Threefold rotational symmetry in hexagonally shaped core–shell (In,Ga)As/GaAs nanowires revealed by coherent X-ray diffraction imaging

Coherent X-ray diffraction imaging at symmetric hhh Bragg reflections was used to resolve the structure of GaAs/In$_{0.15}$Ga$_{0.85}$As/GaAs core–shell–shell nanowires grown on a silicon (111) substrate. Diffraction amplitudes in the vicinity of GaAs 111 and GaAs 333 reflections were used to reconstruct the lost phase information. It is demonstrated that the structure of the core–shell–shell nanowire can be identified by means of phase contrast. Interestingly, it is found that both scattered intensity in the (111) plane and the reconstructed scattering phase show an additional threefold symmetry superimposed with the shape function of the investigated hexagonal nanowires. In order to find the origin of this threefold symmetry, elasticity calculations were performed using the finite element method and subsequent kinematic diffraction simulations. These suggest that a non-hexagonal (In,Ga)As shell covering the hexagonal GaAs core might be responsible for the observation

Threefold rotational symmetry in hexagonally shaped core–shell (In,Ga)As/GaAs nanowires revealed by coherent X-ray diffraction imaging

Coherent X-ray diffraction imaging at symmetric hhh Bragg reflections was used to resolve the structure of GaAs/In0.15Ga0.85As/GaAs core–shell–shell nanowires grown on a silicon (111) substrate. Diffraction amplitudes in the vicinity of GaAs 111 and GaAs 333 reflections were used to reconstruct the lost phase information. It is demonstrated that the structure of the core–shell–shell nanowire can be identified by means of phase contrast. Interestingly, it is found that both scattered intensity in the (111) plane and the reconstructed scattering phase show an additional threefold symmetry superimposed with the shape function of the investigated hexagonal nanowires. In order to find the origin of this threefold symmetry, elasticity calculations were performed using the finite element method and subsequent kinematic diffraction simulations. These suggest that a non-hexagonal (In,Ga)As shell covering the hexagonal GaAs core might be responsible for the observation

ATHENA Research Book

The ATHENA European University is an alliance of nine Higher Education Institutions with the mission of fostering excellence in research and innovation by facilitating international cooperation. The ATHENA acronym stands for Advanced Technologies in Higher Education Alliance. The partner institutions are from France, Germany, Greece, Italy, Lithuania, Portugal, and Slovenia: the University of Orléans, the University of Siegen, the Hellenic Mediterranean University, the Niccolò Cusano University, the Vilnius Gediminas Technical University, the Polytechnic Institute of Porto, and the University of Maribor. In 2022 institutions from Poland and Spain joined the alliance: the Maria Curie-Skłodowska University and the University of Vigo. This research book presents a selection of the ATHENA university partners' research activities. It incorporates peer-reviewed original articles, reprints and student contributions. The ATHENA Research Book provides a platform that promotes joint and interdisciplinary research projects of both advanced and early-career researchers

Navigieren

Prof. Dr. Jens Schröter, Christoph Borbach, Max Kanderske und Prof. Dr. Benjamin Beil sind Herausgeber der Reihe. Die Herausgeber*innen der einzelnen Hefte sind renommierte Wissenschaftler*innen aus dem In- und Ausland.Navigieren ist längst kein Unikum professionalisierter Seefahrer:innen mehr, sondern als Smartphone- und Browser-Praktik fester Bestandteil des vernetzten digitalen Alltags. Da Wegfindungen durch On- und Offline-Räume navigationsspezifische Formen von Medienkompetenz voraussetzen und hervorbringen, fordern sie die Intensivierung der medienkulturwissenschaftlichen Beschäftigung mit den situierten und technisierten Medienpraktiken der Navigation geradezu heraus. Die Ausgabe nimmt diesen Befund zum Anlass, polyperspektivische Zugänge zum »Navigieren« vorzustellen. Die körper-, kultur- und medientechnischen Facetten des Navigierens stehen dabei ebenso im Fokus wie ihre historischen Ausgestaltungen, die Arbeit am und im Datenmaterial von Navigationsmedien und die Theoretisierung postdigitaler Sensor-Medien-Kulturen, die dem Umstand Rechnung trägt, dass es nicht allein Daten, Dinge und Körper sind, die es zu navigieren gilt, sondern zunehmend nicht-menschliche Akteure selbst zielgerichtete Raumdurchquerungen praktizieren. Fehlte es in der (deutschsprachigen) Medienkulturwissenschaft bislang an einer Bündelung heterogener navigationsspezifischer Forschungsarbeiten, gibt diese Ausgabe einen Überblick über das Feld, seine Forscher:innen und Fragestellungen. Denn trotz des Spatial Turns in den Humanities und der gegenwärtigen Konjunktur geomedialer Arbeiten, scheint die synthetisierende Fokussierung auf Medien und Praktiken des Navigierens in historischer, ethnografischer, technischer und theoretischer Perspektive bislang ein Desiderat darzustellen.Navigation is no longer unique to the context of professional seafaring, but has become an integral part of networked digital everyday life enabled through smartphones and web browsers. Indeed, finding one’s way through online and offline spaces increasingly presupposes and produces specific forms of media competence one could call »navigational«. In this, a ›media cultural studies‹ perspective on the situated and ›technologized‹ media practices of navigation becomes imperative to understanding the contemporary media landscape. Issue 1/22 of Navigationen answers this call by presenting polyperspectival approaches to »navigating«. The contributions discuss the bodily, cultural, and media-technical facets of navigation, as well as its historical forms, the work on and in the data produced by and with navigational media, and the theorization of post-digital ›sensor media cultures‹. In doing so, the issue acknowledges that not only do data, things, and bodies need to be ›navigated‹ in the context of logistics, but that the increasingly autonomous wayfinding processes of non-human actors change the notion of navigation itself. As (German language) media cultural studies has so far lacked a convincing compilation of heterogeneous approaches to studying navigation, this issue provides an overview of the field, its researchers and questions. Despite the spatial turn in the humanities and a recent surge in geomedia studies, an approach towards the media and practices of navigation that combines historical, ethnographic, technical and theoretical perspectives, has remained a desideratum until now. The issue fills this gap

Application and Evaluation of a Hierarchical Patch Clustering Method for Remote Sensing Images

In this paper, we apply and evaluate a modified Gaussian-test-based hierarchical clustering method for high-resolution satellite images. The purpose is to obtain homogeneous clusters within each hierarchy level which later allow the classification and annotation of image data ranging from single scenes up to large satellite data archives. After cutting a given image into small patches and feature extraction from each patch, k -means are used to split sets of extracted image feature vectors to create a hierarchical structure. As image feature vectors usually fall into a high-dimensional feature space, we test different distance metrics, to tackle the “curse of dimensionality” problem. By using three different synthetic aperture radar (SAR) and optical image datasets, Gabor texture and Bag-of-Words (BoW) features are extracted, and the clustering results are analyzed via visual and quantitative evaluations. We also compared our approach with other classic unsupervised clustering methods. The most important contributions of this paper are the discussion and evaluation of cluster homogeneity by comparing various datasets, feature descriptors, evaluation measures, and clustering methods, as well as the analysis of the clustering performances under various distance metrics. The results show that the Gaussian-test-based hierarchical patch clustering method is able to obtain homogeneous clusters, while Gabor texture features perform better than the BoW features. In addition, it turns out that a distance parameter ranging from 1.2 to 2 performs best. Also indicated by [1], our modified G-means algorithm is faster than the original algorithm

Exploring high Resolution Satellite Image Collections Using their High-Level Features

Large volume of detailed features of land covers, provided by High-Resolution Earth Observation (EO) images, has attracted the interests to assess the discovery of these features by Content-Based Image Retrieval systems. In this paper, we perform Latent Dirichlet Allocation (LDA) on the Bag-of-Words (BoW) representation of collections of EO images to discover their high-level features, so-called topics. To assess the discovered topics, the images are represented based on the occurrence of different topics, we name it Bag-of-Topics (BoT). Then, the BoT model is compared to the BoW model of images based on the given human-annotations of the data. In our experiments, we compare the classification accuracy resulted by BoT and BoW representations of two different EO datasets, a Synthetic Aperture Radar (SAR) dataset and a multi-spectral satellite dataset. Moreover, we provide isualizations of feature space for better perceiving the changes in the discovered information by BoT and BoW models. Experimental results demonstrate that the dimensionality of the data can be reduced by BoT representation of images; while it either causes no significant reduction in the classification accuracy or even increase the accuracy by sufficient number of topics

On Position and Attitude Estimation for Remote Sensing with Bistatic SAR

Non