Number of found documents: 7
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Automation of metallographic sample cleaning process
Čermák, Jan; Ambrož, Ondřej; Jozefovič, Patrik; Mikmeková, Šárka
2022 - English
Specimen cleaning and drying are critical processes following any metallographic preparation steps. The paper focuses on automation by reason of absence of the process repeatability during manual sample handling. An etchant or electrolyte results in inhomogeneous surface quality because the solution runs off the specimen surface during its removal from the beaker. High-quality specimen cleaning is absolutely crucial for the acquisition of the specimen suitable for characterization by a scanning electron microscope operated at very low landing energies of the primary electrons (SLEEM). The SLEEM technique is a powerful tool for the characterization of advanced steels, as described by many scientific papers. The SLEEM requires the specimen absolutely free of water and any organic residues on the surface. This work presents a novel unique apparatus enabling automatic specimen cleaning and drying after the etching or electropolishing processes. Automation reduces the influence of dependent variables that would be introduced into the process by the metallographer. These variables include cleaning time, kinematics, and motion dynamics, but the process can also be affected by variables that are not obvious. Performed experiments clearly demonstrate our in-house designed apparatus as a useful tool improving efficiency and consistency of the sample cleaning process. The high quality of the specimen surface is verified using a light optical microscope, an electron scanning microscope, and above mentioned SLEEM technique. Keywords: metallography; sample cleaning; process automation; repeatability Fulltext is available at external website.
Automation of metallographic sample cleaning process

Specimen cleaning and drying are critical processes following any metallographic preparation steps. The paper focuses on automation by reason of absence of the process repeatability during manual ...

Čermák, Jan; Ambrož, Ondřej; Jozefovič, Patrik; Mikmeková, Šárka
Ústav přístrojové techniky, 2022

Correction of gradient pulse shape distortions in radial MRI
Vitouš, Jiří
2022 - English
This paper focuses on the optimization of gradient-pulse shapes in MRI measurement. The main topic investigated in this paper is optimization of slice-selective gradient, where imperfections may produce phase distortion in the resulting image and also signal loss in the acquired signal. A method for correction is proposed based on the Nelder-Mead algorithm followed by coordinate ascent search in the neighborhood of the found solution. The adjustment is evaluated using a simple Fast low angle shot (FLASH) sequence with radial readout. The results show a significant improvement in the Free induction decay (FID) signal magnitude, echo stability, and an improvement in the homogeneity of image phase. Keywords: MRI; gradient; Nelder–Mead; slice; adjustment Fulltext is available at external website.
Correction of gradient pulse shape distortions in radial MRI

This paper focuses on the optimization of gradient-pulse shapes in MRI measurement. The main topic investigated in this paper is optimization of slice-selective gradient, where imperfections may ...

Vitouš, Jiří
Ústav přístrojové techniky, 2022

Unfolded Low-rank + Sparse Reconstruction for MRI
Mokrý, O.; Vitouš, Jiří
2022 - English
We apply the methodology of deep unfolding on the problem of reconstruction of DCE-MRI data. The problem is formulated as a convex optimization problem, solvable via the primal-dual splitting algorithm. The unfolding allows for optimal hyperparameter selection for the model. We examine two approaches - with the parameters shared across the layers/iterations, and an adaptive version where the parameters can differ. The results demonstrate that the more complex model can better adapt to the data. Keywords: DCE-MRI; proximal splitting algorithms; deep unfolding; L+S model Fulltext is available at external website.
Unfolded Low-rank + Sparse Reconstruction for MRI

We apply the methodology of deep unfolding on the problem of reconstruction of DCE-MRI data. The problem is formulated as a convex optimization problem, solvable via the primal-dual splitting ...

Mokrý, O.; Vitouš, Jiří
Ústav přístrojové techniky, 2022

Effect Of Al2O3 Barrier On The Field Emission Properties Of Tungsten Single-Tip Field Emitters
Burda, Daniel; Knápek, Alexandr
2022 - English
This research aims to obtain a more in-depth understanding of the field emission properties of tungsten single-tip field emitters (STFEs) coated with a several tens of nanometer thin barrier of Al2O3. The introduction of an additional barrier into the metal-vacuum interface system of the emitter can be beneficial to improve its performance. The tungsten emitters were prepared using a two-step electrochemical drop-off etching technique. Thin oxide barrier coatings were prepared by using low-temperature atomic layer deposition (ALD), a chemical vapor deposition technique. Field emission was studied in an internally developed field emission microscope (FEM) working in UHV vacuum (< 1·10−7 Pa), and the experimental field emission data were analyzed by the so-called Murphy-Good plotsThe value of the local work function of the grown oxide layer were investigated using Ultra-violet photoelectron spectroscopy (UPS). Keywords: Cold field emission; single-tip field emitters; tungsten tip; aluminum oxide; dielectric coatings; Murphy-Good plot Fulltext is available at external website.
Effect Of Al2O3 Barrier On The Field Emission Properties Of Tungsten Single-Tip Field Emitters

This research aims to obtain a more in-depth understanding of the field emission properties of tungsten single-tip field emitters (STFEs) coated with a several tens of nanometer thin barrier of Al2O3. ...

Burda, Daniel; Knápek, Alexandr
Ústav přístrojové techniky, 2022

Electron beam welding of AlCoCrFeNi2.1 eutectic high-entropy alloy
Rončák, Ján; Adam, O.; Müller, P.; Zobač, Martin
2022 - English
Eutectic high-entropy alloys have become a significantly studied type of material due to their combination of strength and ductility. However, previous research has focused primarily on manufacture, solidification behaviour and mechanical properties. Only a small part of the research has been devoted to welding. This paper is focused on evaluating the weldability of eutectic high-entropy alloy AlCoCrFeNi2.1 in the as-cast state without further heat treatment. The electron beam welding process was performed twice at the same parameters, except for the beam current. Properties such as the depth of the remelted layer, the formation of the heat-affected zone, and the presence of undesirable defects in the welded joints were observed using light and electron microscopy. At the same time, material properties in the form of microstructural stability, chemical composition, and hardness of the welded joints were evaluated. Keywords: AlCoCrFeNi2.1; electron beam welding; eutectic high-entropy alloys; microstructure Fulltext is available at external website.
Electron beam welding of AlCoCrFeNi2.1 eutectic high-entropy alloy

Eutectic high-entropy alloys have become a significantly studied type of material due to their combination of strength and ductility. However, previous research has focused primarily on manufacture, ...

Rončák, Ján; Adam, O.; Müller, P.; Zobač, Martin
Ústav přístrojové techniky, 2022

Deep learning for magnetic resonance spectroscopy quantification: A time frequency analysis approach
Shamaei, Amirmohammad
2020 - English
Magnetic resonance spectroscopy (MRS) is a technique capable of detecting chemical compounds from localized volumes in living tissues. Quantification of MRS signals is required for obtaining the metabolite concentrations of the tissue under investigation. However, reliable quantification of MRS is difficult. Recently deep learning (DL) has been used for metabolite quantification of MRS signals in the frequency domain. In another study, it was shown that DL in combination with time-frequency analysis could be used for artifact detection in MRS. In this study, we verify the hypothesis that DL in combination with time-frequency analysis can also be used for metabolite quantification and yields results more robust than DL trained with MR signals in the frequency domain. We used the complex matrix of absolute wavelet coefficients (WC) for the time-frequency representation of the signal, and convolutional neural network (CNN) implementation for DL. The comparison with DL used for quantification of data in the frequency domain is presented. Keywords: magnetic resonance spectroscop; quantification; deep learning; machine learning Fulltext is available at external website.
Deep learning for magnetic resonance spectroscopy quantification: A time frequency analysis approach

Magnetic resonance spectroscopy (MRS) is a technique capable of detecting chemical compounds from localized volumes in living tissues. Quantification of MRS signals is required for obtaining the ...

Shamaei, Amirmohammad
Ústav přístrojové techniky, 2020

Single particle analysis of size-segregated aerosol in Prague city center
Marvanová, S.; Skoupý, Radim; Kulich, P.; Bendl, J.; Hovorka, J.; Machala, M.
2016 - English
Particulate matter (PM) is omnipresent pollutant in the ambient air known to cause cardiovascular and respiratory diseases (WHO 2004). Recently, outdoor air pollution and particulate matter in outdoor air pollution were classified as carcinogenic to humans, Group 1 (IARC 2015). Especially, ambient PM of aerodynamic diameter < 100 nm, ultrafine particles, appears to be of great importance due to its high specific surface area and high number concentration (Hughes et al. 1998). Ultrafine particles also easily enter and are being transferred in organisms, and interact with cells and subcellular components (Oberdorster et al. 2005). As the evidence of ultrafine PM significance increased, size-fractionated PMs sampled by various cascade impactors have been employed into the toxicological studies on cell cultures or isolated cells, using the organic extracts of size-fractionated PMs (Topinka et al. 2013, Topinka et al. 2015) or directly the size-fractionated particles (Becker et al. 2003, Ramgolam et al. 2009, Reibman et al. 2002, Loxham et al. 2013, Jalava et al. 2006, Thomson et al. 2015, Jalava et al. 2015). The aim of this study was to evaluate shape and composition of size-segregated aerosol particles, sampled by high volume cascade impactor, using electron microscopy and energy dispersive X-ray spectroscopy (EDX). Keywords: urban atmospheric aerosol; size-fractionated; electron microscopy; energy dispersive X-ray spectroscopy Fulltext is available at external website.
Single particle analysis of size-segregated aerosol in Prague city center

Particulate matter (PM) is omnipresent pollutant in the ambient air known to cause cardiovascular and respiratory diseases (WHO 2004). Recently, outdoor air pollution and particulate matter in outdoor ...

Marvanová, S.; Skoupý, Radim; Kulich, P.; Bendl, J.; Hovorka, J.; Machala, M.
Ústav přístrojové techniky, 2016

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