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Levy walks are continuous-time random-walk processes with a spatiotemporal coupling of jump lengths and waiting times. We here apply the Hermite polynomial method to study the behavior of LWs with power-law walking time density for four different cases. First we show that the known result for the infinite density of an unconfined, unbiased LW is consistently recovered. We then derive the asymptotic behavior of the probability density function (PDF) for LWs in a constant force field, and we obtain the corresponding qth-order moments. In a harmonic external potential we derive the relaxation dynamic of the LW. For the case of a Poissonian walking time an exponential relaxation behavior is shown to emerge. Conversely, a power-law decay is obtained when the mean walking time diverges. Finally, we consider the case of an unconfined, unbiased LW with decaying speed v(r ) = v0/./r. When the mean walking time is finite, a universal Gaussian law for the position-PDF of the walker is obtained explicitly.
Various mathematical Black-Scholes-Merton-like models of option pricing employ the paradigmatic stochastic process of geometric Brownian motion (GBM). The innate property of such models and of real stock-market prices is the roughly exponential growth of prices with time [on average, in crisis-free times]. We here explore the ensemble- and time averages of a multiplicative-noise stochastic process with power-law-like time-dependent volatility, sigma(t) similar to t(alpha), named scaled GBM (SGBM). For SGBM, the mean-squared displacement (MSD) computed for an ensemble of statistically equivalent trajectories can grow faster than exponentially in time, while the time-averaged MSD (TAMSD)-based on a sliding-window averaging along a single trajectory-is always linear at short lag times Delta. The proportionality factor between these the two averages of the time series is Delta/T at short lag times, where T is the trajectory length, similarly to GBM. This discrepancy of the scaling relations and pronounced nonequivalence of the MSD and TAMSD at Delta/T << 1 is a manifestation of weak ergodicity breaking for standard GBM and for SGBM with s (t)-modulation, the main focus of our analysis. The analytical predictions for the MSD and mean TAMSD for SGBM are in quantitative agreement with the results of stochastic computer simulations.
Self-organized coherence-incoherence patterns, called chimera states, have first been reported in systems of Kuramoto oscillators. For coupled excitable units, similar patterns where coherent units are at rest are called bump states. Here, we study bumps in an array of active rotators coupled by nonlocal attraction and global repulsion. We demonstrate how they can emerge in a supercritical scenario from completely coherent Turing patterns: a single incoherent unit appears in a homoclinic bifurcation, undergoing subsequent transitions to quasiperiodic and chaotic behavior, which eventually transforms into extensive chaos with many incoherent units. We present different types of transitions and explain the formation of coherence-incoherence patterns according to the classical paradigm of short-range activation and long-range inhibition.
We derive. the ensemble-and time-averaged mean-squared displacements (MSD, TAMSD) for Poisson-reset geometric Brownian motion (GBM), in agreement with simulations. We find MSD and TAMSD saturation for frequent resetting, quantify the spread of TAMSDs via the ergodicity-breaking parameter and compute distributions of prices. General MSD-TAMSD nonequivalence proves reset GBM nonergodic.
Hydrogels with a hierarchical structure were prepared from a new highly water-soluble crosslinker N,N,N',N'-tetramethyl-N,N'-bis(2-ethylmethacrylate)-propyl-1,3-diammonium dibromide and from the sulfobetaine monomer 2-(N-3-sulfopropyl-N,N-dimethyl ammonium)ethyl methacrylate. The free radical polymerization of the two compounds is rapid and yields near-transparent hydrogels with sizes up to 5 cm in diameter. Rheology shows a clear correlation between the monomer-to-crosslinker ratio and the storage and loss moduli of the hydrogels. Cryo-scanning electron microscopy, low-field nuclear magnetic resonance (NMR) spectroscopy, and small-angle X-ray scattering show that the gels have a hierarchical structure with features spanning the nanometer to the sub-millimeter scale. The NMR study is challenged by the marked inhomogeneity of the gels and the complex chemical structure of the sulfobetaine monomer. NMR spectroscopy shows how these complications can be addressed via a novel fitting approach that considers the mobility gradient along the side chain of methacrylate-based monomers.
Using magneto-optical Faraday and Kerr measurements, we investigate the magnetic and magnetooptical properties of a thick Bi-substituted gadolinium iron garnet film over a broad range of wavelengths (250-850 nm) and temperatures (150-300 K), including the magnetization compensation point, TM. We observe an exchange-bias-like effect in the vicinity of TM. By slightly changing the sample temperature, we can precisely tune the bias field, which reaches a magnitude 6 times higher than the coercive field. We explain this phenomenon by considering the short-range superexchange interaction and a change in the magnetic behavior when moving from the surface to the bulk of the film. This finding may lead to the development of single-film magneto-optical devices based on the exchange-bias effect.
This paper is concerned with correlation functions of stochastic systems with memory, a prominent example being a molecule or colloid moving through a complex (e.g. viscoelastic) fluid environment. Analytical investigations of such systems based on non-Markovian stochastic equations are notoriously difficult. A common approximation is that of a single-exponential memory, corresponding to the introduction of one auxiliary variable coupled to the Markovian dynamics of the main variable. As a generalization, we here investigate a class of 'toy' models with altogether three degrees of freedom, giving rise to more complex forms of memory. Specifically, we consider, mainly on an analytical basis, the under- and overdamped motion of a colloidal particle coupled linearly to two auxiliary variables, where the coupling between variables can be either reciprocal or non-reciprocal. Projecting out the auxiliary variables, we obtain non-Markovian Langevin equations with friction kernels and colored noise, whose structure is similar to that of a generalized Langevin equation. For the present systems, however, the non-Markovian equations may violate the fluctuation-dissipation relation as well as detailed balance, indicating that the systems are out of equilibrium. We then study systematically the connection between the coupling topology of the underlying Markovian system and various autocorrelation functions. We demonstrate that already two auxiliary variables can generate surprisingly complex (e.g. non-monotonic or oscillatory) memory and correlation functions. Finally, we show that a minimal overdamped model with two auxiliary variables and suitable non-reciprocal coupling yields correlation functions resembling those describing hydrodynamic backflow in an optical trap.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
Owing to global warming and particularly high regional ocean warming, both Thwaites and Pine Island Glaciers in the Amundsen region of the Antarctic Ice Sheet could lose their buttressing ice shelves over time. We analyse the possible consequences using the parallel ice sheet model (PISM), applying a simple cliff-calving parameterization and an ice melange-buttressing model. We find that the instantaneous loss of ice-shelf buttressing, due to enforced ice-shelf melting, initiates grounding-line retreat and triggers marine ice sheet instability (MISI). As a consequence, the grounding line progresses into the interior of the West Antarctic Ice Sheet and leads to a sea level contribution of 0.6 m within 100 a. By subjecting the exposed ice cliffs to cliff calving using our simplified parameterization, we also analyse marine ice cliff instability (MICI). In our simulations it can double or even triple the sea level contribution depending on the only loosely constrained parameter that determines the maximum cliff-calving rate. The speed of MICI depends on this upper bound of the calving rate, which is given by the ice melange buttressing the glacier. However, stabilization of MICI may occur for geometric reasons. Because the embayment geometry changes as MICI advances into the interior of the ice sheet, the upper bound on calving rates is reduced and the progress of MICI is slowed down. Although we cannot claim that our simulations bear relevant quantitative estimates of the effect of ice-melange buttressing on MICI, the mechanism has the potential to stop the instability. Further research is needed to evaluate its role for the past and future evolution of the Antarctic Ice Sheet.
Thanks to the combined effort s of scientist s in several research fields, the preceding decade has witnessed considerable progress in the use of conjugated polymers as emerging thermoelectric materials leading to significant improvements in performance and demonstration of a number of diverse applications. Despite these recent advances, systematic assessments of the impact of molecular design on thermoelectric properties are scarce. Although several reviews marginally highlight the role of chemical structure, the understanding of structure-performance relationships is still fragmented. An in-depth understanding of the relationship between molecular structure and thermoelectric properties will enable the rational design of next-generation thermoelectric polymers. To this end, this review showcases the state-of-the-art thermoelectric polymers, discusses structure-performance relationships, suggests strategies for improving thermoelectric performance that go beyond molecular design, and highlights some of the most impressive applications of thermoelectric polymers.
Organic-inorganic hybrids based on P3HT and mesoporous silicon for thermoelectric applications
(2024)
This thesis presents a comprehensive study on synthesis, structure and thermoelectric transport properties of organic-inorganic hybrids based on P3HT and porous silicon. The effect of embedding polymer in silicon pores on the electrical and thermal transport is studied. Morphological studies confirm successful polymer infiltration and diffusion doping with roughly 50% of the pore space occupied by conjugated polymer. Synchrotron diffraction experiments reveal no specific ordering of the polymer inside the pores. P3HT-pSi hybrids show improved electrical transport by five orders of magnitude compared to porous silicon and power factor values comparable or exceeding other P3HT-inorganic hybrids. The analysis suggests different transport mechanisms in both materials. In pSi, the transport mechanism relates to a Meyer-Neldel compansation rule. The analysis of hybrids' data using the power law in Kang-Snyder model suggests that a doped polymer mainly provides charge carriers to the pSi matrix, similar to the behavior of a doped semiconductor. Heavily suppressed thermal transport in porous silicon is treated with a modified Landauer/Lundstrom model and effective medium theories, which reveal that pSi agrees well with the Kirkpatrick model with a 68% percolation threshold. Thermal conductivities of hybrids show an increase compared to the empty pSi but the overall thermoelectric figure of merit ZT of P3HT-pSi hybrid exceeds both pSi and P3HT as well as bulk Si.
Additive manufacturing (AM) of metals and in particular laser powder bed fusion (LPBF) enables a degree of freedom in design unparalleled by conventional subtractive methods. To ensure that the designed precision is matched by the produced LPBF parts, a full understanding of the interaction between the laser and the feedstock powder is needed. It has been shown that the laser also melts subjacent layers of material underneath. This effect plays a key role when designing small cavities or overhanging structures, because, in these cases, the material underneath is feed-stock powder. In this study, we quantify the extension of the melt pool during laser illumination of powder layers and the defect spatial distribution in a cylindrical specimen. During the LPBF process, several layers were intentionally not exposed to the laser beam at various locations, while the build process was monitored by thermography and optical tomography. The cylinder was finally scanned by X-ray computed tomography (XCT). To correlate the positions of the unmolten layers in the part, a staircase was manufactured around the cylinder for easier registration. The results show that healing among layers occurs if a scan strategy is applied, where the orientation of the hatches is changed for each subsequent layer. They also show that small pores and surface roughness of solidified material below a thick layer of unmolten material (>200 mu m) serve as seeding points for larger voids. The orientation of the first two layers fully exposed after a thick layer of unmolten powder shapes the orientation of these voids, created by a lack of fusion.
Additive manufacturing (AM) processes enable the production of metal structures with exceptional design freedom, of which laser powder bed fusion (PBF-LB) is one of the most common. In this process, a laser melts a bed of loose feedstock powder particles layer-by-layer to build a structure with the desired geometry. During fabrication, the repeated melting and rapid, directional solidification create large temperature gradients that generate large thermal stress. This thermal stress can itself lead to cracking or delamination during fabrication. More often, large residual stresses remain in the final part as a footprint of the thermal stress. This residual stress can cause premature distortion or even failure of the part in service. Hence, knowledge of the residual stress field is critical for both process optimization and structural integrity.
Diffraction-based techniques allow the non-destructive characterization of the residual stress fields. However, such methods require a good knowledge of the material of interest, as certain assumptions must be made to accurately determine residual stress. First, the measured lattice plane spacings must be converted to lattice strains with the knowledge of a strain-free material state. Second, the measured lattice strains must be related to the macroscopic stress using Hooke's law, which requires knowledge of the stiffness of the material. Since most crystal structures exhibit anisotropic material behavior, the elastic behavior is specific to each lattice plane of the single crystal. Thus, the use of individual lattice planes in monochromatic diffraction residual stress analysis requires knowledge of the lattice plane-specific elastic properties. In addition, knowledge of the microstructure of the material is required for a reliable assessment of residual stress.
This work presents a toolbox for reliable diffraction-based residual stress analysis. This is presented for a nickel-based superalloy produced by PBF-LB. First, this work reviews the existing literature in the field of residual stress analysis of laser-based AM using diffraction-based techniques. Second, the elastic and plastic anisotropy of the nickel-based superalloy Inconel 718 produced by PBF-LB is studied using in situ energy dispersive synchrotron X-ray and neutron diffraction techniques. These experiments are complemented by ex situ material characterization techniques. These methods establish the relationship between the microstructure and texture of the material and its elastic and plastic anisotropy. Finally, surface, sub-surface, and bulk residual stress are determined using a texture-based approach. Uncertainties of different methods for obtaining stress-free reference values are discussed.
The tensile behavior in the as-built condition is shown to be controlled by texture and cellular sub-grain structure, while in the heat-treated condition the precipitation of strengthening phases and grain morphology dictate the behavior. In fact, the results of this thesis show that the diffraction elastic constants depend on the underlying microstructure, including texture and grain morphology. For columnar microstructures in both as-built and heat-treated conditions, the diffraction elastic constants are best described by the Reuss iso-stress model. Furthermore, the low accumulation of intergranular strains during deformation demonstrates the robustness of using the 311 reflection for the diffraction-based residual stress analysis with columnar textured microstructures. The differences between texture-based and quasi-isotropic approaches for the residual stress analysis are shown to be insignificant in the observed case. However, the analysis of the sub-surface residual stress distributions show, that different scanning strategies result in a change in the orientation of the residual stress tensor. Furthermore, the location of the critical sub-surface tensile residual stress is related to the surface roughness and the microstructure. Finally, recommendations are given for the diffraction-based determination and evaluation of residual stress in textured additively manufactured alloys.
The rapid uptake of renewable energy technologies in recent decades has increased the demand of energy researchers, policymakers and energy planners for reliable data on the spatial distribution of their costs and potentials. For onshore wind energy this has resulted in an active research field devoted to analysing these resources for regions, countries or globally. A particular thread of this research attempts to go beyond purely technical or spatial restrictions and determine the realistic, feasible or actual potential for wind energy. Motivated by these developments, this paper reviews methods and assumptions for analysing geographical, technical, economic and, finally, feasible onshore wind potentials. We address each of these potentials in turn, including aspects related to land eligibility criteria, energy meteorology, and technical developments of wind turbine characteristics such as power density, specific rotor power and spacing aspects. Economic aspects of potential assessments are central to future deployment and are discussed on a turbine and system level covering levelized costs depending on locations, and the system integration costs which are often overlooked in such analyses. Non-technical approaches include scenicness assessments of the landscape, constraints due to regulation or public opposition, expert and stakeholder workshops, willingness to pay/accept elicitations and socioeconomic cost-benefit studies. For each of these different potential estimations, the state of the art is critically discussed, with an attempt to derive best practice recommendations and highlight avenues for future research.
We study a non-Markovian and nonstationary model of animal mobility incorporating both exploration and memory in the form of preferential returns. Exact results for the probability of visiting a given number of sites are derived and a practical WKB approximation to treat the nonstationary problem is developed. A mean-field version of this model, first suggested by Song et al., [Modelling the scaling properties of human mobility, Nat. Phys. 6, 818 (2010)] was shown to well describe human movement data. We show that our generalized model adequately describes empirical movement data of Egyptian fruit bats (Rousettus aegyptiacus) when accounting for interindividual variation in the population. We also study the probability of visiting any site a given number of times and derive a mean-field equation. Our analysis yields a remarkable phase transition occurring at preferential returns which scale linearly with past visits. Following empirical evidence, we suggest that this phase transition reflects a trade-off between extensive and intensive foraging modes.
We study the ultrafast electronic transport of energy in a photoexcited nanoscale Au/Fe hetero-structure by modeling the spatiotemporal profile of energy densities that drives transient strain, which we quantify by femtosecond x-ray diffraction. This flow of energy is relevant for intrinsic demagnetization and ultrafast spin transport. We measured lattice strain for different Fe layer thicknesses ranging from few atomic layers to several nanometers and modeled the spatiotemporal flow of energy densities. The combination of a high electron-phonon coupling coefficient and a large Sommerfeld constant in Fe is found to yield electronic transfer of nearly all energy from Au to Fe within the first hundreds of femtoseconds.
Scaling up CSP
(2023)
Concentrating solar power (CSP) is one of the few scalable technologies capable of delivering dispatchable renewable power. Therefore, many expect it to shoulder a significant share of system balancing in a renewable electricity future powered by cheap, intermittent PV and wind power: the IEA, for example, projects 73 GW CSP by 2030 and several hundred GW by 2050 in its Net-Zero by 2050 pathway. In this paper, we assess how fast CSP can be expected to scale up and how long time it would take to get new, high-efficiency CSP technologies to market, based on observed trends and historical patterns. We find that to meaningfully contribute to net-zero pathways the CSP sector needs to reach and exceed the maximum historical annual growth rate of 30%/year last seen between 2010-2014 and maintain it for at least two decades. Any CSP deployment in the 2020s will rely mostly on mature existing technologies, namely parabolic trough and molten-salt towers, but likely with adapted business models such as hybrid CSP-PV stations, combining the advantages of higher-cost dispatchable and low-cost intermittent power. New third-generation CSP designs are unlikely to play a role in markets during the 2020s, as they are still at or before the pilot stage and, judging from past pilot-to-market cycles for CSP, they will likely not be ready for market deployment before 2030. CSP can contribute to low-cost zero-emission energy systems by 2050, but to make that happen, at the scale foreseen in current energy models, ambitious technology-specific policy support is necessary, as soon as possible and in several countries.
Thermal energy from concentrating solar thermal technologies (CST) may contribute to decarbonizing applications from heating and cooling, desalination, and power generation to commodities such as aluminium, hydrogen, ammonia or sustainable aviation fuels (SAF). So far, successful commercial-scale CST projects are restricted to solar industrial process heat (SIPH) and concentrating solar power (CSP) generation and, at least for the latter, depend on support from public policies that have been stagnating for years. As they are technologically similar, spillovers between SIPH or CSP and other emerging CST could accelerate commercialization across use cases while maximizing the impact of scarce support. Here, we review the technical potential for cross-fertilization between different CST applications and the ability of the current policy regime to enable this potential. Using working temperature as the key variable, we identify different clusters of current and emerging CST technologies. Low-temperature CST (<400℃) applications for heating, cooling and desalination already profit from the significant progress made in line-focussing CSP over the last 15 years. A newly emerging cluster of high temperature CST (>600℃) for solar chemistry and high-grade process heat has significant leverage for spillovers with point-focussing solar tower third-generation CSP currently under development. For these spillovers to happen, however, CSP policy designs would need to prioritize innovation for high working temperature and encourage modular plant design, by adequately remunerating hybridized plants with heat and power in and outputs that include energy sources beyond CST solar fields. This would enable synergies across applications and scales by incentivizing compatibility of modular CST components in multiple sectors and use cases.
In this study, we model a sequence of a confined and a full eruption, employing the relaxed end state of the confined eruption of a kink-unstable flux rope as the initial condition for the ejective one. The full eruption, a model of a coronal mass ejection, develops as a result of converging motions imposed at the photospheric boundary, which drive flux cancellation. In this process, parts of the positive and negative external flux converge toward the polarity inversion line, reconnect, and cancel each other. Flux of the same amount as the canceled flux transfers to a flux rope, increasing the free magnetic energy of the coronal field. With sustained flux cancellation and the associated progressive weakening of the magnetic tension of the overlying flux, we find that a flux reduction of approximate to 11% initiates the torus instability of the flux rope, which leads to a full eruption. These results demonstrate that a homologous full eruption, following a confined one, can be driven by flux cancellation.
We propose a simple and eco-friendly method for the formation of composite protein-mineral-microcapsules induced by ultrasound treatment. Protein- and nanoparticle-stabilized oil-in-water (O/W) emulsions loaded with different oils are prepared using high-intensity ultrasound. The formation of thin composite mineral proteinaceous shells is realized with various types of nanoparticles, which are pre-modified with Bovine Serum Albumin (BSA) and subsequently characterized by EDX, TGA, zeta potential measurements and Raman spectroscopy. Cryo-SEM and EDX mapping visualizations show the homogeneous distribution of the densely packed nanoparticles in the capsule shell. In contrast to the results reported in our previous paper,(1) the shell of those nanostructured composite microcapsules is not cross-linked by the intermolecular disulfide bonds between BSA molecules. Instead, a Pickering-Emulsion formation takes place because of the amphiphilicity-driven spontaneous attachment of the BSA-modified nanoparticles at the oil/water interface. Using colloidal particles for the formation of the shell of the microcapsules, in our case silica, hydroxyapatite and calcium carbonate nanoparticles, is promising for the creation of new functional materials. The nanoparticulate building blocks of the composite shell with different chemical, physical or morphological properties can contribute to additional, sometimes even multiple, features of the resulting capsules. Microcapsules with shells of densely packed nanoparticles could find interesting applications in pharmaceutical science, cosmetics or in food technology.