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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.
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.
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.
Beim Resonanzenergietransfer werden Fotonen von einem angeregten Donator über einen Wechselwirkungsabstand auf einen Akzeptor übertragen. Nach der quantenmechanischen Theorie von FÖRSTER kann dieser Abstand mit Hilfe des Überlappungsintegrals von Fluoreszenzspektrum des Donators und Absorp-tionsspektrum des Akzeptors berechnet werden.
Eine andere Möglichkeit der Bestimmung erhält man mit Hilfe von statistischen Modellen, die in einem Überblick zusammengestellt sind. Dabei kann der Abstand durch Auswertung der Löschkurve bestimmt werden.
In dieser Arbeit wird dazu eine weitere statistische Variante der Bestimmung des Wechselwirkungsradius hinzugefügt und an einem Beispiel ausführlich demonstriert.
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.
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.
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
Beim Resonanzenergietransfer werden Fotonen von einem angeregten Donator über einen Wechselwirkungsabstand auf einen Akzeptor übertragen. Nach der quantenmechanischen Theorie von FÖRSTER kann dieser Abstand mit Hilfe des Überlappungsintegrals von Fluoreszenzspektrum des Donators und Absorp-tionsspektrum des Akzeptors berechnet werden.
Eine andere Möglichkeit der Bestimmung erhält man mit Hilfe von statistischen Modellen, die in einem Überblick zusammengestellt sind. Dabei kann der Abstand durch Auswertung der Löschkurve bestimmt werden.
In dieser Arbeit wird dazu eine weitere statistische Variante der Bestimmung des Wechselwirkungsradius hinzugefügt und an einem Beispiel ausführlich demonstriert.
It has been experimentally demonstrated that reaction rates for molecules embedded in microfluidic optical cavities are altered when compared to rates observed under "ordinary" reaction conditions. However, precise mechanisms of how strong coupling of an optical cavity mode to molecular vibrations affects the reactivity and how resonance behavior emerges are still under dispute. In the present work, we approach these mechanistic issues from the perspective of a thermal model reaction, the inversion of ammonia along the umbrella mode, in the presence of a single-cavity mode of varying frequency and coupling strength. A topological analysis of the related cavity Born-Oppenheimer potential energy surface in combination with quantum mechanical and transition state theory rate calculations reveals two quantum effects, leading to decelerated reaction rates in qualitative agreement with experiments: the stiffening of quantized modes perpendicular to the reaction path at the transition state, which reduces the number of thermally accessible reaction channels, and the broadening of the barrier region, which attenuates tunneling. We find these two effects to be very robust in a fluctuating environment, causing statistical variations of potential parameters, such as the barrier height. Furthermore, by solving the time-dependent Schrodinger equation in the vibrational strong coupling regime, we identify a resonance behavior, in qualitative agreement with experimental and earlier theoretical work. The latter manifests as reduced reaction probability when the cavity frequency omega(c) is tuned resonant to a molecular reactant frequency. We find this effect to be based on the dynamical localization of the vibro-polaritonic wavepacket in the reactant well.
The detection of internal irregularities is crucial for quality assessment in metal-based additive manufacturing (AM) technologies such as laser powder bed fusion (L-PBF). The utilization of in-process thermography as an in situ monitoring tool in combination with post-process X-ray micro computed tomography (XCT) as a reference technique has shown great potential for this aim. Due to the small irregularity dimensions, a precise registration of the datasets is necessary as a requirement for correlation. In this study, the registration of thermography and XCT reference datasets of a cylindric specimen containing keyhole pores is carried out for the development of a porosity prediction model. The considered datasets show variations in shape, data type and dimensionality, especially due to shrinkage and material elevation effects present in the manufactured part. Since the resulting deformations are challenging for registration, a novel preprocessing methodology is introduced that involves an adaptive volume adjustment algorithm which is based on the porosity distribution in the specimen. Thus, the implementation of a simple three-dimensional image-to-image registration is enabled. The results demonstrate the influence of the part deformation on the resulting porosity location and the importance of registration in terms of irregularity prediction.
Surface-enhanced Raman scattering (SERS) is an effective and widely used technique to study chemical reactions induced or catalyzed by plasmonic substrates, since the experimental setup allows us to trigger and track the reaction simultaneously and identify the products. However, on substrates with plasmonic hotspots, the total signal mainly originates from these nanoscopic volumes with high reactivity and the information about the overall consumption remains obscure in SERS measurements. This has important implications; for example, the apparent reaction order in SERS measurements does not correlate with the real reaction order, whereas the apparent reaction rates are proportional to the real reaction rates as demonstrated by finite-difference time-domain (FDTD) simulations. We determined the electric field enhancement distribution of a gold nanoparticle (AuNP) monolayer and calculated the SERS intensities in light-driven reactions in an adsorbed self-assembled molecular monolayer on the AuNP surface. Accordingly, even if a high conversion is observed in SERS due to the high reactivity in the hotspots, most of the adsorbed molecules on the AuNP surface remain unreacted. The theoretical findings are compared with the hot-electron-induced dehalogenation of 4-bromothiophenol, indicating a time dependency of the hot-carrier concentration in plasmon-mediated reactions. To fit the kinetics of plasmon-mediated reactions in plasmonic hotspots, fractal-like kinetics are well suited to account for the inhomogeneity of reactive sites on the substrates, whereas also modified standard kinetics model allows equally well fits. The outcomes of this study are on the one hand essential to derive a mechanistic understanding of reactions on plasmonic substrates by SERS measurements and on the other hand to drive plasmonic reactions with high local precision and facilitate the engineering of chemistry on a nanoscale.
Modelling of an open quantum system requires knowledge of parameters that specify how it couples to its environment. However, beyond relaxation rates, realistic parameters for specific environments and materials are rarely known. Here we present a method of inferring the coupling between a generic system and its bosonic (e.g., phononic) environment from the experimentally measurable density of states (DOS). With it we confirm that the DOS of the well-known Debye model for three-dimensional solids is physically equivalent to choosing an Ohmic bath. We further match a real phonon DOS to a series of Lorentzian coupling functions, allowing us to determine coupling parameters for gold, yttrium iron garnet (YIG) and iron as examples. The results illustrate how to obtain material-specific dynamical properties, such as memory kernels. The proposed method opens the door to more accurate modelling of relaxation dynamics, for example for phonon-dominated spin damping in magnetic materials.
In recent years, gravitational-wave astronomy has motivated increasingly accurate perturbative studies of gravitational dynamics in compact binaries. This in turn has enabled more detailed analyses of the dynamical black holes in these systems. For example, Pound et al. [Phys. Rev. Lett. 124, 021101 (2020)] recently computed the surface area of a Schwarzschild black hole's apparent horizon, perturbed by an orbiting body, to second order in the binary's mass ratio. In this paper, we take that as the starting point for a comprehensive study of a perturbed Schwarzschild black hole's apparent and event horizon at second perturbative order, deriving generic formulas for the first- and second-order corrections to the horizons' radial profiles, surface areas, Hawking masses, and intrinsic curvatures. We find that the two horizons are remarkably similar, and that any teleological behavior of the event horizon is suppressed in several ways. Critically, we establish that at all orders, the perturbed event horizon in a small-mass-ratio binary is effectively localized in time. Even more pointedly, the event horizon is identical to the apparent horizon at linear order regardless of the source of perturbation, implying that the seemingly teleological "tidal lead," previously observed in linearly perturbed event horizons, is not genuinely teleological in origin. The two horizons do generically differ at second order, but their Hawking masses remain identical, implying that the event horizon obeys the same energy-flux balance law as the apparent horizon. At least in the case of a binary system, the difference between their surface areas remains extremely small even in the late stages of inspiral. In the course of our analysis, we also numerically illustrate puzzling behavior in the black hole's motion around the binary's center of mass.
Anomalous diffusion with a power-law time dependence vertical bar R vertical bar(2)(t) similar or equal to t(alpha i) of the mean squared displacement occurs quite ubiquitously in numerous complex systems. Often, this anomalous diffusion is characterised by crossovers between regimes with different anomalous diffusion exponents alpha(i). Here we consider the case when such a crossover occurs from a first regime with alpha(1) to a second regime with alpha(2) such that alpha(2) > alpha(1), i.e., accelerating anomalous diffusion. A widely used framework to describe such crossovers in a one-dimensional setting is the bi-fractional diffusion equation of the so-called modified type, involving two time-fractional derivatives defined in the Riemann-Liouville sense. We here generalise this bi-fractional diffusion equation to higher dimensions and derive its multidimensional propagator (Green's function) for the general case when also a space fractional derivative is present, taking into consideration long-ranged jumps (Levy flights). We derive the asymptotic behaviours for this propagator in both the short- and long-time as well the short- and long-distance regimes. Finally, we also calculate the mean squared displacement, skewness and kurtosis in all dimensions, demonstrating that in the general case the non-Gaussian shape of the probability density function changes.
A rigorous construction of the supersymmetric path integral associated to a compact spin manifold
(2022)
We give a rigorous construction of the path integral in N = 1/2 supersymmetry as an integral map for differential forms on the loop space of a compact spin manifold. It is defined on the space of differential forms which can be represented by extended iterated integrals in the sense of Chen and Getzler-Jones-Petrack. Via the iterated integral map, we compare our path integral to the non-commutative loop space Chern character of Guneysu and the second author. Our theory provides a rigorous background to various formal proofs of the Atiyah-Singer index theorem for twisted Dirac operators using supersymmetric path integrals, as investigated by Alvarez-Gaume, Atiyah, Bismut and Witten.
As the use of free electron laser (FEL) sources increases, so do the findings mentioning non-linear phenomena occurring at these experiments, such as saturable absorption, induced transparency and scattering breakdowns. These are well known among the laser community, but are still rarely understood and expected among the X-ray community and to date lack tools and theories to accurately predict the respective experimental parameters and results. We present a simple theoretical framework to access short X-ray pulse induced light- matter interactions which occur at intense short X-ray pulses as available at FEL sources. Our approach allows to investigate effects such as saturable absorption, induced transparency and scattering suppression, stimulated emission, and transmission spectra, while including the density of state influence relevant to soft X-ray spectroscopy in, for example, transition metal complexes or functional materials. This computationally efficient rate model based approach is intuitively adaptable to most solid state sample systems in the soft X-ray spectrum with the potential to be extended for liquid and gas sample systems as well. The feasibility of the model to estimate the named effects and the influence of the density of state is demonstrated using the example of CoPd transition metal systems at the Co edge. We believe this work is an important contribution for the preparation, performance, and understanding of FEL based high intensity and short pulse experiments, especially on functional materials in the soft X-ray spectrum.
Populations of globally coupled phase oscillators are described in the thermodynamic limit by kinetic equations for the distribution densities or, equivalently, by infinite hierarchies of equations for the order parameters. Ott and Antonsen [Chaos 18, 037113 (2008)] have found an invariant finite-dimensional subspace on which the dynamics is described by one complex variable per population. For oscillators with Cauchy distributed frequencies or for those driven by Cauchy white noise, this subspace is weakly stable and, thus, describes the asymptotic dynamics. Here, we report on an exact finite-dimensional reduction of the dynamics outside of the Ott-Antonsen subspace. We show that the evolution from generic initial states can be reduced to that of three complex variables, plus a constant function. For identical noise-free oscillators, this reduction corresponds to the Watanabe-Strogatz system of equations [Watanabe and Strogatz, Phys. Rev. Lett. 70, 2391 (1993)]. We discuss how the reduced system can be used to explore the transient dynamics of perturbed ensembles. Published under an exclusive license by AIP Publishing.
How does a systematic time-dependence of the diffusion coefficient D(t) affect the ergodic and statistical characteristics of fractional Brownian motion (FBM)? Here, we answer this question via studying the characteristics of a set of standard statistical quantifiers relevant to single-particle-tracking (SPT) experiments. We examine, for instance, how the behavior of the ensemble- and time-averaged mean-squared displacements-denoted as the standard MSD < x(2)(Delta)> and TAMSD <<(delta(2)(Delta))over bar>> quantifiers-of FBM featuring < x(2) (Delta >> = <<(delta(2)(Delta >)over bar>> proportional to Delta(2H) (where H is the Hurst exponent and Delta is the [lag] time) changes in the presence of a power-law deterministically varying diffusivity D-proportional to(t) proportional to t(alpha-1) -germane to the process of scaled Brownian motion (SBM)-determining the strength of fractional Gaussian noise. The resulting compound "scaled-fractional" Brownian motion or FBM-SBM is found to be nonergodic, with < x(2)(Delta >> proportional to Delta(alpha+)(2H)(-1) and <(delta 2(Delta >) over bar > proportional to Delta(2H). We also detect a stalling behavior of the MSDs for very subdiffusive SBM and FBM, when alpha + 2H - 1 < 0. The distribution of particle displacements for FBM-SBM remains Gaussian, as that for the parent processes of FBM and SBM, in the entire region of scaling exponents (0 < alpha < 2 and 0 < H < 1). The FBM-SBM process is aging in a manner similar to SBM. The velocity autocorrelation function (ACF) of particle increments of FBM-SBM exhibits a dip when the parent FBM process is subdiffusive. Both for sub- and superdiffusive FBM contributions to the FBM-SBM process, the SBM exponent affects the long-time decay exponent of the ACF. Applications of the FBM-SBM-amalgamated process to the analysis of SPT data are discussed. A comparative tabulated overview of recent experimental (mainly SPT) and computational datasets amenable for interpretation in terms of FBM-, SBM-, and FBM-SBM-like models of diffusion culminates the presentation. The statistical aspects of the dynamics of a wide range of biological systems is compared in the table, from nanosized beads in living cells, to chromosomal loci, to water diffusion in the brain, and, finally, to patterns of animal movements.
In this work, it is revealed how the photoinduced deformation of azobenzene containing polymers relates to the local direction of optomechanical stresses generated during irradiation with interference patterns (IPs). It can be substantiated by the modeling approach proposed by Saphiannikova et al., which describes the directional photodeformations in glassy side-chain azobenzene polymers, and proves that these deformations arise from the reorientation of rigid backbone segments along the light polarization direction. In experiments and modeling, surface relief gratings in pre-elongated photosensitive colloids of few micrometers length are inscribed using different IPs such as SS, PP, +/- 45, SP, RL, and LR. The deformation of colloidal particles is studied in situ, whereby the local variation of polymer topography is assigned to the local distribution of the electrical field vector for all IPs. Experimentally observed shapes are reproduced exactly with modeling azopolymer samples as visco-plastic bodies in the finite element software ANSYS. Orientation approach correctly predicts local variations of the main axis of light-induced stress in each interference pattern for both initially isotropic and highly oriented materials. With this work, it is suggested that the orientation approach implements a self-sufficient and convincing mechanism to describe photoinduced deformation in azopolymer films that in principle does not require auxiliary assumptions.
In this work, the fabrication and characterization of a simple, inexpensive, and effective microfluidic paper analytic device (mu PAD) for monitoring DNA samples is reported. The glass microfiber-based chip has been fabricated by a new wax-based transfer-printing technique and an electrode printing process. It is capable of moving DNA effectively in a time-dependent fashion. The nucleic acid sample is not damaged by this process and is accumulated in front of the anode, but not directly on the electrode. Thus, further DNA processing is feasible. The system allows the DNA to be purified by separating it from other components in sample mixtures such as proteins. Furthermore, it is demonstrated that DNA can be moved through several layers of the glass fiber material. This proof of concept will provide the basis for the development of rapid test systems, e.g., for the detection of pathogens in water samples.
A panoply of new tools for tracking single particles and molecules has led to an explosion of experimental data, leading to novel insights into physical properties of living matter governing cellular development and function, health and disease. In this Perspective, we present tools to investigate the dynamics and mechanics of living systems from the molecular to cellular scale via single-particle techniques. In particular, we focus on methods to measure, interpret, and analyse complex data sets that are associated with forces, materials properties, transport, and emergent organisation phenomena within biological and soft-matter systems. Current approaches, challenges, and existing solutions in the associated fields are outlined in order to support the growing community of researchers at the interface of physics and the life sciences. Each section focuses not only on the general physical principles and the potential for understanding living matter, but also on details of practical data extraction and analysis, discussing limitations, interpretation, and comparison across different experimental realisations and theoretical frameworks. Particularly relevant results are introduced as examples. While this Perspective describes living matter from a physical perspective, highlighting experimental and theoretical physics techniques relevant for such systems, it is also meant to serve as a solid starting point for researchers in the life sciences interested in the implementation of biophysical methods.
We develop an encounter-based approach for describing restricted diffusion with a gradient drift toward a partially reactive boundary. For this purpose, we introduce an extension of the Dirichlet-to-Neumann operator and use its eigenbasis to derive a spectral decomposition for the full propagator, i.e. the joint probability density function for the particle position and its boundary local time. This is the central quantity that determines various characteristics of diffusion-influenced reactions such as conventional propagators, survival probability, first-passage time distribution, boundary local time distribution, and reaction rate. As an illustration, we investigate the impact of a constant drift onto the boundary local time for restricted diffusion on an interval. More generally, this approach accesses how external forces may influence the statistics of encounters of a diffusing particle with the reactive boundary.
The electronic and magnetic excitations of bulk NiO have been determined using the 3A2g to 3T2g crystal-field transition at the Ni M2,3 edges with resonant inelastic x-ray scattering at 66.3- and 67.9-eV photon energies and 33-meV spectral resolution. Unambiguous assignment of the high-energy side of this state to a spin-flip satellite is achieved. We extract an effective exchange field of 89±4 meV in the 3T2g excited final state from empirical two-peak spin-flip model. The experimental data is found consistent with crystal-field model calculations using exchange fields of 60–100 meV. Full agreement with crystal-field multiplet calculations is achieved for the incident photon energy dependence of line shapes. The lower exchange parameter in the excited state as compared to the ground-state value of 120 meV is discussed in terms of the modification of the orbital occupancy (electronic effects) and of the structural dynamics: (A) With pure electronic effects, the lower exchange energy is attributed to the reduction in effective hopping integral. (B) With no electronic effects, we use the S = 1 Heisenberg model of antiferromagnetism to derive a second-nearest-neighbor exchange constant J2 = 14.8±0.6 meV. Based on the linear correlation between J2 and the lattice parameter from pressure-dependent experiments, an upper limit of 2% local Ni-O bond elongation during the femtosecond scattering duration is derived.
We propose a simple and eco-friendly method for the formation of composite protein-mineral-microcapsules induced by ultrasound treatment. Protein- and nanoparticle-stabilized oil-in-water (O/W) emulsions loaded with different oils are prepared using high-intensity ultrasound. The formation of thin composite mineral proteinaceous shells is realized with various types of nanoparticles, which are pre-modified with Bovine Serum Albumin (BSA) and subsequently characterized by EDX, TGA, zeta potential measurements and Raman spectroscopy. Cryo-SEM and EDX mapping visualizations show the homogeneous distribution of the densely packed nanoparticles in the capsule shell. In contrast to the results reported in our previous paper,(1) the shell of those nanostructured composite microcapsules is not cross-linked by the intermolecular disulfide bonds between BSA molecules. Instead, a Pickering-Emulsion formation takes place because of the amphiphilicity-driven spontaneous attachment of the BSA-modified nanoparticles at the oil/water interface. Using colloidal particles for the formation of the shell of the microcapsules, in our case silica, hydroxyapatite and calcium carbonate nanoparticles, is promising for the creation of new functional materials. The nanoparticulate building blocks of the composite shell with different chemical, physical or morphological properties can contribute to additional, sometimes even multiple, features of the resulting capsules. Microcapsules with shells of densely packed nanoparticles could find interesting applications in pharmaceutical science, cosmetics or in food technology.
The manufacturability of metallic alloys using laser-based additive manufacturing methods such as laser powder bed fusion has substantially improved within the last decade. However, local melting and solidification cause hierarchically structured and crystallographically textured microstructures possessing large residual stress. Such microstructures are not only the origin of mechanical anisotropy but also pose metrological challenges for the diffraction-based residual stress determination. Here we demonstrate the influence of the build orientation and the texture on the microstructure and consequently the mechanical anisotropy of as-built Inconel 718. For this purpose, we manufactured specimens with [001]/[011]-, [001]- and [011]/[11 (1) over bar]-type textures along their loading direction. In addition to changes in the Young's moduli, the differences in the crystallographic textures result in variations of the yield and ultimate tensile strengths. With this in mind, we studied the anisotropy on the micromechanical scale by subjecting the specimens to tensile loads along the different texture directions during in situ neutron diffraction experiments. In this context, the response of multiple lattice planes up to a tensile strain of 10% displayed differences in the load partitioning and the residual strain accumulation for the specimen with [011]/[(1) over bar 11]-type texture. However, the relative behavior of the specimens possessing an [001] /[011]- and [001]-type texture remained qualitatively similar. The consequences on the metrology of residual stress determination methods are discussed.
Neutrophil granulocytes are essential for the first host defense. After leaving the blood circulation they migrate efficiently towards sites of inflammation. They are guided by chemoattractants released from cells within the inflammatory foci. On a cellular level, directional migration is a consequence of cellular front-rear asymmetry which is induced by the concentration gradient of the chemoattractants. The generation and maintenance of this asymmetry, however, is not yet fully understood. Here we analyzed the paths of chemotacting neutrophils with different stochastic models to gain further insight into the underlying mechanisms. Wildtype chemotacting neutrophils show an anomalous superdiffusive behavior. CXCR2 blockade and TRPC6-knockout cause the tempering of temporal correlations and a reduction of chemotaxis. Importantly, such tempering is found both in vitro and in vivo. These findings indicate that the maintenance of anomalous dynamics is crucial for chemotactic behavior and the search efficiency of neutrophils.
The motility of neutrophils and their ability to sense and to react to chemoattractants in their environment are of central importance for the innate immunity. Neutrophils are guided towards sites of inflammation following the activation of G-protein coupled chemoattractant receptors such as CXCR2 whose signaling strongly depends on the activity of Ca2+ permeable TRPC6 channels. It is the aim of this study to analyze data sets obtained in vitro (murine neutrophils) and in vivo (zebrafish neutrophils) with a stochastic mathematical model to gain deeper insight into the underlying mechanisms. The model is based on the analysis of trajectories of individual neutrophils. Bayesian data analysis, including the covariances of positions for fractional Brownian motion as well as for exponentially and power-law tempered model variants, allows the estimation of parameters and model selection. Our model-based analysis reveals that wildtype neutrophils show pure superdiffusive fractional Brownian motion. This so-called anomalous dynamics is characterized by temporal long-range correlations for the movement into the direction of the chemotactic CXCL1 gradient. Pure superdiffusion is absent vertically to this gradient. This points to an asymmetric 'memory' of the migratory machinery, which is found both in vitro and in vivo. CXCR2 blockade and TRPC6-knockout cause tempering of temporal correlations in the chemotactic gradient. This can be interpreted as a progressive loss of memory, which leads to a marked reduction of chemotaxis and search efficiency of neutrophils. In summary, our findings indicate that spatially differential regulation of anomalous dynamics appears to play a central role in guiding efficient chemotactic behavior.
We report the detection of electron spin resonance (ESR) in individual dimers of the stable free radical 2,2,6,6tetramethyl-piperidine-1-oxyl (TEMPO). ESR is measured by the current fluctuations in a scanning tunneling microscope (ESR-STM method). The multipeak power spectra, distinct from macroscopic data, are assigned to dimers having exchange and Dzyaloshinskii-Moriya interactions in the presence of spin-orbit coupling. These interactions are generated in our model by interfering electronic tunneling pathways from tip to sample via the dimer???s two molecules. This is the first demonstration that tunneling via two spins is a valid mechanism of the ESR-STM method.
Levy walks are continuous-time random-walk processes with a spatiotemporal coupling of jump lengths and waiting times. We here apply the Hermite polynomial method to study the behavior of LWs with power-law walking time density for four different cases. First we show that the known result for the infinite density of an unconfined, unbiased LW is consistently recovered. We then derive the asymptotic behavior of the probability density function (PDF) for LWs in a constant force field, and we obtain the corresponding qth-order moments. In a harmonic external potential we derive the relaxation dynamic of the LW. For the case of a Poissonian walking time an exponential relaxation behavior is shown to emerge. Conversely, a power-law decay is obtained when the mean walking time diverges. Finally, we consider the case of an unconfined, unbiased LW with decaying speed v(r ) = v0/./r. When the mean walking time is finite, a universal Gaussian law for the position-PDF of the walker is obtained explicitly.
We derive. the ensemble-and time-averaged mean-squared displacements (MSD, TAMSD) for Poisson-reset geometric Brownian motion (GBM), in agreement with simulations. We find MSD and TAMSD saturation for frequent resetting, quantify the spread of TAMSDs via the ergodicity-breaking parameter and compute distributions of prices. General MSD-TAMSD nonequivalence proves reset GBM nonergodic.
About two decades ago it was discovered that systems of nonlocally coupled oscillators can exhibit unusual symmetry-breaking patterns composed of coherent and incoherent regions. Since then such patterns, called chimera states, have been the subject of intensive study but mostly in the stationary case when the coarse-grained system dynamics remains unchanged over time. Nonstationary coherence-incoherence patterns, in particular periodically breathing chimera states, were also reported, however not investigated systematically because of their complexity. In this paper we suggest a semi-analytic solution to the above problem providing a mathematical framework for the analysis of breathing chimera states in a ring of nonlocally coupled phase oscillators. Our approach relies on the consideration of an integro-differential equation describing the long-term coarse-grained dynamics of the oscillator system. For this equation we specify a class of solutions relevant to breathing chimera states. We derive a self-consistency equation for these solutions and carry out their stability analysis. We show that our approach correctly predicts macroscopic features of breathing chimera states. Moreover, we point out its potential application to other models which can be studied using the Ott-Antonsen reduction technique.
How do different reset protocols affect ergodicity of a diffusion process in single-particle-tracking experiments? We here address the problem of resetting of an arbitrary stochastic anomalous-diffusion process (ADP) from the general mathematical points of view and assess ergodicity of such reset ADPs for an arbitrary resetting protocol. The process of stochastic resetting describes the events of the instantaneous restart of a particle’s motion via randomly distributed returns to a preset initial position (or a set of those). The waiting times of such resetting events obey the Poissonian, Gamma, or more generic distributions with specified conditions regarding the existence of moments. Within these general approaches, we derive general analytical results and support them by computer simulations for the behavior of the reset mean-squared displacement (MSD), the new reset increment-MSD (iMSD), and the mean reset time-averaged MSD (TAMSD). For parental nonreset ADPs with the MSD(t)∝ tμ we find a generic behavior and a switch of the short-time growth of the reset iMSD and mean reset TAMSDs from ∝ _μ for subdiffusive to ∝ _1 for superdiffusive reset ADPs. The critical condition for a reset ADP that recovers its ergodicity is found to be more general than that for the nonequilibrium stationary state, where obviously the iMSD and the mean TAMSD are equal. The consideration of the new statistical quantifier, the iMSD—as compared to the standard MSD—restores the ergodicity of an arbitrary reset ADP in all situations when the μth moment of the waiting-time distribution of resetting events is finite. Potential applications of these new resetting results are, inter alia, in the area of biophysical and soft-matter systems.
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.
Focusing on transient chaos
(2022)
Recent advances in the field of complex, transiently chaotic dynamics are reviewed, based on the results published in the focus issue of J. Phys. Complex. on this topic. One group of achievements concerns network dynamics where transient features are intimately related to the degree and stability of synchronization, as well as to the network topology. A plethora of various applications of transient chaos are described, ranging from the collective motion of active particles, through the operation of power grids, cardiac arrhythmias, and magnetohydrodynamical dynamos, to the use of machine learning to predict time evolutions. Nontraditional forms of transient chaos are also explored, such as the temporal change of the chaoticity in the transients (called doubly transient chaos), as well as transients in systems subjected to parameter drift, the paradigm of which is climate change.
We introduce and study a Lévy walk (LW) model of particle spreading with a finite propagation speed combined with soft resets, stochastically occurring periods in which an harmonic external potential is switched on and forces the particle towards a specific position. Soft resets avoid instantaneous relocation of particles that in certain physical settings may be considered unphysical. Moreover, soft resets do not have a specific resetting point but lead the particle towards a resetting point by a restoring Hookean force. Depending on the exact choice for the LW waiting time density and the probability density of the periods when the harmonic potential is switched on, we demonstrate a rich emerging response behaviour including ballistic motion and superdiffusion. When the confinement periods of the soft-reset events are dominant, we observe a particle localisation with an associated non-equilibrium steady state. In this case the stationary particle probability density function turns out to acquire multimodal states. Our derivations are based on Markov chain ideas and LWs with multiple internal states, an approach that may be useful and flexible for the investigation of other generalised random walks with soft and hard resets. The spreading efficiency of soft-rest LWs is characterised by the first-passage time statistic.
Understanding the damping is an important fundamental problem with widespread implications in magnetic technology. Ferrimagnetic materials offer a rich platform to explore not only the damping of the ferromagnetic mode, but also the damping of the high-frequency exchange mode very promising for ultrafast devices. Here we use time-resolved magneto-optical Kerr effect to investigate the ferromagnetic and exchange resonance modes and their damping in the bismuth-doped gadolinium iron garnet over a broad range of magnetic fields (0-10 T) and temperatures (50-300 K) including the magnetization and angular compensation points. These two resonance modes are excited via the inverse Faraday effect and unambiguously identified by their distinct frequency dependence on temperature and magnetic field. The temperature-dependent measurements in the external magnetic field H-ext = 2 T revealed that the intrinsic damping of the ferromagnetic mode is always smaller than the one of the exchange modes and both have a maximum near the angular compensation point. These results are fully consistent with recent predictions of atomistic simulations and a theory based on two-sublattice Landau-Lifshitz-Bloch equation. We also demonstrate that the damping of these modes varies differently as a function of H-ext. We explain the observed behaviors by considering the different features of the effective fields defining the precession frequencies of the ferromagnetic and exchange modes.
We study a non-Markovian and nonstationary model of animal mobility incorporating both exploration and memory in the form of preferential returns. Exact results for the probability of visiting a given number of sites are derived and a practical WKB approximation to treat the nonstationary problem is developed. A mean-field version of this model, first suggested by Song et al., [Modelling the scaling properties of human mobility, Nat. Phys. 6, 818 (2010)] was shown to well describe human movement data. We show that our generalized model adequately describes empirical movement data of Egyptian fruit bats (Rousettus aegyptiacus) when accounting for interindividual variation in the population. We also study the probability of visiting any site a given number of times and derive a mean-field equation. Our analysis yields a remarkable phase transition occurring at preferential returns which scale linearly with past visits. Following empirical evidence, we suggest that this phase transition reflects a trade-off between extensive and intensive foraging modes.
We analyse mobile-immobile transport of particles that switch between the mobile and immobile phases with finite rates. Despite this seemingly simple assumption of Poissonian switching, we unveil a rich transport dynamics including significant transient anomalous diffusion and non-Gaussian displacement distributions. Our discussion is based on experimental parameters for tau proteins in neuronal cells, but the results obtained here are expected to be of relevance for a broad class of processes in complex systems. Specifically, we obtain that, when the mean binding time is significantly longer than the mean mobile time, transient anomalous diffusion is observed at short and intermediate time scales, with a strong dependence on the fraction of initially mobile and immobile particles. We unveil a Laplace distribution of particle displacements at relevant intermediate time scales. For any initial fraction of mobile particles, the respective mean squared displacement (MSD) displays a plateau. Moreover, we demonstrate a short-time cubic time dependence of the MSD for immobile tracers when initially all particles are immobile.
We introduce non-Markovian SIR epidemic spreading model inspired by the characteristics of the COVID-19, by considering discrete-and continuous-time versions. The distributions of infection intensity and recovery period may take an arbitrary form. By taking corresponding choice of these functions, it is shown that the model reduces to the classical Markovian case. The epidemic threshold is analytically determined for arbitrary functions of infectivity and recovery and verified numerically. The relevance of the model is shown by modeling the first wave of the epidemic in Italy, Spain and the UK, in the spring, 2020.
We study the diffusive motion of a particle in a subharmonic potential of the form U(x) = |x|( c ) (0 < c < 2) driven by long-range correlated, stationary fractional Gaussian noise xi ( alpha )(t) with 0 < alpha <= 2. In the absence of the potential the particle exhibits free fractional Brownian motion with anomalous diffusion exponent alpha. While for an harmonic external potential the dynamics converges to a Gaussian stationary state, from extensive numerical analysis we here demonstrate that stationary states for shallower than harmonic potentials exist only as long as the relation c > 2(1 - 1/alpha) holds. We analyse the motion in terms of the mean squared displacement and (when it exists) the stationary probability density function. Moreover we discuss analogies of non-stationarity of Levy flights in shallow external potentials.
Perovskite solar cells represent one of the recent success stories in photovoltaics. The device efficiency has been steadily increasing over the past years, but further work is needed to enhance the performance, for example, through the reduction of defects to prevent carrier recombination. SCAPS-1D simulations were performed to assess efficiency limits and identify approaches to decrease the impact of defects, through the selection of an optimal hole-transport material and a hole-collecting electrode. Particular attention was given to evaluation of the influence of bulk defects within light-absorbing CH3NH3SnI3 layers. In addition, the study demonstrates the influence of interface defects at the TiO2/CH3NH3SnI3 (IL1) and CH3NH3SnI3/HTL (IL2) interfaces across the similar range of defect densities. Finally, the optimal device architecture TiO2/CH3NH3SnI3/Cu2O is proposed for the given absorber layer using the readily available Cu2O hole-transporting material with PCE = 27.95%, FF = 84.05%, V-OC = 1.02 V and J(SC) = 32.60 mA/cm(2), providing optimal performance and enhanced resistance to defects.
Thanks to the combined effort s of scientist s in several research fields, the preceding decade has witnessed considerable progress in the use of conjugated polymers as emerging thermoelectric materials leading to significant improvements in performance and demonstration of a number of diverse applications. Despite these recent advances, systematic assessments of the impact of molecular design on thermoelectric properties are scarce. Although several reviews marginally highlight the role of chemical structure, the understanding of structure-performance relationships is still fragmented. An in-depth understanding of the relationship between molecular structure and thermoelectric properties will enable the rational design of next-generation thermoelectric polymers. To this end, this review showcases the state-of-the-art thermoelectric polymers, discusses structure-performance relationships, suggests strategies for improving thermoelectric performance that go beyond molecular design, and highlights some of the most impressive applications of thermoelectric polymers.
Motivated by recent epidemic outbreaks, including those of COVID-19, we solve the canonical problem of calculating the dynamics and likelihood of extensive outbreaks in a population within a large class of stochastic epidemic models with demographic noise, including the susceptible-infected-recovered (SIR) model and its general extensions.
In the limit of large populations, we compute the probability distribution for all extensive outbreaks, including those that entail unusually large or small (extreme) proportions of the population infected.
Our approach reveals that, unlike other well-known examples of rare events occurring in discrete-state stochastic systems, the statistics of extreme outbreaks emanate from a full continuum of Hamiltonian paths, each satisfying unique boundary conditions with a conserved probability flux.
Nanostructured silicon and silicon-aluminum compounds are synthesized by a novel synthesis strategy based on spark plasma sintering (SPS) of silicon nanopowder, mesoporous silicon (pSi), and aluminum nanopowder. The interplay of metal-assisted crystallization and inherent porosity is exploited to largely suppress thermal conductivity. Morphology and temperature-dependent thermal conductivity studies allow us to elucidate the impact of porosity and nanostructure on the macroscopic heat transport. Analytic electron microscopy along with quantitative image analysis is applied to characterize the sample morphology in terms of domain size and interpore distance distributions. We demonstrate that nanostructured domains and high porosity can be maintained in densified mesoporous silicon samples. In contrast, strong grain growth is observed for sintered nanopowders under similar sintering conditions. We observe that aluminum agglomerations induce local grain growth, while aluminum diffusion is observed in porous silicon and dispersed nanoparticles. A detailed analysis of the measured thermal conductivity between 300 and 773 K allows us to distinguish the effect of reduced thermal conductivity caused by porosity from the reduction induced by phonon scattering at nanosized domains. With a modified Landauer/Lundstrom approach the relative thermal conductivity and the scattering length are extracted. The relative thermal conductivity confirms the applicability of Kirkpatrick's effective medium theory. The extracted scattering lengths are in excellent agreement with the harmonic mean of log-normal distributed domain sizes and the interpore distances combined by Matthiessen's rule.
The application of the fractional calculus in the mathematical modelling of relaxation processes in complex heterogeneous media has attracted a considerable amount of interest lately.
The reason for this is the successful implementation of fractional stochastic and kinetic equations in the studies of non-Debye relaxation.
In this work, we consider the rotational diffusion equation with a generalised memory kernel in the context of dielectric relaxation processes in a medium composed of polar molecules. We give an overview of existing models on non-exponential relaxation and introduce an exponential resetting dynamic in the corresponding process.
The autocorrelation function and complex susceptibility are analysed in detail.
We show that stochastic resetting leads to a saturation of the autocorrelation function to a constant value, in contrast to the case without resetting, for which it decays to zero. The behaviour of the autocorrelation function, as well as the complex susceptibility in the presence of resetting, confirms that the dielectric relaxation dynamics can be tuned by an appropriate choice of the resetting rate.
The presented results are general and flexible, and they will be of interest for the theoretical description of non-trivial relaxation dynamics in heterogeneous systems composed of polar molecules.
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.
The photogeneration of free charges in light-harvesting devices is a multistep process, which can be challenging to probe due to the complexity of contributing energetic states and the competitive character of different driving mechanisms. In this contribution, we advance a technique, integral-mode transient charge extraction (ITCE), to probe these processes in thin-film solar cells. ITCE combines capacitance measurements with the integral-mode time-of-flight method in the low intensity regime of sandwich-type thin-film devices and allows for the sensitive determination of photogenerated charge-carrier densities. We verify the theoretical framework of our method by drift-diffusion simulations and demonstrate the applicability of ITCE to organic and perovskite semiconductor-based thin-film solar cells. Furthermore, we examine the field dependence of charge generation efficiency and find our ITCE results to be in excellent agreement with those obtained via time-delayed collection field measurements conducted on the same devices.
Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography-mass spectrometry.
The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged.
Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides.
Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number.
The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment.
Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.
Hot subdwarf B stars are core-helium-burning objects that have undergone envelope stripping, likely by a binary companion. Using high-speed photometry from the Transiting Exoplanet Survey Satellite, we have discovered the hot subdwarf BPM 36430 is a hybrid sdBV(rs) pulsator exhibiting several low-amplitude g-modes and a strong p-mode pulsation. The latter shows a clear, periodic variation in its pulse arrival times. Fits to this phase oscillation imply BPM 36430 orbits a barycenter approximately 10 light-seconds away once every 3.1 days. Using the CHIRON echelle spectrograph on the CTIO 1.5 m telescope, we confirm the reflex motion by detecting a radial-velocity variation with semiamplitude, period, and phase in agreement with the pulse timings. We conclude that a white dwarf companion with minimum mass of approximate to 0.42 M (circle dot) orbits BPM 36430. Our study represents only the second time a companion orbiting a pulsating hot subdwarf or white dwarf has been detected from pulse timings and confirmed with radial velocities.
In this study, we model a sequence of a confined and a full eruption, employing the relaxed end state of the confined eruption of a kink-unstable flux rope as the initial condition for the ejective one. The full eruption, a model of a coronal mass ejection, develops as a result of converging motions imposed at the photospheric boundary, which drive flux cancellation. In this process, parts of the positive and negative external flux converge toward the polarity inversion line, reconnect, and cancel each other. Flux of the same amount as the canceled flux transfers to a flux rope, increasing the free magnetic energy of the coronal field. With sustained flux cancellation and the associated progressive weakening of the magnetic tension of the overlying flux, we find that a flux reduction of approximate to 11% initiates the torus instability of the flux rope, which leads to a full eruption. These results demonstrate that a homologous full eruption, following a confined one, can be driven by flux cancellation.
In this paper, we present a study comparing the depth to diameter (d/D) ratio of small simple craters (200-1000 m) of an area between -88.5 degrees to -90 degrees latitude at the lunar south pole containing Permanent Shadowed Regions (PSRs) versus craters without PSRs. As PSRs can reach temperatures of 110 K and are capable of harboring volatiles, especially water ice, we analyzed the relationship of depth versus diameter ratios and its possible implications for harboring water ice. Variations in the d/D ratios can also be caused by other processes such as degradation, isostatic adjustment, or differences in surface properties. The conducted d/D ratio analysis suggests that a differentiation between craters containing PSRs versus craters without PSRs occurs. Thus, a possible direct relation between d/D ratio, PSRs, and water ice harboring might exist. Our results suggest that differences in the target's surface properties may explain the obtained results. The resulting d/D ratios of craters with PSRs can help to select target areas for future In-Situ Resource Utilization (ISRU) missions.