Records |
Author |
Li, L.; Liao, Z.; Gauquelin, N.; Minh Duc Nguyen; Hueting, R.J.E.; Gravesteijn, D.J.; Lobato, I.; Houwman, E.P.; Lazar, S.; Verbeeck, J.; Koster, G.; Rijnders, G. |
Title |
Epitaxial stress-free growth of high crystallinity ferroelectric PbZr0.52Ti0.48O3 on GaN/AlGaN/Si(111) substrate |
Type |
A1 Journal article |
Year |
2018 |
Publication |
Advanced Materials Interfaces |
Abbreviated Journal |
Adv Mater Interfaces |
Volume |
5 |
Issue |
2 |
Pages |
1700921 |
Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT) |
Abstract |
<script type='text/javascript'>document.write(unpmarked('Due to its physical properties gallium-nitride (GaN) is gaining a lot of attention as an emerging semiconductor material in the field of high-power and high-frequency electronics applications. Therefore, the improvement in the performance and/or perhaps even extension in functionality of GaN based devices would be highly desirable. The integration of ferroelectric materials such as lead-zirconate-titanate (PbZrxTi1-xO3) with GaN has a strong potential to offer such an improvement. However, the large lattice mismatch between PZT and GaN makes the epitaxial growth of Pb(Zr1-xTix)O-3 on GaN a formidable challenge. This work discusses a novel strain relaxation mechanism observed when MgO is used as a buffer layer, with thicknesses down to a single unit cell, inducing epitaxial growth of high crystallinity Pb(Zr0.52Ti0.48)O-3 (PZT) thin films. The epitaxial PZT films exhibit good ferroelectric properties, showing great promise for future GaN device applications.')); |
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Wos |
000423173800005 |
Publication Date |
2017-11-27 |
Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2196-7350 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
4.279 |
Times cited |
15 |
Open Access |
Not_Open_Access |
Notes |
; L.L., Z.L.L., and N.G. contributed equally to this work. L.L. acknowledges financial support from Nano Next NL (Grant no. 7B 04). The authors acknowledge NXP for providing the GaN/AlGaN/Si (111) wafer. N.G. acknowledges funding from the Geconcentreerde Onderzoekacties (GOA) project “Solarpaint” of the University of Antwerp and J.V. acknowledges funding from the Research Foundation Flanders (FWO, Belgium) project 42/FA070100/6088 “nieuwe eigenschappen in complexe Oxides.” N.G. acknowledges the EUROTAPES project (FP7-NMP.2011.2.2-1 Grant no. 280432) which partly funded this study. ; |
Approved |
Most recent IF: 4.279 |
Call Number |
UA @ lucian @ c:irua:148427UA @ admin @ c:irua:148427 |
Serial |
4872 |
Permanent link to this record |
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Author |
van der Jeught, S.; Muyshondt, P.G.G.; Lobato, I. |
Title |
Optimized loss function in deep learning profilometry for improved prediction performance |
Type |
A1 Journal article |
Year |
2021 |
Publication |
JPhys Photonics |
Abbreviated Journal |
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Volume |
3 |
Issue |
2 |
Pages |
024014 |
Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT) |
Abstract |
Single-shot structured light profilometry (SLP) aims at reconstructing the 3D height map of an object from a single deformed fringe pattern and has long been the ultimate goal in fringe projection profilometry. Recently, deep learning was introduced into SLP setups to replace the task-specific algorithm of fringe demodulation with a dedicated neural network. Research on deep learning-based profilometry has made considerable progress in a short amount of time due to the rapid development of general neural network strategies and to the transferrable nature of deep learning techniques to a wide array of application fields. The selection of the employed loss function has received very little to no attention in the recently reported deep learning-based SLP setups. In this paper, we demonstrate the significant impact of loss function selection on height map prediction accuracy, we evaluate the performance of a range of commonly used loss functions and we propose a new mixed gradient loss function that yields a higher 3D surface reconstruction accuracy than any previously used loss functions. |
Address |
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Corporate Author |
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Thesis |
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Publisher |
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Place of Publication |
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Language |
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Wos |
000641030000001 |
Publication Date |
2021-03-18 |
Series Editor |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2515-7647 |
ISBN |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
Impact Factor |
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Times cited |
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Open Access |
OpenAccess |
Notes |
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Approved |
Most recent IF: NA |
Call Number |
UA @ admin @ c:irua:178171 |
Serial |
6797 |
Permanent link to this record |
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Author |
Zhang, Z.; Lobato, I.; Brown, H.; Jannis, D.; Verbeeck, J.; Van Aert, S.; Nellist, P. |
Title |
Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions |
Type |
Dataset |
Year |
2023 |
Publication |
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Abbreviated Journal |
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Volume |
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Issue |
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Pages |
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Keywords |
Dataset; Electron microscopy for materials research (EMAT) |
Abstract |
Inelastic excitation as exploited in Electron Energy Loss Spectroscopy (EELS) contains a rich source of information that is revealed in the scattering process. To accurately quantify core-loss EELS, it is common practice to fit the observed spectrum with scattering cross-sections calculated using experimental parameters and a Generalized Oscillator Strength (GOS) database [1]. The GOS is computed using Fermi’s Golden Rule and orbitals of bound and excited states. Previously, the GOS was based on Hartree-Fock solutions [2], but more recently Density Functional Theory (DFT) has been used [3]. In this work, we have chosen to use the Dirac equation to incorporate relativistic effects and have performed calculations using Flexible Atomic Code (FAC) [4]. This repository contains a tabulated GOS database based on Dirac solutions for computing double differential cross-sections under experimental conditions. We hope the Dirac-based GOS database can benefit the EELS community for both academic use and industry integration. Database Details: – Covers all elements (Z: 1-108) and all edges – Large energy range: 0.01 – 4000 eV – Large momentum range: 0.05 -50 Å-1 – Fine log sampling: 128 points for energy and 256 points for momentum – Data format: GOSH [3] Calculation Details: – Single atoms only; solid-state effects are not considered – Unoccupied states before continuum states of ionization are not considered; no fine structure – Plane Wave Born Approximation – Frozen Core Approximation is employed; electrostatic potential remains unchanged for orthogonal states when – core-shell electron is excited – Self-consistent Dirac–Fock–Slater iteration is used for Dirac calculations; Local Density Approximation is assumed for electron exchange interactions; continuum states are normalized against asymptotic form at large distances – Both large and small component contributions of Dirac solutions are included in GOS – Final state contributions are included until the contribution of the previous three states falls below 0.1%. A convergence log is provided for reference. Version 1.1 release note: – Update to be consistent with GOSH data format [3], all the edges are now within a single hdf5 file. A notable change in particular, the sampling in momentum is in 1/m, instead of previously in 1/Å. Great thanks to Gulio Guzzinati for his suggestions and sending conversion script. Version 1.2 release note: – Add “File Type / File version” information [1] Verbeeck, J., and S. Van Aert. Ultramicroscopy 101.2-4 (2004): 207-224. [2] Leapman, R. D., P. Rez, and D. F. Mayers. The Journal of Chemical Physics 72.2 (1980): 1232-1243. [3] Segger, L, Guzzinati, G, & Kohl, H. Zenodo (2023). doi:10.5281/zenodo.7645765 [4] Gu, M. F. Canadian Journal of Physics 86(5) (2008): 675-689. |
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Approved |
Most recent IF: NA |
Call Number |
UA @ admin @ c:irua:203392 |
Serial |
9042 |
Permanent link to this record |