相关论文: Morphological Analysis of Semiconductor Microstruc…
We show that scanning electron microscopy with polarization analysis (SEMPA) that is sensitive to both in-plane magnetization components can be used to image the out-of-plane magnetized multi-domain state in multilayered chiral spin…
This paper proposes a novel algorithm for the problem of structural image segmentation through an interactive model-based approach. Interaction is expressed in the model creation, which is done according to user traces drawn over a given…
Using electron beam manipulation, we enable deterministic motion of individual Si atoms in graphene along predefined trajectories. Structural evolution during the dopant motion was explored, providing information on changes of the Si atom…
The present paper develops a general methodology for the morphological segmentation of hyperspectral images, i.e., with an important number of channels. This approach, based on watershed, is composed of a spectral classification to obtain…
A near-field scanning optical microscope is used to locally induce photocurrent in a graphene transistor with high spatial resolution. By analyzing the spatially resolved photo-response, we find that in the n-type conduction regime a p-n-p…
The routine and unique determination of minor phases in microstructures is critical to materials science. In metallurgy alone, applications include alloy and process development and the understanding of degradation in service. We develop a…
Ion extraction from DECRIS-PM source is simulated by using initial distributions of ions at the extraction aperture obtained with NAM-ECRIS code. Three-dimensional calculations of plasma emissive surface are done and ions are traced in the…
In this paper we show that 1-electron properties such as Compton profiles and structure factors of crystals can be asymptotically retrieved through cluster-based calculations, followed by an appropriate partition of the 1-electron reduced…
Electron wavefunctions in twisted bilayer graphene may have a strong single layer character or be intrinsically delocalized between layers, with their nature often determined by how energetically close they are to the Dirac point. In this…
Graph embeddings have emerged as a powerful tool for representing complex network structures in a low-dimensional space, enabling the use of efficient methods that employ the metric structure in the embedding space as a proxy for the…
Understanding the evolution of dislocation structures during plastic deformation is critical for predicting the mechanical performance of metallic materials. In this work, we applied in situ scanning electron microscopy/electron backscatter…
In this paper we develop the theory for 2D-to-2D tunneling spectroscopy aided by magnetic or quantum-order excitations, and apply it to the description of van-der-Waals heterostructures of graphene/ultrathin $\alpha-{\rm RuCl}_3$. We study…
A common shortcoming of vibration-based damage localization techniques is that localized damages, i.e. small cracks, have a limited influence on the spectral characteristics of a structure. In contrast, even the smallest of defects, under…
Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in…
The quantitative knowledge of heavy nuclei's partonic structure is currently limited to rather large values of momentum fraction $x$ -- robust experimental constraints below $x \sim 10^{-2}$ at low resolution scale $Q^2$ are particularly…
Photoelectron diffraction (PED) is a powerful spectroscopic technique that combines elemental resolution with a high sensitivity to the local atomic arrangement at crystal surfaces, thus providing unique fingerprints of selected atomic…
The existence of macroscopic shell structure of submicron metal clusters is known for several decades. Since the most studies provide theoretical analysis for clusters of spherical shape, the electron density inhomogeneities caused by shell…
This work addresses a modification of the random geometric graph (RGG) model by considering a set of points uniformly and independently distributed on the surface of a $(d-1)$-sphere with radius $r$ in a $d-$dimensional Euclidean space,…
Graph convolutional networks (GCNs) aim at extending deep learning to arbitrary irregular domains, namely graphs. Their success is highly dependent on how the topology of input graphs is defined and most of the existing GCN architectures…
The Interferometric Bidimensional Spectrometer (IBIS) installed at the Dunn Solar Telescope of the NSO/SP is used to investigate the morphology and dynamics of the lower chromosphere and the virtually non-magnetic fluctosphere below. The…