530 Physik
Refine
Year of publication
- 2024 (11)
- 2023 (33)
- 2022 (190)
- 2021 (95)
- 2020 (183)
- 2019 (237)
- 2018 (238)
- 2017 (125)
- 2016 (36)
- 2015 (31)
- 2014 (26)
- 2013 (8)
- 2012 (18)
- 2011 (15)
- 2010 (13)
- 2009 (11)
- 2008 (7)
- 2007 (22)
- 2006 (49)
- 2005 (26)
- 2004 (30)
- 2003 (12)
- 2002 (8)
- 2001 (8)
- 2000 (4)
- 1999 (5)
- 1998 (6)
- 1997 (7)
- 1996 (7)
- 1995 (9)
- 1994 (8)
- 1989 (1)
- 1972 (1)
Document Type
- Article (886)
- Doctoral Thesis (362)
- Postprint (95)
- Other (49)
- Preprint (36)
- Habilitation Thesis (22)
- Review (12)
- Master's Thesis (10)
- Monograph/Edited Volume (4)
- Course Material (2)
Keywords
- diffusion (43)
- anomalous diffusion (31)
- gamma rays: general (20)
- synchronization (18)
- Synchronisation (16)
- organic solar cells (16)
- stochastic processes (14)
- ISM: supernova remnants (13)
- cosmic rays (13)
- data analysis (12)
Institute
- 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.