Molecular origin of the anisotropic dye orientation in emissive layers of organic light emitting diodes

Molecular orientation anisotropy of the emitter molecules used in organic light emitting diodes (OLEDs) can give rise to an enhanced light-outcoupling efficiency, when their transition dipole moments are oriented preferentially parallel to the substrate, and to a modified internal quantum efficiency, when their static dipole moments give rise to a locally modified internal electric field. Here, the orientation anisotropy of state-of-the-art phosphorescent dye molecules is ivestigated using a simulation approach which mimics the physical vapor deposition process of amorphous thin films. The simulations reveal for all studied systems significant orientation anisotropy. Various types are found, including a preference of the static dipole moments to a certain direction or axis. However, only few systems show an improved outcoupling efficiency. The outcoupling efficiency predicted by the simulations agrees with experimentally reported values. The simulations reveal in some cases a significant effect of the host molecules, and suggest that the driving force of molecular orientation lies in the molecule-specific van der Waals interactions of the dye molecule within the thin film surface. The electrostatic dipole-dipole interaction slightly reduces the anisotropy. These findings can be used for the future design of improved dye molecules

Orogenic lithosphere and slabs in the greater Alpine area – interpretations based on teleseismic P-wave tomography

Based on recent results of AlpArray, we propose a new model of Alpine collision that involves subduction and detachment of thick (∼ 180 km) European lithosphere. Our approach combines teleseismic P-wave tomography and existing local earthquake tomography (LET), allowing us to image the Alpine slabs and their connections with the overlying orogenic lithosphere at an unprecedented resolution. The images call into question the conventional notion that downward-moving lithosphere and slabs comprise only seismically fast lithosphere. We propose that the European lithosphere is heterogeneous, locally containing layered positive and negative Vp anomalies of up to 5 %–6 %. We attribute this layered heterogeneity to seismic anisotropy and/or compositional differences inherited from the Variscan and pre-Variscan orogenic cycles rather than to thermal anomalies. The lithosphere–asthenosphere boundary (LAB) of the European Plate therefore lies below the conventionally defined seismological LAB. In contrast, the lithosphere of the Adriatic Plate is thinner and has a lower boundary approximately at the base of strong positive Vp anomalies at 100–120 km. Horizontal and vertical tomographic slices reveal that beneath the central and western Alps, the European slab dips steeply to the south and southeast and is only locally still attached to the Alpine lithosphere. However, in the eastern Alps and Carpathians, this slab is completely detached from the orogenic crust and dips steeply to the north to northeast. This along-strike change in attachment coincides with an abrupt decrease in Moho depth below the Tauern Window, the Moho being underlain by a pronounced negative Vp anomaly that reaches eastward into the Pannonian Basin area. This negative Vp anomaly is interpreted as representing hot upwelling asthenosphere that heated the overlying crust, allowing it to accommodate Neogene orogen-parallel lateral extrusion and thinning of the ALCAPA tectonic unit (upper plate crustal edifice of Alps and Carpathians) to the east. A European origin of the northward-dipping, detached slab segment beneath the eastern Alps is likely since its down-dip length matches estimated Tertiary shortening in the eastern Alps accommodated by originally south-dipping subduction of European lithosphere. A slab anomaly beneath the Dinarides is of Adriatic origin and dips to the northeast. There is no evidence that this slab dips beneath the Alps. The slab anomaly beneath the Northern Apennines, also of Adriatic origin, hangs subvertically and is detached from the Apenninic orogenic crust and foreland. Except for its northernmost segment where it locally overlies the southern end of the European slab of the Alps, this slab is clearly separated from the latter by a broad zone of low Vp velocities located south of the Alpine slab beneath the Po Basin. Considered as a whole, the slabs of the Alpine chain are interpreted as highly attenuated, largely detached sheets of continental margin and Alpine Tethyan oceanic lithosphere that locally reach down to a slab graveyard in the mantle transition zone (MTZ)

Imaging structure and geometry of Alpine slabs by full waveform inversion of teleseismic body waves

The primary goal of this project was to use records of distant earthquakes from the AlpArray Seismic Network to contribute to the controversial debate about the structure, origin, and fate of subducted lithospheric plates in the deeper mantle beneath the Alps, such as possible slab detachments or changes in subduction polarity, to expand our understanding on mountain-building processes. Originally intended as a preliminary step before full-waveform inversion, we performed a teleseismic P-wave travel-time tomography (Paffrath et al., 2021b) based on waveforms recorded at over 600 temporary and permanent broadband stations of the AlpArray Seismic Network. An algorithm using a combination of automatic picking, beamforming and cross-correlation was developed to extract teleseismic travel times of direct P-waves from 331 events of magnitude > 5.5 recorded between 2015 and 2019 resulting in a database of over 162 000 highly accurate absolute P-wave travel times and travel-time residuals (Paffrath et al., 2021a). In addition, we developed an automatic picking algorithm based on multi-component autoregressive prediction and properties of the analytic signal. This algorithm was applied to a global data set of waveforms from over 6000 events of magnitude < 6 recorded between 1990 and 2019 at more than 25000 stations to obtain about 3.8 million P- and 3.2 million S-phase arrival times. We obtained models of P-wave velocities on a grid with 25 km lateral and 15 km depth spacing, encompassing the entire Alpine region, from the Massif Central to the Pannonian Basin and from the Po Plain to the river Main, down to a depth of 600 km. Hardly resolvable crustal heterogeneities were taken into account by a novel approach of direct incorporation of an external 3D a priori model of the crust and uppermost mantle into the starting model of the inversion. For forward travel-time predictions, a hybrid method was developed by combining ObsPy-Taup with the fast-marching code FM3D. The resulting model provides a detailed image of slab configuration beneath the Alpine and Apennine orogens that differs from previous studies. Major features are: (1) A partly overturned Adriatic slab beneath the Apennines reaching down to 400 km depth exhibiting progressive detachment towards the southeast; (2) a fast anomaly beneath the western Alps indicating a short western Alpine slab that ends at about 100 km depth; (3) a complex deep-reaching coherent fast anomaly beneath the Central Alps generally dipping to the SE down to about 400 km, detached from the overlying lithosphere in its eastern part but suggesting a slab of European origin; (4) a further deep-reaching, nearly vertically dipping high-velocity anomaly beneath the Eastern Alps, laterally well-separated in the upper 200 km from the slab beneath the central Alps but merging with it below, suggesting a slab beneath the eastern Alps of presumably European origin completely detached from the orogenic root so that a change in subduction polarity is not necessary. Very recent P-wave velocity models from teleseismic full-waveform inversion based on hybrid coupling of GEMINI and SPECFEM3D exhibit, in contrast to travel time tomography, surprisingly high resolution in the crust and uppermost mantle with a superb image of the Alpine and Apennine orogenic root and the Ivrea body; they confirm the general distribution of high-velocity anomalies found by traveltime tomography in the mantle below, but might allow new conclusions about the connection of the subducted slabs

Imaging structure and geometry of slabs in the greater Alpine area – a P-wave travel-time tomography using AlpArray Seismic Network data

We perform a teleseismic P-wave travel-time tomography to examine the geometry and structure of subducted lithosphere in the upper mantle beneath the Alpine orogen. The tomography is based on waveforms recorded at over 600 temporary and permanent broadband stations of the dense AlpArray Seismic Network deployed by 24 different European institutions in the greater Alpine region, reaching from the Massif Central to the Pannonian Basin and from the Po Plain to the river Main. Teleseismic travel times and travel-time residuals of direct teleseismic P waves from 331 teleseismic events of magnitude 5.5 and higher recorded between 2015 and 2019 by the AlpArray Seismic Network are extracted from the recorded waveforms using a combination of automatic picking, beamforming and cross-correlation. The resulting database contains over 162 000 highly accurate absolute P-wave travel times and travel-time residuals. For tomographic inversion, we define a model domain encompassing the entire Alpine region down to a depth of 600 km. Predictions of travel times are computed in a hybrid way applying a fast TauP method outside the model domain and continuing the wave fronts into the model domain using a fast marching method. We iteratively invert demeaned travel-time residuals for P-wave velocities in the model domain using a regular discretization with an average lateral spacing of about 25 km and a vertical spacing of 15 km. The inversion is regularized towards an initial model constructed from a 3D a priori model of the crust and uppermost mantle and a 1D standard earth model beneath. The resulting model provides a detailed image of slab configuration beneath the Alpine and Apenninic orogens. Major features are a partly overturned Adriatic slab beneath the Apennines reaching down to 400 km depth still attached in its northern part to the crust but exhibiting detachment towards the southeast. A fast anomaly beneath the western Alps indicates a short western Alpine slab whose easternmost end is located at about 100 km depth beneath the Penninic front. Further to the east and following the arcuate shape of the western Periadriatic Fault System, a deep-reaching coherent fast anomaly with complex internal structure generally dipping to the SE down to about 400 km suggests a slab of European origin limited to the east by the Giudicarie fault in the upper 200 km but extending beyond this fault at greater depths. In its eastern part it is detached from overlying lithosphere. Further to the east, well-separated in the upper 200 km from the slab beneath the central Alps but merging with it below, another deep-reaching, nearly vertically dipping high-velocity anomaly suggests the existence of a slab beneath the eastern Alps of presumably the same origin which is completely detached from the orogenic root. Our image of this slab does not require a polarity switch because of its nearly vertical dip and full detachment from the overlying lithosphere. Fast anomalies beneath the Dinarides are weak and concentrated to the northernmost part and shallow depths. Low-velocity regions surrounding the fast anomalies beneath the Alps to the west and northwest follow the same dipping trend as the overlying fast ones, indicating a kinematically coherent thick subducting lithosphere in this region. Alternatively, these regions may signify the presence of seismic anisotropy with a horizontal fast axis parallel to the Alpine belt due to asthenospheric flow around the Alpine slabs. In contrast, low-velocity anomalies to the east suggest asthenospheric upwelling presumably driven by retreat of the Carpathian slab and extrusion of eastern Alpine lithosphere towards the east while low velocities to the south are presumably evidence of asthenospheric upwelling and mantle hydration due to their position above the European slab

Spatio-temporal distribution of induced seismicity in flooded mines in the Ruhr area - interpretation by geomechanical numerical modelling

Induced seismicity during mine flooding is the focus of the FloodRisk project. One of the study areas is the Ruhr area, which is characterised by centuries of intensive coal mining. After the closure of the last mines, controlled flooding began. Within the FloodRisk project, we investigate ground uplift, stress changes due to pore pressure changes and the reactivation potential of faults to explain induced seismicity. We concentrate on the seismicity monitoring and geomechanics of the Haus Aden catchment, for which we investigate the relationship between water rise, tectonic stress and induced seismicity. The monitoring of seismicity is based on a network of up to 30 short-period seismic stations installed by the Ruhr University in the area of the former "Bergwerk Ost", which exhibited the highest seismicity in the Ruhr area during active mining. The stations cover an area of about 160 km 2 and are spaced between 0.5 and 3.5 km apart. They allow continuous monitoring of seismicity. Since 2019, more than 2200 induced events have been localised. A prerequisite for the interpretation of seismicity is a detailed localisation of the events. The relative localisation of the induced earthquakes has significantly reduced the location uncertainty and allowed the spatial and temporal evolution of earthquake clusters due to the rise in mine water levels to be studied. The resulting pattern of seismicity was compared with known underground structures. This comparison indicates that most of the events occur approximately 300 m below the main pillars between the longwall panels in the already flooded deepest level of the mine. A generic FE numerical model was developed for a section of the Heinrich Robert mine based on the geometry of the pillars, shafts and longwall panels. The stress data for model calibration are based on a compilation of the regional stress state in the eastern Ruhr area. For this purpose, hydraulic fracture tests carried out in the mines to minimise rock bursts were re-evaluated and compared with stress orientations derived from independent sources such as borehole fractures and earthquake source mechanisms. Using this 3D numerical approach, we conclude that there is increased vertical stress within and below the pillars as a result of stress arching. As the horizontal stress changes below the mine levels are small, this results in increasing differential stresses that can lead to the observed events below the mine level when the mine water level rises

Analyzing Dynamical Disorder for Charge Transport in Organic Semiconductors via Machine Learning

Organic semiconductors are indispensable for today’s display technologies in the form of organic light-emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long timescales are required, which is the case to compute static and dynamic energy disorder, i.e., the dominant factor to determine charge transport. Here, we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps are highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyze characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application-relevant materials properties of organic semiconductors and thus make these methods applicable for virtual materials design

Interpretable delta-learning of GW quasiparticle energies from GGA-DFT

Accurate prediction of the ionization potential and electron affinity energies of small molecules are important for many applications. Density functional theory (DFT) is computationally inexpensive, but can be very inaccurate for frontier orbital energies or ionization energies. The GW method is sufficiently accurate for many relevant applications, but much more expensive than DFT. Here we study how we can learn to predict orbital energies with GW accuracy using machine learning (ML) on molecular graphs and fingerprints using an interpretable delta-learning approach. ML models presented here can be used to predict quasiparticle energies of small organic molecules even beyond the size of the molecules used for training. We furthermore analyze the learned DFT-to-GW corrections by mapping them to specific localized fragments of the molecules, in order to develop an intuitive interpretation of the learned corrections, and thus to better understand DFT errors

Applying scattered wave tomography and joint inversion of high density (SWATH D) geophysical and petrophysical datasets to unravel Eastern Alpine crustal structure

This project harnesses the high density of seismic stations in AlpArray and the AlpArray complementary experiment SWATH D to significantly improve the resolution and reliability of the subsurface models by enabling the use of many different inversion methods to obtain and integrate the different results. These advanced models are vital for resolving the complex Alpine plate configuration and understanding how the crustal structure seen today reflects the dramatic changes in mountain building style and reorganisation of plate boundaries at about 20 Ma. We employ the joint inversion of seismological and petrophysical data sets in order to understand the intra-crustal structure, temperature, and petrophysical properties of crustal layers by inverting seismic data directly for the crust’s constituent mineral assemblages. Teleseismic full waveform inversion (FWI) provides a powerful tool for illuminating both the crustal and, complementing the joint inversion, intra-crustal structure. In our application of FWI, we increase the frequency content with the progression of the inversion. To perform FWI with teleseismic data at low frequencies, we couple the 1D code Gemini (Friederich and Dalkolmo, 1995) with the 3D code SPECFEM3D Cartesian for forward modelling and use the FWI code ASKI (Schumacher and Friederich, 2016) for computing waveform sensitivity kernels and performing the inversion. At higher frequencies we opt for a ray theory-based approach rather than full waveform modelling due to its high computational cost. We calculate high frequency P-phase synthetic seismograms by coupling various codes to obtain travel times, amplitudes and source time functions. ObsPy TauP, a 1D code, is used to determine travel times and ray paths in the bulk earth, while FM3D (de Kool et al., 2006), a 3D code, is employed in the study area. Subsequently, the ray paths are used to calculate amplitudes via dynamic ray tracing. Source time functions are obtained by fitting the recorded data. We intend to use the P-phase synthetic seismograms within the framework of ASKI to compute waveform sensitivity kernels. Subsequent inversion with these kernels could improve the resolution of the resulting models. First results of FWI at low frequencies up to 0.1 Hz (using the coupled Gemini-SPECFEM3D code for forward modelling) demonstrate a good agreement with the P-wave velocity models obtained from teleseismic travel time tomography by Paffrath et al. (2021) as part of the first phase of the SPP. Though derived from Fourier-transformed waveform data and currently only 24 events, the FWI model reduces the variance of the P-wave travel time residuals data set by 60 percent. Moreover, the FWI models exhibit surprisingly high resolution in the crust and uppermost mantle with a superb image of the Alpine and Apennine orogenic root and the Ivrea body probably by virtue of the presence of reflected and converted P- and S-phases in the considered time windows. Receiver functions and surface wave dispersion curves, calculated in partner projects, are usually jointly inverted for elastic properties. By utilising the strengths of Markov Chain Monte Carlo inversion, we are able to instead parameterise our model by temperature and mineral assemblage. This allows the introduction of geological-mineralogical constraints, in a probabilistic self-consistent manner, to the inversion. A further significant advantage is in interpretation where the probabilities of certain lithologies being present allows for a more seamless integration of qualitative geological data and a reduction in interpretation biases present when only seismic velocities are presented

Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning

Organic semiconductors are indispensable for today's display technologies in form of organic light emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even design new organic semiconductors with higher charge carrier mobility, computational approaches, in particular multiscale models, are becoming increasingly important. However, such models are computationally very costly, especially when large systems and long time scales are required, which is the case to compute static and dynamic energy disorder, i.e. dominant factor to determine charge transport. Here we overcome this drawback by integrating machine learning models into multiscale simulations. This allows us to obtain unprecedented insight into relevant microscopic materials properties, in particular static and dynamic disorder contributions for a series of application-relevant molecules. We find that static disorder and thus the distribution of shallow traps is highly asymmetrical for many materials, impacting widely considered Gaussian disorder models. We furthermore analyse characteristic energy level fluctuation times and compare them to typical hopping rates to evaluate the importance of dynamic disorder for charge transport. We hope that our findings will significantly improve the accuracy of computational methods used to predict application relevant materials properties of organic semiconductors, and thus make these methods applicable for virtual materials design