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- Institut für Physik und Astronomie (1480) (remove)
Charge extraction methods are popular for measuring the charge carrier density in thin film organic solar cells and to draw conclusions about the order and coefficient of nongeminate charge recombination. However, results from such studies may be falsified by inhomogeneous steady state carrier profiles or surface recombination. Here, we present a detailed drift-diffusion study of two charge extraction methods, bias-assisted charge extraction (BACE) and time-delayed collection field (TDCF). Simulations are performed over a wide range of the relevant parameters. Our simulations reveal that both charge extraction methods provide reliable information about the recombination order and coefficient if the measurements are performed under appropriate conditions. However, results from BACE measurements may be easily affected by surface recombination, in particular for small active layer thicknesses and low illumination densities. TDCF, on the other hand, is more robust against surface recombination due to its transient nature but also because it allows for a homogeneous high carrier density to be inserted into the active layer. Therefore, TDCF is capable to provide meaningful information on the order and coefficient of recombination even if the model conditions are not exactly fulfilled. We demonstrate this for an only 100 nm thick layer of a highly efficient nonfullerene acceptor (NFA) blend, comprising the donor polymer PM6 and the NFA Y6. TDCF measurements were performed as a function of delay time for different laser fluences and bias conditions. The full set of data could be consistently fitted by a strict second order recombination process, with a bias- and fluence-independent bimolecular recombination coefficient k(2) = 1.7 x 10(-17)m(3) s(-1). BACE measurements performed on the very same layer yielded the identical result, despite the very different excitation conditions. This proves that recombination in this blend is mostly through processes in the bulk and that surface recombination is of minor importance despite the small active layer thickness. Published under license by AIP Publishing.
Relaxation processes at the glass transition in polyamide 11: From rigidity to viscoelasticity
(2006)
Relaxation processes associated with the glass transition in nonferroelectric and ferroelectric polyamide (PA) 11 are investigated by means of differential scanning calorimetry, dynamic mechanical analysis, and dielectric relaxation spectroscopy (DRS) in order to obtain information about the molecular mobility within the amorphous phase. In particular, the effects of melt quenching, cold drawing, and annealing just below the melting region are studied with respect to potential possibilities and limitations for improving the piezoelectric and pyroelectric properties of PA 11. A relaxation map is obtained from DRS that shows especially the crossover region where the cooperative alpha relaxation and the local beta relaxation merge into a single high-temperature process. No fundamental difference between quenched, cold-drawn, and annealed films is found, though in the cold-drawn (ferroelectric) film the alpha relaxation is suppressed and slowed down, but it is at least partly recovered by subsequent annealing. It is concluded that there exists an amorphous phase in all structures, even in the cold-drawn film. The amorphous phase can be more rigid or more viscoelastic depending on preparation. Cold drawing not only leads to crystallization in a ferroelectric form but also to higher rigidity of the remaining amorphous phase. Annealing just below the melting region after cold drawing causes a stronger phase separation between the crystalline phase and a more viscoelastic amorphous phase.
Dielectric relaxation processes and structural transitions in Poly(vinylidenefluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE-CFE)) terpolymer films with two different monomer compositions were investigated in comparison with Poly(vinylidenefluoride-trifluoroethylene) (P(VDF-TrFE)) copolymer films as reference material. Differential Scanning Calorimetry was employed to assess annealing effects on phase transitions and crystalline structure, while relaxation processes were investigated by means of Dielectric Relaxation Spectroscopy, the results of which indicate the existence of two separate dispersion regions, denoted as processes A and B, respectively. Process A appears at a certain temperature independent of frequency, but is strongly influenced by the crystallisation temperature and the CFE content, while peak B shows typical features of a relaxation process and is less influenced by crystallisation temperature and CFE content. Furthermore, peak B is related to the glass transition which is more pronounced in the terpolymer than in P(VDF-TrFE). A closer analysis indicates that the addition of CFE and thermal annealing gradually shift the ferro-to-paraelectric transition in P(VDF-TrFE) to lower temperatures, while the phase transition is transformed more and more into a relaxation.
Generalized (non-Markovian) diffusion equations with different memory kernels and subordination schemes based on random time change in the Brownian diffusion process are popular mathematical tools for description of a variety of non-Fickian diffusion processes in physics, biology, and earth sciences. Some of such processes (notably, the fluid limits of continuous time random walks) allow for either kind of description, but other ones do not. In the present work we discuss the conditions under which a generalized diffusion equation does correspond to a subordination scheme, and the conditions under which a subordination scheme does possess the corresponding generalized diffusion equation. Moreover, we discuss examples of random processes for which only one, or both kinds of description are applicable.
We present the use of modern machine learning approaches to suppress self-sustained collective oscillations typically signaled by ensembles of degenerative neurons in the brain. The proposed hybrid model relies on two major components: an environment of oscillators and a policy-based reinforcement learning block. We report a model-agnostic synchrony control based on proximal policy optimization and two artificial neural networks in an Actor-Critic configuration. A class of physically meaningful reward functions enabling the suppression of collective oscillatory mode is proposed. The synchrony suppression is demonstrated for two models of neuronal populations-for the ensembles of globally coupled limit-cycle Bonhoeffer-van der Pol oscillators and for the bursting Hindmarsh-Rose neurons using rectangular and charge-balanced stimuli.
Reflexion und Reflexivität
(2023)
Reflexion gilt in der Lehrkräftebildung als eine Schlüsselkategorie der professionellen Entwicklung. Entsprechend wird auf vielfältige Weise die Qualität reflexionsbezogener Kompetenzen untersucht. Eine Herausforderung hierbei kann in der Annahme bestehen, von der Analyse schriftlicher Reflexionen unmittelbar auf die Reflexivität einer Person zu schließen, da Reflexion stets kontextspezifisch als Abbild reflexionsbezogener Argumentationsprozesse angesehen werden sollte und reflexionsbezogenen Dispositionen unterliegt. Auch kann die Qualität einer Reflexion auf mehreren Dimensionen bewertet werden, ohne quantifizierbare, absolute Aussagen treffen zu können.
Daher wurden im Rahmen einer Physik-Videovignette N = 134 schriftliche Fremdreflexionen verfasst und kontextspezifische reflexionsbezogene Dispositionen erhoben. Expert*innen erstellten theoriegeleitet Qualitätsbewertungen zur Breite, Tiefe, Kohärenz und Spezifität eines jeden Reflexionstextes. Unter Verwendung computerbasierter Klassifikations- und Analyseverfahren wurden weitere Textmerkmale erhoben. Mittels explorativer Faktorenanalyse konnten die Faktoren Qualität, Quantität und Deskriptivität gefunden werden. Da alle konventionell eingeschätzten Qualitätsbewertungen durch einen Faktor repräsentiert wurden, konnte ein maximales Qualitätskorrelat kalkuliert werden, zu welchem jede schriftliche Fremdreflexion im Rahmen der vorliegenden Vignette eine computerbasiert bestimmbare Distanz aufweist. Diese Distanz zum maximalen Qualitätskorrelat konnte validiert werden und kann die Qualität der schriftlichen Reflexionen unabhängig von menschlichen Ressourcen quantifiziert repräsentieren. Abschließend konnte identifiziert werden, dass ausgewählte Dispositionen in unterschiedlichem Maße mit der Reflexionsqualität zusammenhängen. So konnten beispielsweise bezogen auf das Physik-Fachwissen minimale Zusammenhänge identifiziert werden, wohingegen Werthaltung sowie wahrgenommene Unterrichtsqualität eng mit der Qualität einer schriftlichen Reflexion in Verbindung stehen können.
Es wird geschlussfolgert, dass reflexionsbezogene Dispositionen moderierenden Einfluss auf Reflexionen nehmen können. Es wird empfohlen bei der Erhebung von Reflexion mit dem Ziel der Kompetenzmessung ausgewählte Dispositionen mit zu erheben. Weiter verdeutlicht diese Arbeit die Möglichkeit, aussagekräftige Quantifizierungen auch in der Analyse komplexer Konstrukte vorzunehmen. Durch computerbasierte Qualitätsabschätzungen können objektive und individuelle Analysen und differenzierteres automatisiertes Feedback ermöglicht werden.
A maximum entropy (MaxEnt) method is developed to predict flow rates or pressure gradients in hydraulic pipe networks without sufficient information to give a closed-form (deterministic) solution. This methodology substantially extends existing deterministic flow network analysis methods. It builds on the MaxEnt framework previously developed by the authors. This study uses a continuous relative entropy defined on a reduced parameter set, here based on the external flow rates. This formulation ensures consistency between different representations of the same network. The relative entropy is maximized subject to observable constraints on the mean values of a subset of flow rates or potential differences, the frictional properties of each pipe, and physical constraints arising from Kirchhoff’s first and second laws. The new method is demonstrated by application to a simple one-loop network and a 1,123-node, 1,140-pipe water distribution network in the suburb of Torrens, Australian Capital Territory, Australia.
One of the most striking features of ecological systems is their ability to undergo sudden outbreaks in the population numbers of one or a small number of species. The similarity of outbreak characteristics, which is exhibited in totally different and unrelated (ecological) systems naturally leads to the question whether there are universal mechanisms underlying outbreak dynamics in Ecology. It will be shown into two case studies (dynamics of phytoplankton blooms under variable nutrients supply and spread of epidemics in networks of cities) that one explanation for the regular recurrence of outbreaks stems from the interaction of the natural systems with periodical variations of their environment. Natural aquatic systems like lakes offer very good examples for the annual recurrence of outbreaks in Ecology. The idea whether chaos is responsible for the irregular heights of outbreaks is central in the domain of ecological modeling. This question is investigated in the context of phytoplankton blooms. The dynamics of epidemics in networks of cities is a problem which offers many ecological and theoretical aspects. The coupling between the cities is introduced through their sizes and gives rise to a weighted network which topology is generated from the distribution of the city sizes. We examine the dynamics in this network and classified the different possible regimes. It could be shown that a single epidemiological model can be reduced to a one-dimensional map. We analyze in this context the dynamics in networks of weighted maps. The coupling is a saturation function which possess a parameter which can be interpreted as an effective temperature for the network. This parameter allows to vary continously the network topology from global coupling to hierarchical network. We perform bifurcation analysis of the global dynamics and succeed to construct an effective theory explaining very well the behavior of the system.
Recurrences in past climates
(2023)
Our ability to predict the state of a system relies on its tendency to recur to states it has visited before. Recurrence also pervades common intuitions about the systems we are most familiar with: daily routines, social rituals and the return of the seasons are just a few relatable examples. To this end, recurrence plots (RP) provide a systematic framework to quantify the recurrence of states. Despite their conceptual simplicity, they are a versatile tool in the study of observational data. The global climate is a complex system for which an understanding based on observational data is not only of academical relevance, but vital for the predurance of human societies within the planetary boundaries. Contextualizing current global climate change, however, requires observational data far beyond the instrumental period. The palaeoclimate record offers a valuable archive of proxy data but demands methodological approaches that adequately address its complexities. In this regard, the following dissertation aims at devising novel and further developing existing methods in the framework of recurrence analysis (RA). The proposed research questions focus on using RA to capture scale-dependent properties in nonlinear time series and tailoring recurrence quantification analysis (RQA) to characterize seasonal variability in palaeoclimate records (‘Palaeoseasonality’).
In the first part of this thesis, we focus on the methodological development of novel approaches in RA. The predictability of nonlinear (palaeo)climate time series is limited by abrupt transitions between regimes that exhibit entirely different dynamical complexity (e.g. crossing of ‘tipping points’). These possibly depend on characteristic time scales. RPs are well-established for detecting transitions and capture scale-dependencies, yet few approaches have combined both aspects. We apply existing concepts from the study of self-similar textures to RPs to detect abrupt transitions, considering the most relevant time scales. This combination of methods further results in the definition of a novel recurrence based nonlinear dependence measure. Quantifying lagged interactions between multiple variables is a common problem, especially in the characterization of high-dimensional complex systems. The proposed ‘recurrence flow’ measure of nonlinear dependence offers an elegant way to characterize such couplings. For spatially extended complex systems, the coupled dynamics of local variables result in the emergence of spatial patterns. These patterns tend to recur in time. Based on this observation, we propose a novel method that entails dynamically distinct regimes of atmospheric circulation based on their recurrent spatial patterns. Bridging the two parts of this dissertation, we next turn to methodological advances of RA for the study of Palaeoseasonality. Observational series of palaeoclimate ‘proxy’ records involve inherent limitations, such as irregular temporal sampling. We reveal biases in the RQA of time series with a non-stationary sampling rate and propose a correction scheme.
In the second part of this thesis, we proceed with applications in Palaeoseasonality. A review of common and promising time series analysis methods shows that numerous valuable tools exist, but their sound application requires adaptions to archive-specific limitations and consolidating transdisciplinary knowledge. Next, we study stalagmite proxy records from the Central Pacific as sensitive recorders of mid-Holocene El Niño-Southern Oscillation (ENSO) dynamics. The records’ remarkably high temporal resolution allows to draw links between ENSO and seasonal dynamics, quantified by RA. The final study presented here examines how seasonal predictability could play a role for the stability of agricultural societies. The Classic Maya underwent a period of sociopolitical disintegration that has been linked to drought events. Based on seasonally resolved stable isotope records from Yok Balum cave in Belize, we propose a measure of seasonal predictability. It unveils the potential role declining seasonal predictability could have played in destabilizing agricultural and sociopolitical systems of Classic Maya populations.
The methodological approaches and applications presented in this work reveal multiple exciting future research avenues, both for RA and the study of Palaeoseasonality.
Recurrence plots, a rather promising tool of data analysis, have been introduced by Eckman et al. in 1987. They visualise recurrences in phase space and give an overview about the system's dynamics. Two features have made the method rather popular. Firstly they are rather simple to compute and secondly they are putatively easy to interpret. However, the straightforward interpretation of recurrence plots for some systems yields rather surprising results. For example indications of low dimensional chaos have been reported for stock marked data, based on recurrence plots. In this work we exploit recurrences or ``naturally occurring analogues'' as they were termed by E. Lorenz, to obtain three key results. One of which is that the most striking structures which are found in recurrence plots are hinged to the correlation entropy and the correlation dimension of the underlying system. Even though an eventual embedding changes the structures in recurrence plots considerably these dynamical invariants can be estimated independently of the special parameters used for the computation. The second key result is that the attractor can be reconstructed from the recurrence plot. This means that it contains all topological information of the system under question in the limit of long time series. The graphical representation of the recurrences can also help to develop new algorithms and exploit specific structures. This feature has helped to obtain the third key result of this study. Based on recurrences to points which have the same ``recurrence structure'', it is possible to generate surrogates of the system which capture all relevant dynamical characteristics, such as entropies, dimensions and characteristic frequencies of the system. These so generated surrogates are shadowed by a trajectory of the system which starts at different initial conditions than the time series in question. They can be used then to test for complex synchronisation.
Recurrence plot analyses suggest a novel reference system involved in newborn spontaneous movements
(2006)
The movements of newborns have been thoroughly studied in terms of reflexes, muscle synergies, leg coordination, and target-directed arm/hand movements. Since these approaches have concentrated mainly on separate accomplishments, there has remained a clear need for more integrated investigations. Here, we report an inquiry in which we explicitly concentrated on taking such a perspective and, additionally, were guided by the methodological concept of home base behavior, which Ilan Golard developed for studies of exploratory behavior in animals. Methods from nonlinear dynamics, such as symbolic dynamics and recurrence plot analyses of kinematic data received from audiovisual newborn recordings, yielded new insights into the spatial and temporal organization of limb movements. In the framework of home base behavior, our approach uncovered a novel reference system of spontaneous newborn movements.
Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Herewe propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts.
In nature as well as in the context of infection and medical applications, bacteria often have to move in highly complex environments such as soil or tissues. Previous studies have shown that bacteria strongly interact with their surroundings and are often guided by confinements. Here, we investigate theoretically how the dispersal of swimming bacteria can be augmented by microfluidic environments and validate our theoretical predictions experimentally. We consider a system of bacteria performing the prototypical run-and-tumble motion inside a labyrinth with square lattice geometry. Narrow channels between the square obstacles limit the possibility of bacteria to reorient during tumbling events to an area where channels cross. Thus, by varying the geometry of the lattice it might be possible to control the dispersal of cells. We present a theoretical model quantifying diffusive spreading of a run-and-tumble random walker in a square lattice. Numerical simulations validate our theoretical predictions for the dependence of the diffusion coefficient on the lattice geometry. We show that bacteria moving in square labyrinths exhibit enhanced dispersal as compared to unconfined cells. Importantly, confinement significantly extends the duration of the phase with strongly non-Gaussian diffusion, when the geometry of channels is imprinted in the density profiles of spreading cells. Finally, in good agreement with our theoretical findings, we observe the predicted behaviors in experiments with E. coli bacteria swimming in a square lattice labyrinth created in amicrofluidic device. Altogether, our comprehensive understanding of bacterial dispersal in a simple two-dimensional labyrinth makes the first step toward the analysis of more complex geometries relevant for real world applications.
In nature as well as in the context of infection and medical applications, bacteria often have to move in highly complex environments such as soil or tissues. Previous studies have shown that bacteria strongly interact with their surroundings and are often guided by confinements. Here, we investigate theoretically how the dispersal of swimming bacteria can be augmented by microfluidic environments and validate our theoretical predictions experimentally. We consider a system of bacteria performing the prototypical run-and-tumble motion inside a labyrinth with square lattice geometry. Narrow channels between the square obstacles limit the possibility of bacteria to reorient during tumbling events to an area where channels cross. Thus, by varying the geometry of the lattice it might be possible to control the dispersal of cells. We present a theoretical model quantifying diffusive spreading of a run-and-tumble random walker in a square lattice. Numerical simulations validate our theoretical predictions for the dependence of the diffusion coefficient on the lattice geometry. We show that bacteria moving in square labyrinths exhibit enhanced dispersal as compared to unconfined cells. Importantly, confinement significantly extends the duration of the phase with strongly non-Gaussian diffusion, when the geometry of channels is imprinted in the density profiles of spreading cells. Finally, in good agreement with our theoretical findings, we observe the predicted behaviors in experiments with E. coli bacteria swimming in a square lattice labyrinth created in amicrofluidic device. Altogether, our comprehensive understanding of bacterial dispersal in a simple two-dimensional labyrinth makes the first step toward the analysis of more complex geometries relevant for real world applications.
Core-collapse supernova remnants are the gaseous nebulae of galactic interstellar media (ISM) formed after the explosive death of massive stars. Their morphology and emission properties depend both on the surrounding circumstellar structure shaped by the stellar wind-ISM interaction of the progenitor star and on the local conditions of the ambient medium. In the warm phase of the Galactic plane (n approximate to 1 cm(-3), T approximate to 8000 K), an organized magnetic field of strength 7 mu G has profound consequences on the morphology of the wind bubble of massive stars at rest. In this paper, we show through 2.5D magnetohydrodynamical simulations, in the context of a Wolf-Rayet-evolving 35 M 0 star, that it affects the development of its supernova remnant. When the supernova remnant reaches its middle age (15-20 kyr), it adopts a tubular shape that results from the interaction between the isotropic supernova ejecta and the anisotropic, magnetized, shocked stellar progenitor bubble into which the supernova blast wave expands. Our calculations for non-thermal emission, i.e. radio synchrotron and inverse-Compton radiation, reveal that such supernova remnants can, due to projection effects, appear as rectangular objects in certain cases. This mechanism for shaping a supernova remnant is similar to the bipolar and elliptical planetary nebula production by wind-wind interaction in the low-mass regime of stellar evolution. If such a rectangular core-collapse supernova remnant is created, the progenitor star must not have been a runaway star. We propose that such a mechanism is at work in the shaping of the asymmetric core-collapse supernova remnant Puppis A.
Using a special technique of data analysis, we have found out 34 grand minima of solar activity obtained from a 7,700 years long Δ14C record. The method used rests on a proper filtering of the Δ14C record and the extrapolation of verifiable results for the later history back in time. Additionally, we use a method of nonlinear dynamics, the recurrence rate, to back up the results. Our findings are not contradictory to the record of solar maxima resp. minima by Eddy [5], but constitute a considerable extension. Hence, it has become possible to look closer at the validity of models. This way, we have tested several models for solar activity, esp. the model of Barnes et al. [1]. There are hints for that the grand minima might solely be driven by the 209 year period found in the Δ14C record.
We propose a method of reconstruction of the network coupling matrix for a basic voltage-model of the neural field dynamics. Assuming that the multivariate time series of observations from all nodes are available, we describe a technique to find coupling constants which is unbiased in the limit of long observations. Furthermore, the method is generalized for reconstruction of networks with time-delayed coupling, including the reconstruction of unknown time delays. The approach is compared with other recently proposed techniques.
We consider networks of coupled phase oscillators of different complexity: Kuramoto–Daido-type networks, generalized Winfree networks, and hypernetworks with triple interactions. For these setups an inverse problem of reconstruction of the network connections and of the coupling function from the observations of the phase dynamics is addressed. We show how a reconstruction based on the minimization of the squared error can be implemented in all these cases. Examples include random networks with full disorder both in the connections and in the coupling functions, as well as networks where the coupling functions are taken from experimental data of electrochemical oscillators. The method can be directly applied to asynchronous dynamics of units, while in the case of synchrony, additional phase resettings are necessary for reconstruction.
Achieving the highest power conversion efficiencies in bulk heterojunction organic solar cells requires a morphology that delivers electron and hole percolation pathways for optimized transport, plus sufficient donor:acceptor contact area for near unity charge transfer state formation. This is a significant structural challenge, particularly in semiconducting polymer:fullerene systems. This balancing act in the model high efficiency PTB7:PC70BM blend is studied by tuning the donor:acceptor ratio, with a view to understanding the recombination loss mechanisms above and below the fullerene transport percolation threshold. The internal quantum efficiency is found to be strongly correlated to the slower carrier mobility in agreement with other recent studies. Furthermore, second-order recombination losses dominate the shape of the current density-voltage curve in efficient blend combinations, where the fullerene phase is percolated. However, below the charge transport percolation threshold, there is an electric-field dependence of first-order losses, which includes electric-field-dependent photogeneration. In the intermediate regime, the fill factor appears to be limited by both first- and second-order losses. These findings provide additional basic understanding of the interplay between the bulk heterojunction morphology and the order of recombination in organic solar cells. They also shed light on the limitations of widely used transport models below the percolation threshold.
Charge extraction in organic solar cells (OSCs) is commonly believed to be limited by bimolecular recombination of photogenerated charges. However, the fill factor of OSCs is usually almost entirely governed by recombination processes that scale with the first order of the light intensity. This linear loss was often interpreted to be a consequence of geminate or trap-assisted recombination. Numerical simulations show that this linear dependence is a direct consequence of the large amount of excess dark charge near the contact. The first-order losses increase with decreasing mobility of minority carriers, and we discuss the impact of several material and device parameters on this loss mechanism. This work highlights that OSCs are especially vulnerable to injected charges as a result of their poor charge transport properties. This implies that dark charges need to be better accounted for when interpreting electro-optical measurements and charge collection based on simple figures of merit.
We predict the recoil-induced molecular dissociation in hard-x-ray photoionization. The recoil effect is caused by electronic and photon momentum exchange with the molecule. We show the strong role of relativistic effects for the studied molecular fragmentation. The recoil-induced fragmentation of the molecule is caused by elongation of the bond due to the vibrational recoil effect and because of the centrifugal force caused by the rotational recoil. The calculations of the x-ray photoelectron spectra of the H-2 and NO molecules show that the predicted effects can be observed in high-energy synchrotrons like SOLEIL, SPring-8, PETRA, and XFEL SACLA. The relativistic effect enhances the recoil momentum transfer and makes it strongly sensitive to the direction of ejection of the fast photoelectron with respect to the photon momentum.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
Reciprocal space slicing
(2021)
An experimental technique that allows faster assessment of out-of-plane strain dynamics of thin film heterostructures via x-ray diffraction is presented. In contrast to conventional high-speed reciprocal space-mapping setups, our approach reduces the measurement time drastically due to a fixed measurement geometry with a position-sensitive detector. This means that neither the incident (ω) nor the exit (2θ) diffraction angle is scanned during the strain assessment via x-ray diffraction. Shifts of diffraction peaks on the fixed x-ray area detector originate from an out-of-plane strain within the sample. Quantitative strain assessment requires the determination of a factor relating the observed shift to the change in the reciprocal lattice vector. The factor depends only on the widths of the peak along certain directions in reciprocal space, the diffraction angle of the studied reflection, and the resolution of the instrumental setup. We provide a full theoretical explanation and exemplify the concept with picosecond strain dynamics of a thin layer of NbO2.
The formation process of zeolite A (Linde Type A) was monitored inline at 1.5 L scale by Photon Density Wave (PDW) spectroscopy as novel process analytical technology for highly turbid liquid suspensions. As a result, the reduced scattering coefficient, being a measure for particle number, size, and morphology, provides distinct process information, including the formation of amorphous particles and their transfer into crystalline zeolite structures. The onset and end of the crystallization process can be detected inline and in real-time. Analyses by powder X-ray diffraction and electron microscopy, based on a sampling approach, support the interpretation of the results obtained by PDW spectroscopy. In addition, the influence of the molar water content was investigated, indicating a linear increase of the time needed to reach the end of the zeolite A crystallization with increasing molar water content. Further experiments indicate a strong influence of the silica source on the course of the crystallization. The applicability of PDW spectroscopy under even more demanding chemical and physical conditions was investigated by monitoring the synthesis of zeolite L (Linde Type L).
Recent experiments show that transcription factors (TFs) indeed use the facilitated diffusion mechanism to locate their target sequences on DNA in living bacteria cells: TFs alternate between sliding motion along DNA and relocation events through the cytoplasm. From simulations and theoretical analysis we study the TF-sliding motion for a large section of the DNA-sequence of a common E. coli strain, based on the two-state TF-model with a fast-sliding search state and a recognition state enabling target detection. For the probability to detect the target before dissociating from DNA the TF-search times self-consistently depend heavily on whether or not an auxiliary operator (an accessible sequence similar to the main operator) is present in the genome section. Importantly, within our model the extent to which the interconversion rates between search and recognition states depend on the underlying nucleotide sequence is varied. A moderate dependence maximises the capability to distinguish between the main operator and similar sequences. Moreover, these auxiliary operators serve as starting points for DNA looping with the main operator, yielding a spectrum of target detection times spanning several orders of magnitude. Auxiliary operators are shown to act as funnels facilitating target detection by TFs.
Recent experiments show that transcription factors (TFs) indeed use the facilitated diffusion mechanism to locate their target sequences on DNA in living bacteria cells: TFs alternate between sliding motion along DNA and relocation events through the cytoplasm. From simulations and theoretical analysis we study the TF-sliding motion for a large section of the DNA-sequence of a common E. coli strain, based on the two-state TF-model with a fast-sliding search state and a recognition state enabling target detection. For the probability to detect the target before dissociating from DNA the TF-search times self-consistently depend heavily on whether or not an auxiliary operator (an accessible sequence similar to the main operator) is present in the genome section. Importantly, within our model the extent to which the interconversion rates between search and recognition states depend on the underlying nucleotide sequence is varied. A moderate dependence maximises the capability to distinguish between the main operator and similar sequences. Moreover, these auxiliary operators serve as starting points for DNA looping with the main operator, yielding a spectrum of target detection times spanning several orders of magnitude. Auxiliary operators are shown to act as funnels facilitating target detection by TFs.
Space radiation is one of the main concerns for human space flights. The prediction of the radiation dose for the actual spacecraft geometry is very important for the planning of long-duration missions. We present a numerical method for the fast calculation of the radiation dose rate during a space flight. We demonstrate its application for dose calculations during the first and the second sessions of the MATROSHKA-R space experiment with a spherical tissue-equivalent phantom. The main advantage of the method is the short simulation time, so it can be applied for urgent radiation dose calculations for low-Earth orbit space missions. The method uses depth-dose curve and shield-and-composition distribution functions to calculate a radiation dose at the point of interest. The spacecraft geometry is processed into a shield-and-composition distribution function using a ray-tracing method. Depth-dose curves are calculated using the GEANT4 Monte-Carlo code (version 10.00.P02) for a double-layer aluminum-water shielding. Aluminum-water shielding is a good approximation of the real geometry, as water is a good equivalent for biological tissues, and aluminum is the major material of spacecraft bodies.
Two new hole selective materials (HSMs) based on dangling methylsulfanyl groups connected to the C-9 position of the fluorene core are synthesized and applied in perovskite solar cells. Being structurally similar to a half of Spiro-OMeTAD molecule, these HSMs (referred as FS and DFS) share similar redox potentials but are endowed with slightly higher hole mobility, due to the planarity and large extension of their structure. Competitive power conversion efficiency (up to 18.6%) is achieved by using the new HSMs in suitable perovskite solar cells. Time-resolved photoluminescence decay measurements and electrochemical impedance spectroscopy show more efficient charge extraction at the HSM/perovskite interface with respect to Spiro-OMeTAD, which is reflected in higher photocurrents exhibited by DFS/FS-integrated perovskite solar cells. Density functional theory simulations reveal that the interactions of methylammonium with methylsulfanyl groups in DFS/FS strengthen their electrostatic attraction with the perovskite surface, providing an additional path for hole extraction compared to the sole presence of methoxy groups in Spiro-OMeTAD. Importantly, the low-cost synthesis of FS makes it significantly attractive for the future commercialization of perovskite solar cells.
We present a framework for systems in which diffusion-advection transport of a tracer substance in a mobile zone is interrupted by trapping in an immobile zone.
Our model unifies different model approaches based on distributed-order diffusion equations, exciton diffusion rate models, and random-walk models for multirate mobile-immobile mass transport.
We study various forms for the trapping time dynamics and their effects on the tracer mass in the mobile zone.
Moreover, we find the associated breakthrough curves, the tracer density at a fixed point in space as a function of time, and the mobile and immobile concentration profiles and the respective moments of the transport.
Specifically, we derive explicit forms for the anomalous transport dynamics and an asymptotic power-law decay of the mobile mass for a Mittag-Leffler trapping time distribution.
In our analysis we point out that even for exponential trapping time densities, transient anomalous transport is observed.
Our results have direct applications in geophysical contexts, but also in biological, soft matter, and solid state systems.
Transport processes in and of cells are of major importance for the survival of the organism. Muscles have to be able to contract, chromosomes have to be moved to opposing ends of the cell during mitosis, and organelles, which are compartments enclosed by membranes, have to be transported along molecular tracks. Molecular motors are proteins whose main task is moving other molecules.For that purpose they transform the chemical energy released in the hydrolysis of ATP into mechanical work. The motors of the cytoskeleton belong to the three super families myosin, kinesin and dynein. Their tracks are filaments of the cytoskeleton, namely actin and the microtubuli. Here, we examine stochastic models which are used for describing the movements of these linear molecular motors. The scale of the movements comprises the regime of single steps of a motor protein up to the directed walk along a filament. A single step bridges around 10 nm, depending on the protein, and takes about 10 ms, if there is enough ATP available. Our models comprise M states or conformations the motor can attain during its movement along a one-dimensional track. At K locations along the track transitions between the states are possible. The velocity of the protein depending on the transition rates between the single states can be determined analytically. We calculate this velocity for systems of up to four states and locations and are able to derive a number of rules which are helpful in estimating the behaviour of an arbitrary given system. Beyond that we have a look at decoupled subsystems, i.e., one or a couple of states which have no connection to the remaining system. With a certain probability a motor undergoes a cycle of conformational changes, with another probability an independent other cycle. Active elements in real transport processes by molecular motors will not be limited to the transitions between the states. In distorted networks or starting from the discrete Master equation of the system, it is possible to specify horizontal rates, too, which furthermore no longer have to fulfill the conditions of detailed balance. Doing so, we obtain unique, complete paths through the respective network and rules for the dependence of the total current on all the rates of the system. Besides, we view the time evolutions for given initial distributions. In enzymatic reactions there is the idea of a main pathway these reactions follow preferably. We determine optimal paths and the maximal flow for given networks. In order to specify the dependence of the motor's velocity on its fuel ATP, we have a look at possible reaction kinetics determining the connection between unbalanced transitions rates and ATP-concentration. Depending on the type of reaction kinetics and the number of unbalanced rates, we obtain qualitatively different curves connecting the velocity to the ATP-concentration. The molecular interaction potentials the motor experiences on its way along its track are unknown. We compare different simple potentials and the effects the localization of the vertical rates in the network model has on the transport coefficients in comparison to other models.
Electron acceleration at Saturn due to whistler mode chorus waves has previously been assumed to be ineffective; new data closer to the planet show it can be very rapid (factor of 104 flux increase at 1 MeV in 10 days compared to factor of 2). A full survey of chorus waves at Saturn is combined with an improved plasma density model to show that where the plasma frequency falls below the gyrofrequency additional strong resonances are observed favoring electron acceleration. This results in strong chorus acceleration between approximately 2.5 R-S and 5.5 R-S outside which adiabatic transport may dominate. Strong pitch angle dependence results in butterfly pitch angle distributions that flatten over a few days at 100s keV, tens of days at MeV energies which may explain observations of butterfly distributions of MeV electrons near L = 3. Including cross terms in the simulations increases the tendency toward butterfly distributions. Plain Language Summary Radiation belts are hazardous regions found around several of the planets in our Solar System. They consist of very hot, electrically charged particles trapped in the magnetic field of the planet. At Saturn the most important way to heat these particles has for many years been thought to involve the particles drifting closer toward the planet. This paper adds to the emerging idea at Saturn that a different way to heat the particles is also possible where the heating is done by waves, in a similar way to what we find at the Earth. We use recent information from the Cassini spacecraft on the number and location of particles and also of the waves strength and location combined with computer simulations to show that a particular wave called chorus is excellent at heating the particles where the surrounding number of cold particles is low.
Over the last decades, the Arctic regions of the earth have warmed at a rate 2–3 times faster than the global average– a phenomenon called Arctic Amplification. A complex, non-linear interplay of physical processes and unique pecularities in the Arctic climate system is responsible for this, but the relative role of individual processes remains to be debated. This thesis focuses on the climate change and related processes on Svalbard, an archipelago in the North Atlantic sector of the Arctic, which is shown to be a "hotspot" for the amplified recent warming during winter. In this highly dynamical region, both oceanic and atmospheric large-scale transports of heat and moisture interfere with spatially inhomogenous surface conditions, and the corresponding energy exchange strongly shapes the atmospheric boundary layer. In the first part, Pan-Svalbard gradients in the surface air temperature (SAT) and sea ice extent (SIE) in the fjords are quantified and characterized. This analysis is based on observational data from meteorological stations, operational sea ice charts, and hydrographic observations from the adjacent ocean, which cover the 1980–2016 period. It is revealed that typical estimates of SIE during late winter range from 40–50% (80–90%) in the western (eastern) parts of Svalbard. However, strong SAT warming during winter of the order of 2–3K per decade dictates excessive ice loss, leaving fjords in the western parts essentially ice-free in recent winters. It is further demostrated that warm water currents on the west coast of Svalbard, as well as meridional winds contribute to regional differences in the SIE evolution. In particular, the proximity to warm water masses of the West Spitsbergen Current can explain 20–37% of SIE variability in fjords on west Svalbard, while meridional winds and associated ice drift may regionally explain 20–50% of SIE variability in the north and northeast. Strong SAT warming has overruled these impacts in recent years, though.
In the next part of the analysis, the contribution of large-scale atmospheric circulation changes to the Svalbard temperature development over the last 20 years is investigated. A study employing kinematic air-back trajectories for Ny-Ålesund reveals a shift in the source regions of lower-troposheric air over time for both the winter and the summer season. In winter, air in the recent decade is more often of lower-latitude Atlantic origin, and less frequent of Arctic origin. This affects heat- and moisture advection towards Svalbard, potentially manipulating clouds and longwave downward radiation in that region. A closer investigation indicates that this shift during winter is associated with a strengthened Ural blocking high and Icelandic low, and contributes about 25% to the observed winter warming on Svalbard over the last 20 years. Conversely, circulation changes during summer include a strengthened Greenland blocking high which leads to more frequent cold air advection from the central Arctic towards Svalbard, and less frequent air mass origins in the lower latitudes of the North Atlantic. Hence, circulation changes during winter are shown to have an amplifying effect on the recent warming on Svalbard, while summer circulation changes tend to mask warming.
An observational case study using upper air soundings from the AWIPEV research station in Ny-Ålesund during May–June 2017 underlines that such circulation changes during summer are associated with tropospheric anomalies in temperature, humidity and boundary layer height.
In the last part of the analysis, the regional representativeness of the above described changes around Svalbard for the broader Arctic is investigated. Therefore, the terms in the diagnostic temperature equation in the Arctic-wide lower troposphere are examined for the Era-Interim atmospheric reanalysis product. Significant positive trends in diabatic heating rates, consistent with latent heat transfer to the atmosphere over regions of increasing ice melt, are found for all seasons over the Barents/Kara Seas, and in individual months in the vicinity of Svalbard. The above introduced warm (cold) advection trends during winter (summer) on Svalbard are successfully reproduced. Regarding winter, they are regionally confined to the Barents Sea and Fram Strait, between 70°–80°N, resembling a unique feature in the whole Arctic. Summer cold advection trends are confined to the area between eastern Greenland and Franz Josef Land, enclosing Svalbard.
Random search with resetting
(2018)
We provide a unified renewal approach to the problem of random search for several targets under resetting. This framework does not rely on specific properties of the search process and resetting procedure, allows for simpler derivation of known results, and leads to new ones. Concentrating on minimizing the mean hitting time, we show that resetting at a constant pace is the best possible option if resetting helps at all, and derive the equation for the optimal resetting pace. No resetting may be a better strategy if without resetting the probability of not finding a target decays with time to zero exponentially or faster. We also calculate splitting probabilities between the targets, and define the limits in which these can be manipulated by changing the resetting procedure. We moreover show that the number of moments of the hitting time distribution under resetting is not less than the sum of the numbers of moments of the resetting time distribution and the hitting time distribution without resetting.
Random multi-hopper model
(2018)
We develop a mathematical model considering a random walker with long-range hops on arbitrary graphs. The random multi-hopper can jump to any node of the graph from an initial position, with a probability that decays as a function of the shortest-path distance between the two nodes in the graph. We consider here two decaying functions in the form of Laplace and Mellin transforms of the shortest-path distances. We prove that when the parameters of these transforms approach zero asymptotically, the hitting time in the multi-hopper approaches the minimum possible value for a normal random walker. We show by computational experiments that the multi-hopper explores a graph with clusters or skewed degree distributions more efficiently than a normal random walker. We provide computational evidences of the advantages of the random multi-hopper model with respect to the normal random walk by studying deterministic, random and real-world networks.
Random logic networks
(2021)
We investigate dynamical properties of a quantum generalization of classical reversible Boolean networks. The state of each node is encoded as a single qubit, and classical Boolean logic operations are supplemented by controlled bit-flip and Hadamard operations. We consider synchronous updating schemes in which each qubit is updated at each step based on stored values of the qubits from the previous step. We investigate the periodic or quasiperiodic behavior of quantum networks, and we analyze the propagation of single site perturbations through the quantum networks with input degree one. A nonclassical mechanism for perturbation propagation leads to substantially different evolution of the Hamming distance between the original and perturbed states.
Percolation process, which is intrinsically a phase transition process near the critical point, is ubiquitous in nature. Many of its applications embrace a wide spectrum of natural phenomena ranging from the forest fires, spread of contagious diseases, social behaviour dynamics to mathematical finance, formation of bedrocks and biological systems. The topology generated by the percolation process near the critical point is a random (stochastic) fractal. It is fundamental to the percolation theory that near the critical point, a unique infinite fractal structure, namely the infinite cluster, would emerge. As de Gennes suggested, the properties of the infinite cluster could be deduced by studying the dynamical behaviour of the random walk process taking place on it. He coined the term the ant in the labyrinth. The random walk process on such an infinite fractal cluster exhibits a subdiffusive dynamics in the sense that the mean squared displacement grows as ~t2/dw, where dw, called the fractal dimension of the random walk path, is greater than 2. Thus, the random walk process on the infinite cluster is classified as a process exhibiting the properties of anomalous diffusions. Yet near the critical point, the infinite cluster is not the sole emergent topology, but it coexists with other clusters whose size is finite. Though finite, on specific length scales these finite clusters exhibit fractal properties as well. In this work, it is assumed that the random walk process could take place on these finite size objects as well. Bearing this assumption in mind requires one address the non-equilibrium initial condition. Due to the lack of knowledge on the propagator of the random walk process in stochastic random environments, a phenomenological correspondence between the renowned Ornstein-Uhlenbeck process and the random walk process on finite size clusters is established. It is elucidated that when an ensemble of these finite size clusters and the infinite cluster is considered, the anisotropy and size of these finite clusters effects the mean squared displacement and its time averaged counterpart to grow in time as ~t(d+df (t-2))/dw, where d is the embedding Euclidean dimension, df is the fractal dimension of the infinite cluster, and , called the Fisher exponent, is a critical exponent governing the power-law distribution of the finite size clusters. Moreover, it is demonstrated that, even though the random walk process on a specific finite size cluster is ergodic, it exhibits a persistent non-ergodic behaviour when an ensemble of finite size and the infinite clusters is considered.
A considerable number of systems have recently been reported in which
Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential(Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.
Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential(Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.
Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as ‘superstatistics’ or ‘diffusing diffusivity’. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.
Many studies on biological and soft matter systems report the joint presence of a linear mean-squared displacement and a non-Gaussian probability density exhibiting, for instance, exponential or stretched-Gaussian tails. This phenomenon is ascribed to the heterogeneity of the medium and is captured by random parameter models such as ‘superstatistics’ or ‘diffusing diffusivity’. Independently, scientists working in the area of time series analysis and statistics have studied a class of discrete-time processes with similar properties, namely, random coefficient autoregressive models. In this work we try to reconcile these two approaches and thus provide a bridge between physical stochastic processes and autoregressive models.Westart from the basic Langevin equation of motion with time-varying damping or diffusion coefficients and establish the link to random coefficient autoregressive processes. By exploring that link we gain access to efficient statistical methods which can help to identify data exhibiting Brownian yet non-Gaussian diffusion.
R-Group stabilization in methylated formamides observed by resonant inelastic X-ray scattering
(2022)
The inherent stability of methylated formamides is traced to a stabilization of the deep-lying sigma-framework by resonant inelastic X-ray scattering at the nitrogen K-edge. Charge transfer from the amide nitrogen to the methyl groups underlie this stabilization mechanism that leaves the aldehyde group essentially unaltered and explains the stability of secondary and tertiary amides.
The subject of the present thesis is the one-dimensional Bose gas. Since long-rang order is destroyed by infra-red fluctuations in one dimension, only the formation of a quasi-condensate is possible, which exhibits suppressed density fluctuations, but whose phase fluctuates strongly. It is shown that modified mean-field theories based on a symmetry-breaking approach can even characterise phase coherence properties of such a quasi-condensate properly. A correct description of the transition from the degenerate ideal Bose gas to the quasi-condensate, which is a smooth cross-over rather than a phase transition, is not possible though. Basic conditions for the applicability of the theories are not fulfilled in this regime, such that the existence of a critical point is predicted.
The theories are compared on the basis of their excitation sprectum, equation of state, density fluctuations and related correlation functions. High-temperature expansions of the corresponding integrals are derived analytically for the numerical evaluation of the self-consistent integral equations. Apart from that, the Stochastic Gross-Pitaevskii equation (SGPE), a non-linear Langevin equation, is analysed numerically by means of Monte-Carlo simulations and the results are compared to those of the mean-field theories. In this context, a lot of attention is payed to the appropriate choice of the parameters. The simulations prove that the SGPE is capable of describing the cross-over properly, but highlight the limitations of the widely used local density approximation as well.
The Thesis is focused on the properties of self-organized nanostructures. Atomic and electronic properties of different systems have been investigated using methods of electron diffraction, scanning tunneling microscopy and photoelectron spectroscopy. Implementation of the STM technique (including design, construction, and tuning of the UHV experimental set-up) has been done in the framework of present work. This time-consuming work is reported to greater detail in the experimental part of this Thesis. The scientific part starts from the study of quantum-size effects in the electronic structure of a two-dimensional Ag film on the supporting substrate Ni(111). Distinct quantum well states in the sp-band of Ag were observed in photoelectron spectra. Analysis of thickness- and angle-dependent photoemission supplies novel information on the properties of the interface. For the first time the Ni(111) relative band gap was indirectly probed in the ground-state through the electronic structure of quantum well states in the adlayer. This is particularly important for Ni where valence electrons are strongly correlated. Comparison of the experiment with calculations performed in the formalism of the extended phase accumulation model gives the substrate gap which is fully consistent with the one obtained by ab-initio LDA calculations. It is, however, in controversy to the band structure of Ni measured directly by photoemission. These results lend credit to the simplest view of photoemission from Ni, assigning early observed contradictions between theory and experiments to electron correlation effects in the final state of photoemission. Further, nanosystems of lower dimensionality have been studied. Stepped surfaces W(331) and W(551) were used as one-dimensional model systems and as templates for self-organization of Au nanoclusters. Photon energy dependent photoemission revealed a surface resonance which was never observed before on W(110) which is the base plane of the terrace microsurfaces. The dispersion E(k) of this state measured on stepped W(331) and W(551) with angle-resolved photoelectron spectroscopy is modified by a strong umklapp effect. It appears as two parabolas shifted symmetrically relative to the microsurface normal by half of the Brillouin zone of the step superlattice. The reported results are very important for understanding of the electronic properties of low-dimensional nanostructures. It was also established that W(331) and W(551) can serve as templates for self-organization of metallic nanostructures. A combined study of electronic and atomic properties of sub-monolayer amounts of gold deposited on these templates have shown that if the substrate is slightly pre-oxidized and the temperature is elevated, then Au can alloy with the first monolayer of W. As a result, a nanostructure of uniform clusters of a surface alloy is produced all over the steps. Such clusters feature a novel sp-band in the vicinity of the Fermi level, which appears split into constant energy levels due to effects of lateral quantization. The last and main part of this work is devoted to large-scale reconstructions on surfaces and nanostructures self-assembled on top. The two-dimensional surface carbide W(110)/C-R(15x3) has been extensively investigated. Photoemission studies of quantum size effects in the electronic structure of this reconstruction, combined with an investigation of its surface geometry, lead to an advanced structural model of the carbide overlayer. It was discovered that W(110)/C-R(15x3) can control self-organization of adlayers into nanostructures with extremely different electronic and structural properties. Thus, it was established that at elevated temperature the R(15x3) superstructure controls the self-assembly of sub-monolayer amounts of Au into nm-wide nanostripes. Based on the results of core level photoemission, the R(15x3)-induced surface alloying which takes place between Au and W can be claimed as driving force of self-organization. The observed stripes exhibit a characteristic one-dimensional electronic structure with laterally quantized d-bands. Obviously, these are very important for applications, since dimensions of electronic devices have already stepped into the nm-range, where quantum-size phenomena must undoubtedly be considered. Moreover, formation of perfectly uniform molecular clusters of C60 was demonstrated and described in terms of the van der Waals formalism. It is the first experimental observation of two-dimensional fullerene nanoclusters with "magic numbers". Calculations of the cluster potentials using the static approach have revealed characteristic minima in the interaction energy. They are achieved for 4 and 7 molecules per cluster. The obtained "magic numbers" and the corresponding cluster structures are fully consistent with the results of the STM measurements.
Can the statistical properties of single-electron transfer events be correctly predicted within a common equilibrium ensemble description? This fundamental in nanoworld question of ergodic behavior is scrutinized within a very basic semi-classical curve-crossing problem. It is shown that in the limit of non-adiabatic electron transfer (weak tunneling) well-described by the Marcus–Levich–Dogonadze(MLD) rate the answer is yes. However, in the limit of the so-called solvent-controlled adiabatic electron transfer, a profound breaking of ergodicity occurs. Namely, a common description based on the ensemble reduced density matrix with an initial equilibrium distribution of the reaction coordinate is not able to reproduce the statistics of single-trajectory events in this seemingly classical regime. For sufficiently large activation barriers, the ensemble survival probability in a state remains nearly exponential with the inverse rate given by the sum of the adiabatic curve crossing (Kramers) time and the inverse MLD rate. In contrast, near to the adiabatic regime, the single-electron survival probability is clearly non-exponential, even though it possesses an exponential tail which agrees well with the ensemble description. Initially, it is well described by a Mittag-Leffler distribution with a fractional rate. Paradoxically, the mean transfer time in this classical on the ensemble level regime is well described by the inverse of the nonadiabatic quantum tunneling rate on a single particle level. An analytical theory is developed which perfectly agrees with stochastic simulations and explains our findings.
Can the statistical properties of single-electron transfer events be correctly predicted within a common equilibrium ensemble description? This fundamental in nanoworld question of ergodic behavior is scrutinized within a very basic semi-classical curve-crossing problem. It is shown that in the limit of non-adiabatic electron transfer (weak tunneling) well-described by the Marcus-Levich-Dogonadze (MLD) rate the answer is yes. However, in the limit of the so-called solvent-controlled adiabatic electron transfer, a profound breaking of ergodicity occurs. Namely, a common description based on the ensemble reduced density matrix with an initial equilibrium distribution of the reaction coordinate is not able to reproduce the statistics of single-trajectory events in this seemingly classical regime. For sufficiently large activation barriers, the ensemble survival probability in a state remains nearly exponential with the inverse rate given by the sum of the adiabatic curve crossing (Kramers) time and the inverse MLD rate. In contrast, near to the adiabatic regime, the single-electron survival probability is clearly non-exponential, even though it possesses an exponential tail which agrees well with the ensemble description. Initially, it is well described by a Mittag-Leffler distribution with a fractional rate. Paradoxically, the mean transfer time in this classical on the ensemble level regime is well described by the inverse of the nonadiabatic quantum tunneling rate on a single particle level. An analytical theory is developed which perfectly agrees with stochastic simulations and explains our findings.
Recent progress towards a quantum theory of laser-induced desorption and related phenomena is reviewed, for specific examples. These comprise the photodesorption of NO from Pt(111), the scanning tunnelling microscope and laser- induced desorption and switching of H at Si(100), and the electron stimulated desorption and dissociation of CO at Ru(0001). The theoretical methods used for nuclear dynamics range from open-system density matrix theory over nonadiabatically coupled multi-state models to electron-nuclear wavepackets. Also, aspects of time-dependent spectroscopy to probe ultrafast nonadiabatic processes at surfaces will be considered for the example of two-photon photoemission of solvated electrons in ice layers on Cu(111)
This paper focuses on the ground state phase diagram of a 1D spin-1/2 quantum Ising model with competing first and second nearest neighbour interactions known as the axial next nearest neighbour Ising model in the presence of a transverse magnetic field. Here, using quantum correlations, both numerically and analytically, some evidence is provided to clarify the identification of the ground state phase diagram. Local quantum correlations play a crucial role in detecting the critical lines either revealed or hidden by symmetry-breaking. A non-symmetry-breaking disorder transition line can be identified by the first derivative of both entanglement of formation and quantum discord between nearest neighbour spins. In addition, the quantum correlations between the second neighbour spins can also be used to reveal Kosterlitz-Thouless phase transition when their interaction strength grows and becomes closer to the first nearest neighbour one. The results obtained using the Jordan-Wigner transformation confirm the accuracy of the numerical case.
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.
It is demonstrated for the case of photo-excited ferrocyanide how time-resolved soft X-ray absorption spectroscopy in transmission geometry at the ligand K-edge and metal L-3-edge provides quantitatively equivalent valence electronic structure information, where signatures of photo-oxidation are assessed locally at the metal as well as the ligand. This allows for a direct and independent quantification of the number of photo-oxidized molecules at two soft X-ray absorption edges highlighting the sensitivity of X-ray absorption spectroscopy to the valence orbital occupation of 3d transition metal complexes throughout the soft X-ray range.