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We have analysed an archival XMM-Newton EPIC observation that serendipitously covered the sky position of a variable X-ray source AX J1714.1-3912, previously suggested to be a Supergiant Fast X-ray Transient (SFXT). During the XMM-Newton observation the source is variable on a timescale of hundred seconds and shows two luminosity states, with a flaring activity followed by unflared emission, with a variability amplitude of a factor of about 50. We have discovered an intense iron emission line with a centroid energy of 6.4 keV in the power law-like spectrum, modified by a large absorption (N-H similar to 10(24) cm(-2)), never observed before from this source. This X-ray spectrum is unusual for an SFXT, but resembles the so-called 'highly obscured sources', high mass X-ray binaries (HMXBs) hosting an evolved B[e] supergiant companion (sgB[e]). This might suggest that AX J1714.1-3912 is a new member of this rare type of HMXBs, which includes IGR J16318-4848 and CI Camelopardalis. Increasing this small population of sources would be remarkable, as they represent an interesting short transition evolutionary stage in the evolution of massive binaries. Nevertheless, AX J1714.1-3912 appears to share X-ray properties of both kinds of HMXBs (SFXT versus sgB[e] HMXB). Therefore, further investigations of the companion star are needed to disentangle the two hypothesis.
X-rays are integral to furthering our knowledge of exoplanetary systems. In this work we discuss the use of X-ray observations to understand star-planet interac- tions, mass-loss rates of an exoplanet’s atmosphere and the study of an exoplanet’s atmospheric components using future X-ray spectroscopy.
The low-mass star GJ 1151 was reported to display variable low-frequency radio emission, which is an indication of coronal star-planet interactions with an unseen exoplanet. In chapter 5 we report the first X-ray detection of GJ 1151’s corona based on XMM-Newton data. Averaged over the observation, we detect the star with a low coronal temperature of 1.6 MK and an X-ray luminosity of LX = 5.5 × 1026 erg/s. This is compatible with the coronal assumptions for a sub-Alfvénic star- planet interaction origin of the observed radio signals from this star.
In chapter 6, we aim to characterise the high-energy environment of known ex- oplanets and estimate their mass-loss rates. This work is based on the soft X-ray instrument on board the Spectrum Roentgen Gamma (SRG) mission, eROSITA, along with archival data from ROSAT, XMM-Newton, and Chandra. We use these four X-ray source catalogues to derive X-ray luminosities of exoplanet host stars in the 0.2-2 keV energy band. A catalogue of the mass-loss rates of 287 exoplan- ets is presented, with 96 of these planets characterised for the first time using new eROSITA detections. Of these first time detections, 14 are of transiting exoplanets that undergo irradiation from their host stars that is of a level known to cause ob- servable evaporation signals in other systems, making them suitable for follow-up observations.
In the next generation of space observatories, X-ray transmission spectroscopy of an exoplanet’s atmosphere will be possible, allowing for a detailed look into the atmospheric composition of these planets. In chapter 7, we model sample spectra using a toy model of an exoplanetary atmosphere to predict what exoplanet transit observations with future X-ray missions such as Athena will look like. We then estimate the observable X-ray transmission spectrum for a typical Hot Jupiter-type exoplanet, giving us insights into the advances in X-ray observations of exoplanets in the decades to come.
Predicting the electron population of Earth's ring current during geomagnetic storms still remains a challenging task.
In this work, we investigate the sensitivity of 10 keV ring current electrons to different driving processes, parameterised by the Kp index, during several moderate and intense storms.
Results are validated against measurements from the Van Allen Probes satellites. Perturbing the Kp index allows us to identify the most dominant processes for moderate and intense storms respectively.
We find that during moderate storms (Kp < 6) the drift velocities mostly control the behaviour of low energy electrons, while loss from wave-particle interactions is the most critical parameter for quantifying the evolution of intense storms (Kp > 6). Perturbations of the Kp index used to drive the boundary conditions at GEO and set the plasmapause location only show a minimal effect on simulation results over a limited L range.
It is further shown that the flux at L & SIM; 3 is more sensitive to changes in the Kp index compared to higher L shells, making it a good proxy for validating the source-loss balance of a ring current model.
Differential absorption spectroscopy techniques serve as powerful techniques to study the excited species in organic solar cells. However, it has always been challenging to employ these techniques for characterizing thick-junction organic solar cells, especially when a reflective top contact is involved. In this work, we present a detailed and systematic study on how a combination of the presence of the interference effect and a nonuniform charge-distribution profile, severely manipulates experimental spectra and the decay dynamics. Furthermore, we provide a practical methodology to correct these optical artifacts in differential absorption spectroscopies. The results and the proposed correction method generally apply to all kinds of differential absorption spectroscopy techniques and various thin-film systems, such as organics, perovskites, kesterites, and two-dimensional materials. Notably, it is found that the shape of differential absorption spectra can be strongly distorted, starting from 150-nm active-layer thickness; this matches the thickness range of thick-junction organic solar cells and most perovskite solar cells and needs to be carefully considered in experiments. In addition, the decay dynamics of differential absorption spectra is found to be disturbed by optical artifacts under certain conditions. With the help of the proposed correction formalism, differential spectra and the decay dynamics can be characterized on the full device of thin-film solar cells in transmission mode and yield accurate and reliable results to provide design rules for further progress.
Transparent conductive materials based on indium oxide remain yet irreplaceable in various optoelectronic applications. Amorphous oxides appear especially attractive for technology as they are isotropic, demonstrate relatively high electron mobility and can be processed at low temperatures. Among them is indium zinc oxide (IZO) with a large zinc content that is crucial for keeping the amorphous state but redundant for the doping. In this work we investigated water-free and water containing IZO films obtained by radio frequency sputtering. The correlation between temperature driven changes of the chemical state, the optical and electrical properties as well as the progression of crystallization was in focus. Such characterization methods as: scanning electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, temperature dependent Hall-effect measurements and others were applied. Temperature dependent electrical properties of amorphous IZO and IZO:H2O films were found to evolve similarly. Based on our experience in In2O3:H2O (In2O3:H or IOH) we proposed an explanation for the changes observed. Water admixture was found to decrease crystallization temperature of IZO significantly from similar to 550 degrees C to similar to 280 degrees C. Herewith, the presence and concentration of water and/or hydroxyls was found to determine Zn distribution in the film. In particular, Zn enrichment was detected at the film's surface respective to the high water and/or hydroxyl amount. Raman spectra revealed a two-dimensional crystallization of w-ZnO which precedes regardless water presence an extensive In2O3 crystallization. An abrupt loss of electron mobility as a result of crystallization was attributed to the formation of ZnO interlayer on grain boundaries.
Computer-based analysis of preservice teachers' written reflections could enable educational scholars to design personalized and scalable intervention measures to support reflective writing. Algorithms and technologies in the domain of research related to artificial intelligence have been found to be useful in many tasks related to reflective writing analytics such as classification of text segments. However, mostly shallow learning algorithms have been employed so far. This study explores to what extent deep learning approaches can improve classification performance for segments of written reflections. To do so, a pretrained language model (BERT) was utilized to classify segments of preservice physics teachers' written reflections according to elements in a reflection-supporting model. Since BERT has been found to advance performance in many tasks, it was hypothesized to enhance classification performance for written reflections as well. We also compared the performance of BERT with other deep learning architectures and examined conditions for best performance. We found that BERT outperformed the other deep learning architectures and previously reported performances with shallow learning algorithms for classification of segments of reflective writing. BERT starts to outperform the other models when trained on about 20 to 30% of the training data. Furthermore, attribution analyses for inputs yielded insights into important features for BERT's classification decisions. Our study indicates that pretrained language models such as BERT can boost performance for language-related tasks in educational contexts such as classification.
Uppsala and Berkeley
(2022)
The development of modern photoelectron spectroscopy is reviewed with a special focus on the importance of research at Uppsala University and at Berkeley. The influence of two pioneers, Kai Siegbahn and Dave Shirley, is underlined. Early interaction between the two centers helped to kick-start the field. Both laboratories have continued to play an important role in the field, both in terms of creating new experimental capabilities and developing the theoretical understanding of the spectroscopic processes.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
Anomalous diffusion or, more generally, anomalous transport, with nonlinear dependence of the mean-squared displacement on the measurement time, is ubiquitous in nature. It has been observed in processes ranging from microscopic movement of molecules to macroscopic, large-scale paths of migrating birds. Using data from multiple empirical systems, spanning 12 orders of magnitude in length and 8 orders of magnitude in time, we employ a method to detect the individual underlying origins of anomalous diffusion and transport in the data. This method decomposes anomalous transport into three primary effects: long-range correlations (“Joseph effect”), fat-tailed probability density of increments (“Noah effect”), and nonstationarity (“Moses effect”). We show that such a decomposition of real-life data allows us to infer nontrivial behavioral predictions and to resolve open questions in the fields of single-particle tracking in living cells and movement ecology.
The manufacturability of metallic alloys using laser-based additive manufacturing methods such as laser powder bed fusion has substantially improved within the last decade. However, local melting and solidification cause hierarchically structured and crystallographically textured microstructures possessing large residual stress. Such microstructures are not only the origin of mechanical anisotropy but also pose metrological challenges for the diffraction-based residual stress determination. Here we demonstrate the influence of the build orientation and the texture on the microstructure and consequently the mechanical anisotropy of as-built Inconel 718. For this purpose, we manufactured specimens with [001]/[011]-, [001]- and [011]/[11 (1) over bar]-type textures along their loading direction. In addition to changes in the Young's moduli, the differences in the crystallographic textures result in variations of the yield and ultimate tensile strengths. With this in mind, we studied the anisotropy on the micromechanical scale by subjecting the specimens to tensile loads along the different texture directions during in situ neutron diffraction experiments. In this context, the response of multiple lattice planes up to a tensile strain of 10% displayed differences in the load partitioning and the residual strain accumulation for the specimen with [011]/[(1) over bar 11]-type texture. However, the relative behavior of the specimens possessing an [001] /[011]- and [001]-type texture remained qualitatively similar. The consequences on the metrology of residual stress determination methods are discussed.