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- wahrgenommene Relevanz (1)
Institute
- Institut für Physik und Astronomie (246) (remove)
Stochastic models based on random diffusivities, such as the diffusing-diffusivity approach, are popular concepts for the description of non-Gaussian diffusion in heterogeneous media. Studies of these models typically focus on the moments and the displacement probability density function. Here we develop the complementary power spectral description for a broad class of random-diffusivity processes. In our approach we cater for typical single particle tracking data in which a small number of trajectories with finite duration are garnered. Apart from the diffusing-diffusivity model we study a range of previously unconsidered random-diffusivity processes, for which we obtain exact forms of the probability density function. These new processes are different versions of jump processes as well as functionals of Brownian motion. The resulting behaviour subtly depends on the specific model details. Thus, the central part of the probability density function may be Gaussian or non-Gaussian, and the tails may assume Gaussian, exponential, log-normal, or even power-law forms. For all these models we derive analytically the moment-generating function for the single-trajectory power spectral density. We establish the generic 1/f²-scaling of the power spectral density as function of frequency in all cases. Moreover, we establish the probability density for the amplitudes of the random power spectral density of individual trajectories. The latter functions reflect the very specific properties of the different random-diffusivity models considered here. Our exact results are in excellent agreement with extensive numerical simulations.
Context. The High Energy Stereoscopic System Galactic plane survey (HGPS) is to date the most comprehensive census of Galactic gamma -ray sources at very high energies (VHE; 100 GeV <= E <= 100 TeV). As a consequence of the limited sensitivity of this survey, the 78 detected gamma -ray sources comprise only a small and biased subsample of the overall population. The larger part consists of currently unresolved sources, which contribute to large-scale diffuse emission to a still uncertain amount.Aims. We study the VHE gamma -ray source population in the Milky Way. For this purpose population-synthesis models are derived based on the distributions of source positions, extents, and luminosities.Methods. Several azimuth-symmetric and spiral-arm models are compared for spatial source distribution. The luminosity and radius function of the population are derived from the source properties of the HGPS data set and are corrected for the sensitivity bias of the HGPS. Based on these models, VHE source populations are simulated and the subsets of sources detectable according to the HGPS are compared with HGPS sources.Results. The power-law indices of luminosity and radius functions are determined to range between -1.6 and -1.9 for luminosity and -1.1 and -1.6 for radius. A two-arm spiral structure with central bar is discarded as spatial distribution of VHE sources, while azimuth-symmetric distributions and a distribution following a four-arm spiral structure without bar describe the HGPS data reasonably well. The total number of Galactic VHE sources is predicted to be in the range from 800 to 7000 with a total luminosity and flux of (1.6-6.3) x 10(36) ph s(-1) and (3-15) x 10(-10) ph cm(-2) s(-1), respectively.Conclusions. Depending on the model, the HGPS sample accounts for (68-87)% of the emission of the population in the scanned region. This suggests that unresolved sources represent a critical component of the diffuse emission measurable in the HGPS. With the foreseen jump in sensitivity of the Cherenkov Telescope Array, the number of detectable sources is predicted to increase by a factor between 5 and 9.
Gold at the nanoscale
(2020)
In this cumulative dissertation, I want to present my contributions to the field of plasmonic nanoparticle science. Plasmonic nanoparticles are characterised by resonances of the free electron gas around the spectral range of visible light. In recent years, they have evolved as promising components for light based nanocircuits, light harvesting, nanosensors, cancer therapies, and many more.
This work exhibits the articles I authored or co-authored in my time as PhD student at the University of Potsdam. The main focus lies on the coupling between localised plasmons and excitons in organic dyes. Plasmon–exciton coupling brings light–matter coupling to the nanoscale. This size reduction is accompanied by strong enhancements of the light field which can, among others, be utilised to enhance the spectroscopic footprint of molecules down to single molecule detection, improve the efficiency of solar cells, or establish lasing on the nanoscale. When the coupling exceeds all decay channels, the system enters the strong coupling regime. In this case, hybrid light–matter modes emerge utilisable as optical switches, in quantum networks, or as thresholdless lasers. The present work investigates plasmon–exciton coupling in gold–dye core–shell geometries and contains both fundamental insights and technical novelties. It presents a technique which reveals the anticrossing in coupled systems without manipulating the particles themselves. The method is used to investigate the relation between coupling strength and particle size. Additionally, the work demonstrates that pure extinction measurements can be insufficient when trying to assess the coupling regime. Moreover, the fundamental quantum electrodynamic effect of vacuum induced saturation is introduced. This effect causes the vacuum fluctuations to diminish the polarisability of molecules and has not yet been considered in the plasmonic context.
The work additionally discusses the reaction of gold nanoparticles to optical heating. Such knowledge is of great importance for all potential optical applications utilising plasmonic nanoparticles since optical excitation always generates heat. This heat can induce a change in the optical properties, but also mechanical changes up to melting can occur. Here, the change of spectra in coupled plasmon–exciton particles is discussed and explained with a precise model. Moreover, the work discusses the behaviour of gold nanotriangles exposed to optical heating. In a pump–probe measurement, X-ray probe pulses directly monitored the particles’ breathing modes. In another experiment, the triangles were exposed to cw laser radiation with varying intensities and illumination areas. X-ray diffraction directly measured the particles’ temperature. Particle melting was investigated with surface enhanced Raman spectroscopy and SEM imaging demonstrating that larger illumination areas can cause melting at lower intensities. An elaborate methodological and theoretical introduction precedes the articles. This way, also readers without specialist’s knowledge get a concise and detailed overview of the theory and methods used in the articles. I introduce localised plasmons in metal nanoparticles of different shapes. For this work, the plasmons were mostly coupled to excitons in J-aggregates. Therefore, I discuss these aggregates of organic dyes with sharp and intense resonances and establish an understanding of the coupling between the two systems. For ab initio simulations of the coupled systems, models for the systems’ permittivites are presented, too. Moreover, the route to the sample fabrication – the dye coating of gold nanoparticles, their subsequent deposition on substrates, and the covering with polyelectrolytes – is presented together with the measurement methods that were used for the articles.
Classical option pricing schemes assume that the value of a financial asset follows a geometric Brownian motion (GBM). However, a growing body of studies suggest that a simple GBM trajectory is not an adequate representation for asset dynamics, due to irregularities found when comparing its properties with empirical distributions. As a solution, we investigate a generalisation of GBM where the introduction of a memory kernel critically determines the behaviour of the stochastic process. We find the general expressions for the moments, log-moments, and the expectation of the periodic log returns, and then obtain the corresponding probability density functions using the subordination approach. Particularly, we consider subdiffusive GBM (sGBM), tempered sGBM, a mix of GBM and sGBM, and a mix of sGBMs. We utilise the resulting generalised GBM (gGBM) in order to examine the empirical performance of a selected group of kernels in the pricing of European call options. Our results indicate that the performance of a kernel ultimately depends on the maturity of the option and its moneyness.
Perovskite photovoltaic (PV) cells have demonstrated power conversion efficiencies (PCE) that are close to those of monocrystalline silicon cells; however, in contrast to silicon PV, perovskites are not limited by Auger recombination under 1-sun illumination. Nevertheless, compared to GaAs and monocrystalline silicon PV, perovskite cells have significantly lower fill factors due to a combination of resistive and non-radiative recombination losses. This necessitates a deeper understanding of the underlying loss mechanisms and in particular the ideality factor of the cell. By measuring the intensity dependence of the external open-circuit voltage and the internal quasi-Fermi level splitting (QFLS), the transport resistance-free efficiency of the complete cell as well as the efficiency potential of any neat perovskite film with or without attached transport layers are quantified. Moreover, intensity-dependent QFLS measurements on different perovskite compositions allows for disentangling of the impact of the interfaces and the perovskite surface on the non-radiative fill factor and open-circuit voltage loss. It is found that potassium-passivated triple cation perovskite films stand out by their exceptionally high implied PCEs > 28%, which could be achieved with ideal transport layers. Finally, strategies are presented to reduce both the ideality factor and transport losses to push the efficiency to the thermodynamic limit.
Perovskite photovoltaic (PV) cells have demonstrated power conversion efficiencies (PCE) that are close to those of monocrystalline silicon cells; however, in contrast to silicon PV, perovskites are not limited by Auger recombination under 1-sun illumination. Nevertheless, compared to GaAs and monocrystalline silicon PV, perovskite cells have significantly lower fill factors due to a combination of resistive and non-radiative recombination losses. This necessitates a deeper understanding of the underlying loss mechanisms and in particular the ideality factor of the cell. By measuring the intensity dependence of the external open-circuit voltage and the internal quasi-Fermi level splitting (QFLS), the transport resistance-free efficiency of the complete cell as well as the efficiency potential of any neat perovskite film with or without attached transport layers are quantified. Moreover, intensity-dependent QFLS measurements on different perovskite compositions allows for disentangling of the impact of the interfaces and the perovskite surface on the non-radiative fill factor and open-circuit voltage loss. It is found that potassium-passivated triple cation perovskite films stand out by their exceptionally high implied PCEs > 28%, which could be achieved with ideal transport layers. Finally, strategies are presented to reduce both the ideality factor and transport losses to push the efficiency to the thermodynamic limit.
The development of methods such as super-resolution microscopy (Nobel prize in Chemistry, 2014) and multi-scale computer modelling (Nobel prize in Chemistry, 2013) have provided scientists with powerful tools to study microscopic systems. Sub-micron particles or even fluorescently labelled single molecules can now be tracked for long times in a variety of systems such as living cells, biological membranes, colloidal solutions etc. at spatial and temporal resolutions previously inaccessible. Parallel to such single-particle tracking experiments, super-computing techniques enable simulations of large atomistic or coarse-grained systems such as biologically relevant membranes or proteins from picoseconds to seconds, generating large volume of data. These have led to an unprecedented rise in the number of reported cases of anomalous diffusion wherein the characteristic features of Brownian motion—namely linear growth of the mean squared displacement with time and the Gaussian form of the probability density function (PDF) to find a particle at a given position at some fixed time—are routinely violated. This presents a big challenge in identifying the underlying stochastic process and also estimating the corresponding parameters of the process to completely describe the observed behaviour. Finding the correct physical mechanism which leads to the observed dynamics is of paramount importance, for example, to understand the first-arrival time of transcription factors which govern gene regulation, or the survival probability of a pathogen in a biological cell post drug administration. Statistical Physics provides useful methods that can be applied to extract such vital information. This cumulative dissertation, based on five publications, focuses on the development, implementation and application of such tools with special emphasis on Bayesian inference and large deviation theory. Together with the implementation of Bayesian model comparison and parameter estimation methods for models of diffusion, complementary tools are developed based on different observables and large deviation theory to classify stochastic processes and gather pivotal information. Bayesian analysis of the data of micron-sized particles traced in mucin hydrogels at different pH conditions unveiled several interesting features and we gained insights into, for example, how in going from basic to acidic pH, the hydrogel becomes more heterogeneous and phase separation can set in, leading to observed non-ergodicity (non-equivalence of time and ensemble averages) and non-Gaussian PDF. With large deviation theory based analysis we could detect, for instance, non-Gaussianity in seeming Brownian diffusion of beads in aqueous solution, anisotropic motion of the beads in mucin at neutral pH conditions, and short-time correlations in climate data. Thus through the application of the developed methods to biological and meteorological datasets crucial information is garnered about the underlying stochastic processes and significant insights are obtained in understanding the physical nature of these systems.
The PM6:Y6 bulk-heterojunction (BHJ) blend system achieves high short-circuit current (J(SC)) values in thick photovoltaic junctions. Here we analyse these solar cells to understand the observed independence of the short-circuit current upon photoactive layer thickness. We employ a range of optoelectronic measurements and analyses, including Mott-Schottky analysis, CELIV, photoinduced absorption spectroscopy, mobility measurements and simulations, to conclude that, the invariant photocurrent for the devices with different active layer thicknesses is associated with the Y6's diffusion length exceeding 300 nm in case of a 300 nm thick cell. This is despite unintentional doping that occurs in PM6 and the associated space-charge effect, which is expected to be even more profound upon photogeneration. This extraordinarily long diffusion length - which is an order of magnitude larger than typical values for organics - dominates transport in the flat-band region of thick junctions. Our work suggests that the performance of the doped PM6:Y6 organic solar cells resembles that of inorganic devices with diffusion transport playing a pivotal role. Ultimately, this is expected to be a key requirement for the fabrication of efficient, high-photocurrent, thick organic solar cells.
Low-dimensional description for ensembles of identical phase oscillators subject to Cauchy noise
(2020)
We study ensembles of globally coupled or forced identical phase oscillators subject to independent white Cauchy noise. We demonstrate that if the oscillators are forced in several harmonics, stationary synchronous regimes can be exactly described with a finite number of complex order parameters. The corresponding distribution of phases is a product of wrapped Cauchy distributions. For sinusoidal forcing, the Ott-Antonsen low-dimensional reduction is recovered.
Medientechnisches Wissen
(2020)
Das mehrbändige Lehrbuch vermittelt Studierenden und Medienwissenschaftlern eine Einführung aus den Naturwissenschaften, Ingenieurwissenschaften und Technik-Disziplinen. Dabei steht im Zentrum, die Lesekompetenz für die jeweilige Disziplin zu etablieren und zu verbessern, damit innerhalb medien- und kulturwissenschaftlicher Studienprogramme Fachtexte der einzelnen Disziplinen diskutiert werden können
We report on the adsorption kinetics of azoben-zene-containing surfactants on solid surfaces of different hydrophobicity. The understanding of this processes is of great importance for many interfacial phenomena that can be actuated and triggered by light, since the surfactant molecules contain a photoresponsive azobenzene group in their hydrophobic tail. Three surfactant types are studied, differing in the spacer connecting the headgroup and the azobenzene unit by between 6 and 10 CH2 groups. Under irradiation with light of a suitable wavelength, the azobenzene undergoes reversible photoisomerization between two states, a nonpolar trans-state and a highly polar cis-state. Consequently, the surfactant molecule changes its hydrophobicity and thus affinity to a surface depending on the photoisomerization state of the azobenzene. The adsorption behavior on hydrophilic (glass) and hydrophobic (TeflonAF) surfaces is analyzed using quartz crystal microbalance with dissipation (QCM-D) and zeta-potential measurements. At equilibrium, the adsorbed surfactant amount is almost twice as large on glass compared to TeflonAF for both isomers. The adsorption rate for the trans-isomers on both surfaces is similar, but the desorption rate of the trans-isomers is faster at the glass-water interface than at the Teflon-water interface. This result demonstrates that the trans-isomers have higher affinity for the glass surface, so the trans-to-cis ratios on glass and TeflonAF are 80/1 and 2/1, respectively, with similar trends for all three surfactant types.
We show that, although the equilibrium band dispersion of the Shockley-type surface state of two-dimensional Au(111) quantum films grown on W(110) does not deviate from the expected free-electron-like behavior, its nonequilibrium energy-momentum dispersion probed by time- and angle-resolved photoemission exhibits a remarkable kink above the Fermi level due to a significant enhancement of the effective mass. The kink is pronounced for certain thicknesses of the Au quantum well and vanishes in the very thin limit. We identify the kink as induced by the coupling between the Au(111) surface state and emergent quantum-well states which probe directly the buried gold-tungsten interface. The signatures of the coupling are further revealed by our time-resolved measurements which show that surface state and quantum-well states thermalize together behaving as dynamically locked electron populations. In particular, relaxation of hot carriers following laser excitation is similar for both surface state and quantum-well states and much slower than expected for a bulk metallic system. The influence of quantum confinement on the interplay between elementary scattering processes of the electrons at the surface and ultrafast carrier transport in the direction perpendicular to the surface is shown to be the reason for the slow electron dynamics.
We show that, although the equilibrium band dispersion of the Shockley-type surface state of two-dimensional Au(111) quantum films grown on W(110) does not deviate from the expected free-electron-like behavior, its nonequilibrium energy-momentum dispersion probed by time- and angle-resolved photoemission exhibits a remarkable kink above the Fermi level due to a significant enhancement of the effective mass. The kink is pronounced for certain thicknesses of the Au quantum well and vanishes in the very thin limit. We identify the kink as induced by the coupling between the Au(111) surface state and emergent quantum-well states which probe directly the buried gold-tungsten interface. The signatures of the coupling are further revealed by our time-resolved measurements which show that surface state and quantum-well states thermalize together behaving as dynamically locked electron populations. In particular, relaxation of hot carriers following laser excitation is similar for both surface state and quantum-well states and much slower than expected for a bulk metallic system. The influence of quantum confinement on the interplay between elementary scattering processes of the electrons at the surface and ultrafast carrier transport in the direction perpendicular to the surface is shown to be the reason for the slow electron dynamics.
A new ion mobility (IM) spectrometer, enabling mobility measurements in the pressure range between 5 and 500 mbar and in the reduced field strength range E/N of 5-90 Td, was developed and characterized. Reduced mobility (K-0) values were studied under low E/N (constant value) as well as high E/N (deviation from low field K-0) for a series of molecular ions in nitrogen. Infrared matrix-assisted laser desorption ionization (IR-MALDI) was used in two configurations: a source working at atmospheric pressure (AP) and, for the first time, an IR-MALDI source working with a liquid (aqueous) matrix at sub-ambient/reduced pressure (RP). The influence of RP on IR-MALDI was examined and new insights into the dispersion process were gained. This enabled the optimization of the IM spectrometer for best analytical performance. While ion desolvation is less efficient at RP, the transport of ions is more efficient, leading to intensity enhancement and an increased number of oligomer ions. When deciding between AP and RP IR-MALDI, a trade-off between intensity and resolving power has to be considered. Here, the low field mobility of peptide ions was first measured and compared with reference values from ESI-IM spectrometry (at AP) as well as collision cross sections obtained from molecular dynamics simulations. The second application was the determination of the reduced mobility of various substituted ammonium ions as a function of E/N in nitrogen. The mobility is constant up to a threshold at high E/N. Beyond this threshold, mobility increases were observed. This behavior can be explained by the loss of hydrated water molecules.
Corona and the climate
(2020)
The determination of the voltage-dependent density of free charge carriers via capacitance spectroscopy is considered an important step in the analysis of emerging photovoltaic technologies, such as organic and perovskite solar cells. In particular, an intimate knowledge of the density of free charge carriers is required for the determination of crucial parameters such as the effective mobility, charge carrier lifetime, nongeminate recombination coefficients, average extraction times, and competition factors. Hence, it is paramount to verify the validity of the commonly employed approaches to obtain the density of free charge carriers. The advantages, drawbacks, and limitations of the most common approaches are investigated in detail and strategies to mitigate misleading values are explored. To this end, two types of nonfullerene organic solar cells based on a PTB7-Th:ITIC-2F blend and a PM6:Y6 blend, respectively, are used as a case study to assess how subsequent analyses of the nongeminate recombination dynamics depend on the chosen approach to calculate the density of free charge carriers via capacitance spectroscopy.
Understanding the recombination dynamics of organic and perovskite solar cells has been a crucial prerequisite in the steadily increasing performance of these promising new types of photovoltaics. Surface recombination in particular has turned out to be one of the last remaining roadblocks, which specifically reduces the open circuit voltage. In this study, the relationship between the rate of surface recombination and the density of charge carriers is analyzed, revealing a cubic dependence between these two parameters. This hypothesis is then tested and verified with the recombination dynamics of an organic solar cell known to exhibit significant surface recombination and a high energy proton irradiated CH3NH3PbI3 pemvskite solar cell during white light illumination. Incidentally, these results can also explain recombination orders exceeding the commonly known threshold for bimolecular recombination that have been observed in some studies without the need for a charge carrier dependent bimolecular recombination coefficient.
Context.
Wide hot subdwarf B (sdB) binaries with main-sequence companions are outcomes of stable mass transfer from evolved red giants. The orbits of these binaries show a strong correlation between their orbital periods and mass ratios. The origins of this correlation have, so far, been lacking a conclusive explanation.
Aims.
We aim to find a binary evolution model which can explain the observed correlation.
Methods.
Radii of evolved red giants, and hence the resulting orbital periods, strongly depend on their metallicity. We performed a small but statistically significant binary population synthesis study with the binary stellar evolution code MESA. We used a standard model for binary mass loss and a standard metallicity history of the Galaxy. The resulting sdB systems were selected based on the same criteria as was used in observations and then compared with the observed population.
Results.
We have achieved an excellent match to the observed period-mass ratio correlation without explicitly fine-tuning any parameters. Furthermore, our models produce a very good match to the observed period-metallicity correlation. We predict several new correlations, which link the observed sdB binaries to their progenitors, and a correlation between the orbital period, metallicity, and core mass for subdwarfs and young low-mass helium white dwarfs. We also predict that sdB binaries have distinct orbital properties depending on whether they formed in the Galactic bulge, thin or thick disc, or the halo.
Conclusions
We demonstrate, for the first time, how the metallicity history of the Milky Way is imprinted in the properties of the observed post-mass transfer binaries. We show that Galactic chemical evolution is an important factor in binary population studies of interacting systems containing at least one evolved low-mass (M-init< 1.6 M-circle dot) component. Finally, we provide an observationally supported model of mass transfer from low-mass red giants onto main-sequence stars.
As one of the most-produced commodity polymers, polypropylene draws considerable scientific and commercial interest as an electret material. In the present thesis, the influence of the surface chemical modification and crystalline reconstruction on the electret properties of the polypropylene thin films will be discussed. The chemical treatment with orthophosphoric acid can significantly improve the surface charge stability of the polypropylene electrets by introducing phosphorus- and oxygen-containing structures onto the modified surface. The thermally stimulated discharge measurement and charge profiling by means of piezoelectrically generated pressure steps are used to investigate the electret behaviour. It is concluded that deep traps of limited number density are created during the treatment with inorganic chemicals. Hence, the improvement dramatically decreases when the surface-charge density is substantially higher than ±1.2×10^(-3) C·m^(-2). The newly formed traps also show a higher trapping energy for negative charges. The energetic distributions of the traps in the non-treated and chemically treated samples offer an insight regarding the surface and foreign-chemical dominance on the charge storage and transport in the polypropylene electrets.
Additionally, different electret properties are observed on the polypropylene films with the spherulitic and transcrystalline structures. It indicates the dependence of the charge storage and transport on the crystallite and molecular orientations in the crystalline phase. In general, a more diverse crystalline growth in the spherulitic samples can result in a more complex energetic trap distribution, in comparison to that in a transcrystalline polypropylene. The double-layer transcrystalline polypropylene film with a crystalline interface in the middle can be obtained by crystallising the film in contact with rough moulding surfaces on both sides. A layer of heterocharges appears on each side of the interface in the double-layer transcrystalline polypropylene electrets after the thermal poling. However, there is no charge captured within the transcrystalline layers. The phenomenon reveals the importance of the crystalline interface in terms of creating traps with the higher activation energy in polypropylene. The present studies highlight the fact that even slight variations in the polypropylene film may lead to dramatic differences in its electret properties.
Bipolar electrets from polypropylene (PP) are essential, e.g., in electret air filters and in cellular-foam ferroelectrets. Therefore, the mechanism of surface-charge stability enhancement on PP electrets via orthophosphoric-acid surface treatment is investigated in detail. It is shown that the significant charge-stability enhancement can be mainly attributed to deeper surface traps originating from deposited chemicals and topographic features on the modified surfaces. Thermally stimulated discharge of chemically treated and non-treated PP films with different surface-charge densities is used to test the limits of the newly formed deep traps in terms of the capacity for hosting surface charges. When the initial surface-charge density is very high, more charges are forced into shallower original traps on the surface or in the bulk of the treated PP samples, reducing the effect of the deeper surface traps brought by the surface modification. The well-known crossover phenomenon (of the surface-charge decay curves) has been observed between modified PP electrets charged to +/- 2kV and to +/- 3kV. Acoustically probed charge distributions in the thickness direction of PP electrets at different stages of thermal discharging indicate that the deep surface trapping sites may have preference for negative charges, resulting in the observed asymmetric charge stability of the modified PP films.
A double-layer transcrystalline polypropylene (PP) film with a flat central interface layer between its two transcrystalline layers is obtained by recrystallization from the melt between two polytetrafluoroethylene (PTFE) surfaces on both sides of the PP film. Its electret properties are studied and compared with those of a single-layer transcrystalline PP film re-crystallized in contact with only one PTFE surface. Within experimental uncertainty, the two types of transcrystalline films exhibit the same thermal properties and crystallinities. After thermal poling, however, two hetero-charge layers of opposite polarity are found on the internal interfaces of the double-layer transcrystalline films and may together be considered as micrometer-sized dipoles. The unexpected phenomenon does not occur in single-layer transcrystalline samples without a central interface layer, suggesting that the interfaces between the transcrystalline layers and the micrometer-thick central interface layer may be the origin of deeper traps rather than the crystalline structures in the transcrystallites or the spherulites. The origin of the interfacial charges was also studied by means of an injection-blocking charging method, which revealed that intrinsic charge carriers introduced during recrystallization are most likely responsible for the interfacial charges. It is fascinating that a material as familiar as PP can exhibit such intriguing properties with a special bipolar space-charge polarization across the central interface layer after quasi-epitaxial surface moulding into a double-layer transcrystalline form. In addition to applications in electret (micro-)devices for electro-mechanical transduction, the highly ordered structures may also be employed as a new paradigm for studying charge storage and transport in polymer electrets and in dielectrics for DC electrical insulation.
Inorganic perovskites with cesium (Cs+) as the cation have great potential as photovoltaic materials if their phase purity and stability can be addressed. Herein, a series of inorganic perovskites is studied, and it is found that the power conversion efficiency of solar cells with compositions CsPbI1.8Br1.2, CsPbI2.0Br1.0, and CsPbI2.2Br0.8 exhibits a high dependence on the initial annealing step that is found to significantly affect the crystallization and texture behavior of the final perovskite film. At its optimized annealing temperature, CsPbI1.8Br1.2 exhibits a pure orthorhombic phase and only one crystal orientation of the (110) plane. Consequently, this allows for the best efficiency of up to 14.6% and the longest operational lifetime, T-S80, of approximate to 300 h, averaged of over six solar cells, during the maximum power point tracking measurement under continuous light illumination and nitrogen atmosphere. This work provides essential progress on the enhancement of photovoltaic performance and stability of CsPbI3 - xBrx perovskite solar cells.
Inorganic perovskites with cesium (Cs+) as the cation have great potential as photovoltaic materials if their phase purity and stability can be addressed. Herein, a series of inorganic perovskites is studied, and it is found that the power conversion efficiency of solar cells with compositions CsPbI1.8Br1.2, CsPbI2.0Br1.0, and CsPbI2.2Br0.8 exhibits a high dependence on the initial annealing step that is found to significantly affect the crystallization and texture behavior of the final perovskite film. At its optimized annealing temperature, CsPbI1.8Br1.2 exhibits a pure orthorhombic phase and only one crystal orientation of the (110) plane. Consequently, this allows for the best efficiency of up to 14.6% and the longest operational lifetime, T-S80, of approximate to 300 h, averaged of over six solar cells, during the maximum power point tracking measurement under continuous light illumination and nitrogen atmosphere. This work provides essential progress on the enhancement of photovoltaic performance and stability of CsPbI3 - xBrx perovskite solar cells.
Numerous examples for a priori unexpected non-Gaussian behaviour for normal and anomalous diffusion have recently been reported in single-particle tracking experiments. Here, we address the case of non-Gaussian anomalous diffusion in terms of a random-diffusivity mechanism in the presence of power-law correlated fractional Gaussian noise. We study the ergodic properties of this model via examining the ensemble- and time-averaged mean-squared displacements as well as the ergodicity breaking parameter EB quantifying the trajectory-to-trajectory fluctuations of the latter. For long measurement times, interesting crossover behaviour is found as function of the correlation time tau characterising the diffusivity dynamics. We unveil that at short lag times the EB parameter reaches a universal plateau. The corresponding residual value of EB is shown to depend only on tau and the trajectory length. The EB parameter at long lag times, however, follows the same power-law scaling as for fractional Brownian motion. We also determine a corresponding plateau at short lag times for the discrete representation of fractional Brownian motion, absent in the continuous-time formulation. These analytical predictions are in excellent agreement with results of computer simulations of the underlying stochastic processes. Our findings can help distinguishing and categorising certain nonergodic and non-Gaussian features of particle displacements, as observed in recent single-particle tracking experiments.
Heterogeneous diffusion processes (HDPs) feature a space-dependent diffusivity of the form D(x) = D-0|x|(alpha). Such processes yield anomalous diffusion and weak ergodicity breaking, the asymptotic disparity between ensemble and time averaged observables, such as the mean-squared displacement. Fractional Brownian motion (FBM) with its long-range correlated yet Gaussian increments gives rise to anomalous and ergodic diffusion. Here, we study a combined model of HDPs and FBM to describe the particle dynamics in complex systems with position-dependent diffusivity driven by fractional Gaussian noise. This type of motion is, inter alia, relevant for tracer-particle diffusion in biological cells or heterogeneous complex fluids. We show that the long-time scaling behavior predicted theoretically and by simulations for the ensemble-and time-averaged mean-squared displacements couple the scaling exponents alpha of HDPs and the Hurst exponent H of FBM in a characteristic way. Our analysis of the simulated data in terms of the rescaled variable y similar to |x|(1/(2/(2-alpha)))/t(H) coupling particle position x and time t yields a simple, Gaussian probability density function (PDF), PHDP-FBM(y) = e(-y2)/root pi. Its universal shape agrees well with theoretical predictions for both uni- and bimodal PDF distributions.
The passive and active motion of micron-sized tracer particles in crowded liquids and inside living biological cells is ubiquitously characterised by 'viscoelastic' anomalous diffusion, in which the increments of the motion feature long-ranged negative and positive correlations. While viscoelastic anomalous diffusion is typically modelled by a Gaussian process with correlated increments, so-called fractional Gaussian noise, an increasing number of systems are reported, in which viscoelastic anomalous diffusion is paired with non-Gaussian displacement distributions. Following recent advances in Brownian yet non-Gaussian diffusion we here introduce and discuss several possible versions of random-diffusivity models with long-ranged correlations. While all these models show a crossover from non-Gaussian to Gaussian distributions beyond some correlation time, their mean squared displacements exhibit strikingly different behaviours: depending on the model crossovers from anomalous to normal diffusion are observed, as well as a priori unexpected dependencies of the effective diffusion coefficient on the correlation exponent. Our observations of the non-universality of random-diffusivity viscoelastic anomalous diffusion are important for the analysis of experiments and a better understanding of the physical origins of 'viscoelastic yet non-Gaussian' diffusion.
The passive and active motion of micron-sized tracer particles in crowded liquids and inside living biological cells is ubiquitously characterised by 'viscoelastic' anomalous diffusion, in which the increments of the motion feature long-ranged negative and positive correlations. While viscoelastic anomalous diffusion is typically modelled by a Gaussian process with correlated increments, so-called fractional Gaussian noise, an increasing number of systems are reported, in which viscoelastic anomalous diffusion is paired with non-Gaussian displacement distributions. Following recent advances in Brownian yet non-Gaussian diffusion we here introduce and discuss several possible versions of random-diffusivity models with long-ranged correlations. While all these models show a crossover from non-Gaussian to Gaussian distributions beyond some correlation time, their mean squared displacements exhibit strikingly different behaviours: depending on the model crossovers from anomalous to normal diffusion are observed, as well as a priori unexpected dependencies of the effective diffusion coefficient on the correlation exponent. Our observations of the non-universality of random-diffusivity viscoelastic anomalous diffusion are important for the analysis of experiments and a better understanding of the physical origins of 'viscoelastic yet non-Gaussian' diffusion.
After the United Kingdom has left the European Union it remains unclear whether the two parties can successfully negotiate and sign a trade agreement within the transition period. Ongoing negotiations, practical obstacles and resulting uncertainties make it highly unlikely that economic actors would be fully prepared to a “no-trade-deal” situation. Here we provide an economic shock simulation of the immediate aftermath of such a post-Brexit no-trade-deal scenario by computing the time evolution of more than 1.8 million interactions between more than 6,600 economic actors in the global trade network. We find an abrupt decline in the number of goods produced in the UK and the EU. This sudden output reduction is caused by drops in demand as customers on the respective other side of the Channel incorporate the new trade restriction into their decision-making. As a response, producers reduce prices in order to stimulate demand elsewhere. In the short term consumers benefit from lower prices but production value decreases with potentially severe socio-economic consequences in the longer term.
After the United Kingdom has left the European Union it remains unclear whether the two parties can successfully negotiate and sign a trade agreement within the transition period. Ongoing negotiations, practical obstacles and resulting uncertainties make it highly unlikely that economic actors would be fully prepared to a “no-trade-deal” situation. Here we provide an economic shock simulation of the immediate aftermath of such a post-Brexit no-trade-deal scenario by computing the time evolution of more than 1.8 million interactions between more than 6,600 economic actors in the global trade network. We find an abrupt decline in the number of goods produced in the UK and the EU. This sudden output reduction is caused by drops in demand as customers on the respective other side of the Channel incorporate the new trade restriction into their decision-making. As a response, producers reduce prices in order to stimulate demand elsewhere. In the short term consumers benefit from lower prices but production value decreases with potentially severe socio-economic consequences in the longer term.
Context.
Tycho's supernova remnant (SNR) is associated with the historical supernova (SN) event SN 1572 of Type Ia. The explosion occurred in a relatively clean environment, and was visually observed, providing an age estimate. This SNR therefore represents an ideal astrophysical test-bed for the study of cosmic-ray acceleration and related phenomena. A number of studies suggest that shock acceleration with particle feedback and very efficient magnetic-field amplification combined with Alfvenic drift are needed to explain the rather soft radio spectrum and the narrow rims observed in X-rays.
Aims.
We show that the broadband spectrum of Tycho's SNR can alternatively be well explained when accounting for stochastic acceleration as a secondary process. The re-acceleration of particles in the turbulent region immediately downstream of the shock should be efficient enough to impact particle spectra over several decades in energy. The so-called Alfvenic drift and particle feedback on the shock structure are not required in this scenario. Additionally, we investigate whether synchrotron losses or magnetic-field damping play a more profound role in the formation of the non-thermal filaments.
Methods.
We solved the full particle transport equation in test-particle mode using hydrodynamic simulations of the SNR plasma flow. The background magnetic field was either computed from the induction equation or follows analytic profiles, depending on the model considered. Fast-mode waves in the downstream region provide the diffusion of particles in momentum space.
Results.
We show that the broadband spectrum of Tycho can be well explained if magnetic-field damping and stochastic re-acceleration of particles are taken into account. Although not as efficient as standard diffusive shock acceleration, stochastic acceleration leaves its imprint on the particle spectra, which is especially notable in the emission at radio wavelengths. We find a lower limit for the post-shock magnetic-field strength similar to 330 mu G, implying efficient amplification even for the magnetic-field damping scenario. Magnetic-field damping is necessary for the formation of the filaments in the radio range, while the X-ray filaments are shaped by both the synchrotron losses and magnetic-field damping.
Perovskite solar cells have become one of the most studied systems in the quest for new, cheap and efficient solar cell materials. Within a decade device efficiencies have risen to >25% in single-junction and >29% in tandem devices on top of silicon. This rapid improvement was in many ways fortunate, as e. g. the energy levels of commonly used halide perovskites are compatible with already existing materials from other photovoltaic technologies such as dye-sensitized or organic solar cells. Despite this rapid success, fundamental working principles must be understood to allow concerted further improvements. This thesis focuses on a comprehensive understanding of recombination processes in functioning devices.
First the impact the energy level alignment between the perovskite and the electron transport layer based on fullerenes is investigated. This controversial topic is comprehensively addressed and recombination is mitigated through reducing the energy difference between the perovskite conduction band minimum and the LUMO of the fullerene. Additionally, an insulating blocking layer is introduced, which is even more effective in reducing this recombination, without compromising carrier collection and thus efficiency. With the rapid efficiency development (certified efficiencies have broken through the 20% ceiling) and thousands of researchers working on perovskite-based optoelectronic devices, reliable protocols on how to reach these efficiencies are lacking. Having established robust methods for >20% devices, while keeping track of possible pitfalls, a detailed description of the fabrication of perovskite solar cells at the highest efficiency level (>20%) is provided. The fabrication of low-temperature p-i-n structured devices is described, commenting on important factors such as practical experience, processing atmosphere & temperature, material purity and solution age. Analogous to reliable fabrication methods, a method to identify recombination losses is needed to further improve efficiencies. Thus, absolute photoluminescence is identified as a direct way to quantify the Quasi-Fermi level splitting of the perovskite absorber (1.21eV) and interfacial recombination losses the transport layers impose, reducing the latter to ~1.1eV. Implementing very thin interlayers at both the p- and n-interface (PFN-P2 and LiF, respectively), these losses are suppressed, enabling a VOC of up to 1.17eV. Optimizing the device dimensions and the bandgap, 20% devices with 1cm2 active area are demonstrated. Another important consideration is the solar cells’ stability if subjected to field-relevant stressors during operation. In particular these are heat, light, bias or a combination thereof. Perovskite layers – especially those incorporating organic cations – have been shown to degrade if subjected to these stressors. Keeping in mind that several interlayers have been successfully used to mitigate recombination losses, a family of perfluorinated self-assembled monolayers (X-PFCn, where X denotes I/Br and n = 7-12) are introduced as interlayers at the n-interface. Indeed, they reduce interfacial recombination losses enabling device efficiencies up to 21.3%. Even more importantly they improve the stability of the devices. The solar cells with IPFC10 are stable over 3000h stored in the ambient and withstand a harsh 250h of MPP at 85◦C without appreciable efficiency losses. To advance further and improve device efficiencies, a sound understanding of the photophysics of a device is imperative. Many experimental observations in recent years have however drawn an inconclusive picture, often suffering from technical of physical impediments, disguising e. g. capacitive discharge as recombination dynamics. To circumvent these obstacles, fully operational, highly efficient perovskites solar cells are investigated by a combination of multiple optical and optoelectronic probes, allowing to draw a conclusive picture of the recombination dynamics in operation. Supported by drift-diffusion simulations, the device recombination dynamics can be fully described by a combination of first-, second- and third-order recombination and JV curves as well as luminescence efficiencies over multiple illumination intensities are well described within the model. On this basis steady state carrier densities, effective recombination constants, densities-of-states and effective masses are calculated, putting the devices at the brink of the radiative regime. Moreover, a comprehensive review of recombination in state-of-the-art devices is given, highlighting the importance of interfaces in nonradiative recombination. Different strategies to assess these are discussed, before emphasizing successful strategies to reduce interfacial recombination and pointing towards the necessary steps to further improve device efficiency and stability. Overall, the main findings represent an advancement in understanding loss mechanisms in highly efficient solar cells. Different reliable optoelectronic techniques are used and interfacial losses are found to be of grave importance for both efficiency and stability. Addressing the interfaces, several interlayers are introduced, which mitigate recombination losses and degradation.
Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback.
Several large-scale cryosphere elements such as the Arctic summer sea ice, the mountain glaciers, the Greenland and West Antarctic Ice Sheet have changed substantially during the last century due to anthropogenic global warming. However, the impacts of their possible future disintegration on global mean temperature (GMT) and climate feedbacks have not yet been comprehensively evaluated. Here, we quantify this response using an Earth system model of intermediate complexity. Overall, we find a median additional global warming of 0.43 degrees C (interquartile range: 0.39-0.46 degrees C) at a CO2 concentration of 400 ppm. Most of this response (55%) is caused by albedo changes, but lapse rate together with water vapour (30%) and cloud feedbacks (15%) also contribute significantly. While a decay of the ice sheets would occur on centennial to millennial time scales, the Arctic might become ice-free during summer within the 21st century. Our findings imply an additional increase of the GMT on intermediate to long time scales. The disintegration of cryosphere elements such as the Arctic summer sea ice, mountain glaciers, Greenland and West Antarctica is associated with temperature and radiative feedbacks. In this work, the authors quantify these feedbacks and find an additional global warming of 0.43 degrees C.
To analyze stochastic processes, one often uses integral transform (Fourier and Laplace) methods. However, for the time-space coupled cases, e.g. the Levy walk, sometimes the integral transform method may fail. Here we provide a Hermite polynomial expansion approach, being complementary to the integral transform method, to the Levy walk. Two approaches are compared for some already known results. We also consider the generalized Levy walk with parameter dependent velocity. Namely, we consider the Levy walk with velocity which depends on the walking length or on the duration of each step. Some interesting features of the generalized Levy walk are observed, including the special shapes of the probability density function, the first passage time distributions, and various diffusive behaviors of the mean squared displacement.
Levy walks (LWs) are spatiotemporally coupled random-walk processes describing superdiffusive heat conduction in solids, propagation of light in disordered optical materials, motion of molecular motors in living cells, or motion of animals, humans, robots, and viruses. We here investigate a key feature of LWs-their response to an external harmonic potential. In this generic setting for confined motion we demonstrate that LWs equilibrate exponentially and may assume a bimodal stationary distribution. We also show that the stationary distribution has a horizontal slope next to a reflecting boundary placed at the origin, in contrast to correlated superdiffusive processes. Our results generalize LWs to confining forces and settle some longstanding puzzles around LWs.
Heterogeneous diffusion processes (HDPs) with space-dependent diffusion coefficients D(x) are found in a number of real-world systems, such as for diffusion of macromolecules or submicron tracers in biological cells. Here, we examine HDPs in quenched-disorder systems with Gaussian colored noise (GCN) characterized by a diffusion coefficient with a power-law dependence on the particle position and with a spatially random scaling exponent. Typically, D(x) is considered to be centerd at the origin and the entire x axis is characterized by a single scaling exponent a. In this work we consider a spatially random scenario: in periodic intervals ("layers") in space D(x) is centerd to the midpoint of each interval. In each interval the scaling exponent alpha is randomly chosen from a Gaussian distribution. The effects of the variation of the scaling exponents, the periodicity of the domains ("layer thickness") of the diffusion coefficient in this stratified system, and the correlation time of the GCN are analyzed numerically in detail. We discuss the regimes of superdiffusion, subdiffusion, and normal diffusion realisable in this system. We observe and quantify the domains where nonergodic and non-Gaussian behaviors emerge in this system. Our results provide new insights into the understanding of weak ergodicity breaking for HDPs driven by colored noise, with potential applications in quenched layered systems, typical model systems for diffusion in biological cells and tissues, as well as for diffusion in geophysical systems.
This paper presents a study of the surface properties of two Ce/Zr mixed oxides with different reducibility, obtained by applying distinct thermal ageing treatments to an oxide with the composition Ce0.62Zr0.38O2. The surface composition was investigated by XPS. Chemical reactivity of the surface was studied by adsorption of the probe molecules CO2, D-2 and methanol. Nanostructural characterization was carried out by XRD, Raman and high-resolution Eu3+ spectroscopy (FLNS). The characterization showed only slight variations in surface composition and bulk Ce-Zr distribution, but hardy differences concerning the type and strength of acidic surface centres, as well as strong differences in the ability to dissociate hydrogen. Structural variations between both samples were identified by comparing the optical spectra of Eu3+ in surface doped samples.
Excitable solitons
(2020)
Excitable pulses are among the most widespread dynamical patterns that occur in many different systems, ranging from biological cells to chemical reactions and ecological populations. Traditionally, the mutual annihilation of two colliding pulses is regarded as their prototypical signature. Here we show that colliding excitable pulses may exhibit solitonlike crossover and pulse nucleation if the system obeys a mass conservation constraint. In contrast to previous observations in systems without mass conservation, these alternative collision scenarios are robustly observed over a wide range of parameters. We demonstrate our findings using a model of intracellular actin waves since, on time scales of wave propagations over the cell scale, cells obey conservation of actin monomers. The results provide a key concept to understand the ubiquitous occurrence of actin waves in cells, suggesting why they are so common, and why their dynamics is robust and long-lived.
The Milky Way is a spiral galaxy consisting of a disc of gas, dust and stars embedded in a halo of dark matter. Within this dark matter halo there is also a diffuse population of stars called the stellar halo, that has been accreting stars for billions of years from smaller galaxies that get pulled in and disrupted by the large gravitational potential of the Milky Way. As they are disrupted, these galaxies leave behind long streams of stars that can take billions of years to mix with the rest of the stars in the halo. Furthermore, the amount of heavy elements (metallicity) of the stars in these galaxies reflects the rate of chemical enrichment that occurred in them, since the Universe has been slowly enriched in heavy elements (e.g. iron) through successive generations of stars which produce them in their cores and supernovae explosions. Therefore, stars that contain small amounts of heavy elements (metal-poor stars) either formed at early times before the Universe was significantly enriched, or in isolated environments. The aim of this thesis is to develop a better understanding of the substructure content and chemistry of the Galactic stellar halo, in order to gain further insight into the formation and evolution of the Milky Way.
The Pristine survey uses a narrow-band filter which specifically targets the Ca II H & K spectral absorption lines to provide photometric metallicities for a large number of stars down to the extremely metal-poor (EMP) regime, making it a very powerful data set for Galactic archaeology studies. In Chapter 2, we quantify the efficiency of the survey using a preliminary spectroscopic follow-up sample of ~ 200 stars. We also use this sample to establish a set of selection criteria to improve the success rate of selecting EMP candidates for follow-up spectroscopy. In Chapter 3, we extend this work and present the full catalogue of ~ 1000 stars from a three year long medium resolution spectroscopic follow-up effort conducted as part of the Pristine survey. From this sample, we compute success rates of 56% and 23% for recovering stars with [Fe/H] < -2.5 and [Fe/H] < -3.0, respectively. This demonstrates a high efficiency for finding EMP stars as compared to previous searches with success rates of 3-4%.
In Chapter 4, we select a sample of ~ 80000 halo stars using colour and magnitude cuts to select a main sequence turnoff population in the distance range 6 < dʘ < 20 kpc. We then use the spectroscopic follow-up sample presented in Chapter 3 to statistically rescale the Pristine photometric metallicities of this sample, and present the resulting corrected metallicity distribution function (MDF) of the halo. The slope at the metal-poor end is significantly shallower than previous spectroscopic efforts have shown, suggesting that there may be more metal-poor stars with [Fe/H] < -2.5 in the halo than previously thought. This sample also shows evidence that the MDF of the halo may not be bimodal as was proposed by previous works, and that the lack of globular clusters in the Milky Way may be the result of a physical truncation of the MDF rather than just statistical under-sampling.
Chapter 5 showcases the unexpected capability of the Pristine filter for separating blue horizontal branch (BHB) stars from Blue Straggler (BS) stars. We demonstrate a purity of 93% and completeness of 91% for identifying BHB stars, a substantial improvement over previous works. We then use this highly pure and complete sample of BHB stars to trace the halo density profile out to d > 100 kpc, and the Sagittarius stream substructure out to ~ 130 kpc.
In Chapter 6 we use the photometric metallicities from the Pristine survey to perform a clustering analysis of the halo as a function of metallicity. Separating the Pristine sample into four metallicity bins of [Fe/H] < -2, -2 < [Fe/H] < -1.5, -1.5 < [Fe/H] < -1 and -0.9 < [Fe/H] < -0.8, we compute the two-point correlation function to measure the amount of clustering on scales of < 5 deg. For a smooth comparison sample we make a mock Pristine data set generated using the Galaxia code based on the Besançon model of the Galaxy. We find enhanced clustering on small scales (< 0.5 deg) for some regions of the Galaxy for the most metal-poor bin ([Fe/H] < -2), while in others we see large scale signals that correspond to known substructures in those directions. This confirms that the substructure content of the halo is highly anisotropic and diverse in different Galactic environments. We discuss the difficulties of removing systematic clustering signals from the data and the limitations of disentangling weak clustering signals from real substructures and residual systematic structure in the data.
Taken together, the work presented in this thesis approaches the problem of better understanding the halo of our Galaxy from multiple angles. Firstly, presenting a sizeable sample of EMP stars and improving the selection efficiency of EMP stars for the Pristine survey, paving the way for the further discovery of metal-poor stars to be used as probes to early chemical evolution. Secondly, improving the selection of BHB distance tracers to map out the halo to large distances, and finally, using the large samples of metal-poor stars to derive the MDF of the inner halo and analyse the substructure content at different metallicities. The results of this thesis therefore expand our understanding of the physical and chemical properties of the Milky Way stellar halo, and provide insight into the processes involved in its formation and evolution.
Acceleration of the flow of ice drives mass losses in both the Antarctic and the Greenland Ice Sheet. The projections of possible future sea-level rise rely on numerical ice-sheet models, which solve the physics of ice flow, melt, and calving. While major advancements have been made by the ice-sheet modeling community in addressing several of the related uncertainties, the flow law, which is at the center of most process-based ice-sheet models, is not in the focus of the current scientific debate. However, recent studies show that the flow law parameters are highly uncertain and might be different from the widely accepted standard values. Here, we use an idealized flow-line setup to investigate how these uncertainties in the flow law translate into uncertainties in flow-driven mass loss. In order to disentangle the effect of future warming on the ice flow from other effects, we perform a suite of experiments with the Parallel Ice Sheet Model (PISM), deliberately excluding changes in the surface mass balance. We find that changes in the flow parameters within the observed range can lead up to a doubling of the flow-driven mass loss within the first centuries of warming, compared to standard parameters. The spread of ice loss due to the uncertainty in flow parameters is on the same order of magnitude as the increase in mass loss due to surface warming. While this study focuses on an idealized flow-line geometry, it is likely that this uncertainty carries over to realistic three-dimensional simulations of Greenland and Antarctica.
The plasmasphere is a dynamic region of cold, dense plasma surrounding the Earth. Its shape and size are highly susceptible to variations in solar and geomagnetic conditions. Having an accurate model of plasma density in the plasmasphere is important for GNSS navigation and for predicting hazardous effects of radiation in space on spacecraft. The distribution of cold plasma and its dynamic dependence on solar wind and geomagnetic conditions remain, however, poorly quantified. Existing empirical models of plasma density tend to be oversimplified as they are based on statistical averages over static parameters. Understanding the global dynamics of the plasmasphere using observations from space remains a challenge, as existing density measurements are sparse and limited to locations where satellites can provide in-situ observations. In this dissertation, we demonstrate how such sparse electron density measurements can be used to reconstruct the global electron density distribution in the plasmasphere and capture its dynamic dependence on solar wind and geomagnetic conditions.
First, we develop an automated algorithm to determine the electron density from in-situ measurements of the electric field on the Van Allen Probes spacecraft. In particular, we design a neural network to infer the upper hybrid resonance frequency from the dynamic spectrograms obtained with the Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite, which is then used to calculate the electron number density. The developed Neural-network-based Upper hybrid Resonance Determination (NURD) algorithm is applied to more than four years of EMFISIS measurements to produce the publicly available electron density data set.
We utilize the obtained electron density data set to develop a new global model of plasma density by employing a neural network-based modeling approach. In addition to the location, the model takes the time history of geomagnetic indices and location as inputs, and produces electron density in the equatorial plane as an output. It is extensively validated using in-situ density measurements from the Van Allen Probes mission, and also by comparing the predicted global evolution of the plasmasphere with the global IMAGE EUV images of He+ distribution. The model successfully reproduces erosion of the plasmasphere on the night side as well as plume formation and evolution, and agrees well with data.
The performance of neural networks strongly depends on the availability of training data, which is limited during intervals of high geomagnetic activity. In order to provide reliable density predictions during such intervals, we can employ physics-based modeling. We develop a new approach for optimally combining the neural network- and physics-based models of the plasmasphere by means of data assimilation. The developed approach utilizes advantages of both neural network- and physics-based modeling and produces reliable global plasma density reconstructions for quiet, disturbed, and extreme geomagnetic conditions.
Finally, we extend the developed machine learning-based tools and apply them to another important problem in the field of space weather, the prediction of the geomagnetic index Kp. The Kp index is one of the most widely used indicators for space weather alerts and serves as input to various models, such as for the thermosphere, the radiation belts and the plasmasphere. It is therefore crucial to predict the Kp index accurately. Previous work in this area has mostly employed artificial neural networks to nowcast and make short-term predictions of Kp, basing their inferences on the recent history of Kp and solar wind measurements at L1. We analyze how the performance of neural networks compares to other machine learning algorithms for nowcasting and forecasting Kp for up to 12 hours ahead. Additionally, we investigate several machine learning and information theory methods for selecting the optimal inputs to a predictive model of Kp. The developed tools for feature selection can also be applied to other problems in space physics in order to reduce the input dimensionality and identify the most important drivers.
Research outlined in this dissertation clearly demonstrates that machine learning tools can be used to develop empirical models from sparse data and also can be used to understand the underlying physical processes. Combining machine learning, physics-based modeling and data assimilation allows us to develop novel methods benefiting from these different approaches.
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
Organic photovoltaics based on non-fullerene acceptors (NFAs) show record efficiency of 16 to 17% and increased photovoltage owing to the low driving force for interfacial charge-transfer. However, the low driving force potentially slows down charge generation, leading to a tradeoff between voltage and current. Here, we disentangle the intrinsic charge-transfer rates from morphology-dependent exciton diffusion for a series of polymer:NFA systems. Moreover, we establish the influence of the interfacial energetics on the electron and hole transfer rates separately. We demonstrate that charge-transfer timescales remain at a few hundred femtoseconds even at near-zero driving force, which is consistent with the rates predicted by Marcus theory in the normal region, at moderate electronic coupling and at low re-organization energy. Thus, in the design of highly efficient devices, the energy offset at the donor:acceptor interface can be minimized without jeopardizing the charge-transfer rate and without concerns about a current-voltage tradeoff.
The remarkable progress of metal halide perovskites in photovoltaics has led to the power conversion efficiency approaching 26%. However, practical applications of perovskite-based solar cells are challenged by the stability issues, of which the most critical one is photo-induced degradation. Bare CH3NH3PbI3 perovskite films are known to decompose rapidly, with methylammonium and iodine as volatile species and residual solid PbI2 and metallic Pb, under vacuum under white light illumination, on the timescale of minutes. We find, in agreement with previous work, that the degradation is non-uniform and proceeds predominantly from the surface, and that illumination under N-2 and ambient air (relative humidity 20%) does not induce substantial degradation even after several hours. Yet, in all cases the release of iodine from the perovskite surface is directly identified by X-ray photoelectron spectroscopy. This goes in hand with a loss of organic cations and the formation of metallic Pb. When CH3NH3PbI3 films are covered with a few nm thick organic capping layer, either charge selective or non-selective, the rapid photodecomposition process under ultrahigh vacuum is reduced by more than one order of magnitude, and becomes similar in timescale to that under N-2 or air. We conclude that the light-induced decomposition reaction of CH3NH3PbI3, leading to volatile methylammonium and iodine, is largely reversible as long as these products are restrained from leaving the surface. This is readily achieved by ambient atmospheric pressure, as well as a thin organic capping layer even under ultrahigh vacuum. In addition to explaining the impact of gas pressure on the stability of this perovskite, our results indicate that covalently "locking" the position of perovskite components at the surface or an interface should enhance the overall photostability.