state spectroscopy of mainly 2-thiouracil to provide the basis for the time-resolved experiments. Many of the previously published studies that focused on the gas-phase time-resolved dynamics of thionated uracils after UV excitation relied on information from solution phase spectroscopy to determine the excitation energies. This is not an optimal strategy as solvents alter the absorption spec- trum and, hence, there is no guarantee that liquid-phase spectra resemble the gas-phase spectra. Therefore, I measured the UV-absorption spectra of all three thionated uracils to provide a gas-phase reference and, in combination with calculations, we determined the excited states involved in the transitions.
In contrast to the UV absorption, the literature on the x-ray spectroscopy of thionated uracil is sparse. Thus, we measured static photoelectron, Auger-Meitner and x-ray absorption spectra on the sulfur L edge before or parallel to the time-resolved experiments we performed at FLASH (DESY, Hamburg). In addition, (so far unpublished) measurements were performed at the synchrotron SOLEIL (France) which have been included in this thesis and show the spin-orbit splitting of the S 2p photoline and its satellite which was not observed at the free-electron laser.
The relaxation of 2-thiouracil has been studied extensively in recent years with ultrafast visible and ultraviolet methods showing the ultrafast nature of the molecular process after photoexcitation. Ultrafast spectroscopy probing the core-level electrons provides a complementary approach to common optical ultrafast techniques. The method inherits its local sensitivity from the strongly localised core electrons. The core energies and core-valence transitions are strongly affected by local valence charge and geometry changes, and past studies have utilised this sensitivity to investigate the molecular process reflected by the ultrafast dynamics. We have built an apparatus that provides the requirements to perform time-resolved x-ray spectroscopy on molecules in the gas phase. With the apparatus, we performed UV-pump x-ray-probe electron spectroscopy on the S 2p edge of 2-thiouracil using the free-electron laser FLASH2. While the UV triggers the relaxation dynamics, the x-ray probes the single sulfur atom inside the molecule. I implemented photoline self-referencing for the photoelectron spectral analysis. This minimises the spectral jitter of the FEL, which is due to the underlying self-amplified spontaneous emission (SASE) process. With this approach, we were not only able to study dynamical changes in the binding energy of the electrons but also to detect an oscillatory behaviour in the shift of the observed photoline, which we associate with non-adiabatic dynamics involving several electronic states. Moreover, we were able to link the UV-induced shift in binding energy to the local charge flow at the sulfur which is directly connected to the electronic state. Furthermore, the analysis of the Auger-Meitner electrons shows that energy shifts observed at early stages of the photoinduced relaxation are related to the geometry change in the molecule. More specifically, the observed increase in kinetic energy of the Auger-Meitner electrons correlates with a previously predicted C=S bond stretch.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
In this paper, the phenomenon of light-driven diffusioosmotic (DO) long-range attractive and repulsive interactions between micro-sized objects trapped near a solid wall is investigated. The range of the DO flow extends several times the size of microparticles and can be adjusted to point towards or away from the particle by varying irradiation parameters such as intensity or wavelength of light. The "fuel" of the light-driven DO flow is a photosensitive surfactant which can be photo-isomerized between trans and cis-states. The trans-isomer tends to accumulate at the interface, while the cis-isomer prefers to stay in solution. In combination with a dissimilar photo-isomerization rate at the interface and in bulk, this yields a concentration gradient of the isomers around single particles resulting in local light-driven diffusioosmotic (l-LDDO) flow. Here, the extended analysis of the l-LDDO flow as a function of irradiation parameters by introducing time-dependent development of the concentration excess of isomers near the particle surface is presented. It is also demonstrated that the l-LDDO can be generated at any solid/liquid interface being more pronounced in the case of strongly absorbing material. This phenomenon has plenty of potential applications since it makes any type of surface act as a micropump.
The random nature of self-amplified spontaneous emission (SASE) is a well-known challenge for x-ray core level spectroscopy at SASE free-electron lasers (FELs). Especially in time-resolved experiments that require a combination of good temporal and spectral resolution the jitter and drifts in the spectral characteristics, relative arrival time as well as power fluctuations can smear out spectral-temporal features. We present a combination of methods for the analysis of time-resolved photoelectron spectra based on power and time corrections as well as self-referencing of a strong photoelectron line. Based on sulfur 2p photoelectron spectra of 2-thiouracil taken at the SASE FEL FLASH2, we show that it is possible to correct for some of the photon energy drift and jitter even when reliable shot-to-shot photon energy data is not available. The quality of pump-probe difference spectra improves as random jumps in energy between delay points reduce significantly. The data analysis allows to identify coherent oscillations of 1 eV shift on the mean photoelectron line of 4 eV width with an error of less than 0.1 eV.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.
Isoflux tension propagation (IFTP) theory and Langevin dynamics (LD) simulations are employed to study the dynamics of channel-driven polymer translocation in which a polymer translocates into a narrow channel and the monomers in the channel experience a driving force fc. In the high driving force limit, regardless of the channel width, IFTP theory predicts τ ∝ f βc for the translocation time, where β = −1 is the force scaling exponent. Moreover, LD data show that for a very narrow channel fitting only a single file of monomers, the entropic force due to the subchain inside the channel does not play a significant role in the translocation dynamics and the force exponent β = −1 regardless of the force magnitude. As the channel width increases the number of possible spatial configurations of the subchain inside the channel becomes significant and the resulting entropic force causes the force exponent to drop below unity.