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The remarkable progress of metal halide perovskites in photovoltaics has led to the power conversion efficiency approaching 26%. However, practical applications of perovskite-based solar cells are challenged by the stability issues, of which the most critical one is photo-induced degradation. Bare CH3NH3PbI3 perovskite films are known to decompose rapidly, with methylammonium and iodine as volatile species and residual solid PbI2 and metallic Pb, under vacuum under white light illumination, on the timescale of minutes. We find, in agreement with previous work, that the degradation is non-uniform and proceeds predominantly from the surface, and that illumination under N-2 and ambient air (relative humidity 20%) does not induce substantial degradation even after several hours. Yet, in all cases the release of iodine from the perovskite surface is directly identified by X-ray photoelectron spectroscopy. This goes in hand with a loss of organic cations and the formation of metallic Pb. When CH3NH3PbI3 films are covered with a few nm thick organic capping layer, either charge selective or non-selective, the rapid photodecomposition process under ultrahigh vacuum is reduced by more than one order of magnitude, and becomes similar in timescale to that under N-2 or air. We conclude that the light-induced decomposition reaction of CH3NH3PbI3, leading to volatile methylammonium and iodine, is largely reversible as long as these products are restrained from leaving the surface. This is readily achieved by ambient atmospheric pressure, as well as a thin organic capping layer even under ultrahigh vacuum. In addition to explaining the impact of gas pressure on the stability of this perovskite, our results indicate that covalently "locking" the position of perovskite components at the surface or an interface should enhance the overall photostability.
Organic solar cells with large insensitivity to donor polymer molar mass across all acceptor classes
(2020)
Donor polymer number-average molar mass (M-n) has long been known to influence organic photovoltaic (OPV) performance via changes in both the polymer properties and the resulting bulk heterojunction morphology. The exact nature of these M-n effects varies from system to system, although there is generally some intermediate M-n that results in optimal performance. Interestingly, our earlier work with the difluorobenzotriazole (FTAZ)-based donor polymer, paired with either N2200 (polymer acceptor) or PC61BM (fullerene acceptor), PcBm demonstrated <10% variation in power conversion efficiency and a consistent morphology over a large span of M-n (30 kg/mol to over 100 kg/mol). Would such insensitivity to polymer M-n still hold true when prevailing small molecular acceptors were used with FTAZ? To answer this question, we explored the impact of FTAZ on OPVs with ITIC, a high-performance small-molecule fused-ring electron acceptor (FREA). By probing the photovoltaic characteristics of the resulting OPVs, we show that a similar FTAZ mn insensitivity is also found in the FTAZ:ITIC system. This study highlights a single-donor polymer which, when paired with an archetypal fullerene, polymer, and FREA, results in systems that are largely insensitive to donor M. Our results may have implications in polymer batch-to-batch reproducibility, in particular, relaxing the need for tight M-n control during synthesis.
Recent experiments on laser-dissociation of aligned homonuclear diatomic molecules show an asymmetric forward-backward (spatial) electron-localization along the laser polarization axis. Most theoretical models attribute this asymmetry to interference effects between gerade and ungerade vibronic states. Presumably due to alignment, these models neglect molecular rotations and hence infer an asymmetric (post-dissociation) charge distribution over the two identical nuclei. In this paper, we question the equivalence that is made between spatial electron-localization, observed in experiments, and atomic electron-localization, alluded by these theoretical models. We show that (seeming) agreement between these models and experiments is due to an unfortunate omission of nuclear permutation symmetry, i.e., quantum statistics. Enforcement of the latter requires mandatory inclusion of the molecular rotational degree of freedom, even for perfectly aligned molecules. Unlike previous interpretations, we ascribe spatial electron-localization to the laser creation of a rovibronic wavepacket that involves field-free molecular eigenstates with opposite space-inversion symmetry i.e., even and odd parity. Space-inversion symmetry breaking would then lead to an asymmetric distribution of the (space-fixed) electronic density over the forward and backward hemisphere. However, owing to the simultaneous coexistence of two indistinguishable molecular orientational isomers, our analytical and computational results show that the post-dissociation electronic density along a specified space-fixed axis is equally shared between the two identical nuclei-a result that is in perfect accordance with the principle of the indistinguishability of identical particles. Published under an exclusive license by AIP Publishing.
Context.
The supergiant ionized shell SMC-SGS 1 (DEM 167), which is located in the outer Wing of the Small Magellanic Cloud (SMC), resembles structures that originate from an energetic star-formation event and later stimulate star formation as they expand into the ambient medium. However, stellar populations within and surrounding SMC-SGS 1 tell a different story. Aims. We present a photometric study of the stellar population encompassed by SMC-SGS 1 in order to trace the history of such a large structure and its potential influence on star formation within the low-density, low-metallicity environment of the SMC.
Methods.
For a stellar population that is physically associated with SMC-SGS 1, we combined near-ultraviolet (NUV) photometry from the Galaxy Evolution Explorer with archival optical (V-band) photometry from the ESO Danish 1.54 m Telescope. Given their colors and luminosities, we estimated stellar ages and masses by matching observed photometry to theoretical stellar isochrone models. Results. We find that the investigated region supports an active, extended star-formation event spanning similar to 25-40 Myr ago, as well as continued star formation into the present. Using a standard initial mass function, we infer a lower bound on the stellar mass from this period of similar to 3 x 10(4) M-circle dot, corresponding to a star-formation intensity of similar to 6 x 10(-3) M-circle dot kpc(-2) yr(-1).
Conclusions.
The spatial and temporal distributions of young stars encompassed by SMC-SGS 1 imply a slow, consistent progression of star formation over millions of years. Ongoing star formation, both along the edge and interior to SMC-SGS 1, suggests a combined stimulated and stochastic mode of star formation within the SMC Wing. We note that a slow expansion of the shell within this low-density environment may preserve molecular clouds within the volume of the shell, leaving them to form stars even after nearby stellar feedback expels local gas and dust.
The DNA interaction with cis-isomers of photosensitive azobenzene-containing surfactants was studied by both experimental methods and computer simulation. It was shown that before the organization of micelles, such surfactants in the cis-conformation form associates of only a single type with a disordered orientation of molecules. In contrast, for trans-isomers, there exist two types of associates with head-to-head or head-to-tail orientations of molecules in dependence on salt concentration in a solution. The comparison of cis- and trans-isomer binding to DNA and the influence of salt concentration on the formation of their complexes with DNA were studied. It was shown that cis-isomers interact with phosphate groups of DNA and that their molecules were also located along the minor groove of DNA.
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.
Seasonal forecasts are of great interest in many areas. Knowing the amount of precipitation for the upcoming season in regions of water scarcity would facilitate a better water management. If farmers knew the weather conditions of the upcoming summer at sowing time, they could select those cereal species that are best adapted to these conditions. This would allow farmers to improve the harvest and potentially even reduce the amount of pesticides used. However, the undoubted advantages of seasonal forecasts are often opposed by their high degree of uncertainty. The great challenge of generating seasonal forecasts with lead times of several months mainly originates from the chaotic nature of the earth system. In a chaotic system, even tiny differences in the initial conditions can lead to strong deviations in the system’s state in the long run.
In this dissertation we propose an emergent machine learning approach for seasonal forecasting, called the AnlgModel. The AnlgModel combines the analogue method with myopic feature selection and bootstrapping. To benchmark the abilities of the AnlgModel we apply it to seasonal cyclone activity forecasts in the North Atlantic and Northwest Pacific. The AnlgModel demonstrates competitive hindcast skills with two operational forecasts and even outperforms these for long lead times.
In the second chapter we comprehend the forecasting strategy of the Anlg-Model. We thereby analyse the analogue selection process for the 2017 North Atlantic and the 2018 Northwest Pacific seasonal cyclone activity. The analysis shows that those climate indices which are known to influence the seasonal cyclone activity, such as the Niño 3.4 SST, are correctly represented among the selected analogues. Furthermore the selected analogues reflect large-scale climate patterns that were identified by expert reports as being determinative for these particular seasons.
In the third chapter we analyse the features that are used by the AnlgModel for its predictions. We therefore inspect the feature relevance (FR). The FR patterns learned by the AnlgModel show a high congruence with the predictor regions used by the operational forecasts. However, the AnlgModel also discovered new features, such as the SST anomaly in the Gulf of Guinea during November. This SST pattern exhibits a remarkably high predictive potential for the upcoming Atlantic hurricane activity.
In the final chapter we investigate potential mechanisms, that link two of these regions with high feature relevance to the Atlantic hurricane activity. We mainly focus on ocean surface transport. The ocean surface flow paths are calculated using Lagrangian particle analysis. We demonstrate that the FR patterns in the region of the Canary islands do not correspond with ocean surface transport. It is instead likely that these FR patterns fingerprint a wind transport of latent heat. The second region to be studied is situated in the Gulf of Guinea. Our analysis shows that the FR patterns seen there do fingerprint ocean surface transport. However, our simulations also show that at least one other mechanism is involved in linking the Gulf of Guinea SST anomaly in November to the hurricane activity of the upcoming season.
In this work the AnlgModel does not only demonstrate its outstanding forecast skills but also shows its capabilities as research tool for detecting oceanic and atmospheric mechanisms.
Laser-induced breakdown spectroscopy (LIBS) analysers are becoming increasingly common for material classification purposes. However, to achieve good classification accuracy, mostly noncompact units are used based on their stability and reproducibility. In addition, computational algorithms that require significant hardware resources are commonly applied. For performing measurement campaigns in hard-to-access environments, such as mining sites, there is a need for compact, portable, or even handheld devices capable of reaching high measurement accuracy. The optics and hardware of small (i.e., handheld) devices are limited by space and power consumption and require a compromise of the achievable spectral quality. As long as the size of such a device is a major constraint, the software is the primary field for improvement. In this study, we propose a novel combination of handheld LIBS with non-negative tensor factorisation to investigate its classification capabilities of copper minerals. The proposed approach is based on the extraction of source spectra for each mineral (with the use of tensor methods) and their labelling based on the percentage contribution within the dataset. These latent spectra are then used in a regression model for validation purposes. The application of such an approach leads to an increase in the classification score by approximately 5% compared to that obtained using commonly used classifiers such as support vector machines, linear discriminant analysis, and the k-nearest neighbours algorithm.
We analyze historical data of stock-market prices for multiple financial indices using the concept of delay-time averaging for the financial time series (FTS). The region of validity of our recent theoretical predictions [Cherstvy A G et al 2017 New J. Phys. 19 063045] for the standard and delayed time-averaged mean-squared 'displacements' (TAMSDs) of the historical FTS is extended to all lag times. As the first novel element, we perform extensive computer simulations of the stochastic differential equation describing geometric Brownian motion (GBM) which demonstrate a quantitative agreement with the analytical long-term price-evolution predictions in terms of the delayed TAMSD (for all stock-market indices in crisis-free times). Secondly, we present a robust procedure of determination of the model parameters of GBM via fitting the features of the price-evolution dynamics in the FTS for stocks and cryptocurrencies. The employed concept of single-trajectory-based time averaging can serve as a predictive tool (proxy) for a mathematically based assessment and rationalization of probabilistic trends in the evolution of stock-market prices.
We report a comparison of two photonic techniques for single-molecule sensing: fluorescence nanoscopy and optoplasmonic sensing. As the test system, oligonucleotides with and without fluorescent labels are transiently hybridized to complementary "docking" strands attached to gold nanorods. Comparing the measured single-molecule kinetics helps to examine the influence of the fluorescent labels as well as factors arising from different sensing geometries. Our results demonstrate that DNA dissociation is not significantly altered by the fluorescent labels and that DNA association is affected by geometric factors in the two techniques. These findings open the door to exploiting plasmonic sensing and fluorescence nanoscopy in a complementary fashion, which will aid in building more powerful sensors and uncovering the intricate effects that influence the behavior of single molecules.