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Chen, B.; Gauquelin, N.; Jannis, D.; Cunha, D.M.; Halisdemir, U.; Piamonteze, C.; Lee, J.H.; Belhadi, J.; Eltes, F.; Abel, S.; Jovanovic, Z.; Spreitzer, M.; Fompeyrine, J.; Verbeeck, J.; Bibes, M.; Huijben, M.; Rijnders, G.; Koster, G. |
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Title |
Strain-engineered metal-to-insulator transition and orbital polarization in nickelate superlattices integrated on silicon |
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A1 Journal article |
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Year |
2020 |
Publication |
Advanced Materials |
Abbreviated Journal |
Adv Mater |
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Pages |
2004995 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Epitaxial growth of SrTiO3 (STO) on silicon greatly accelerates the monolithic integration of multifunctional oxides into the mainstream semiconductor electronics. However, oxide superlattices (SLs), the birthplace of many exciting discoveries, remain largely unexplored on silicon. In this work, LaNiO3/LaFeO3 SLs are synthesized on STO-buffered silicon (Si/STO) and STO single-crystal substrates, and their electronic properties are compared using dc transport and X-ray absorption spectroscopy. Both sets of SLs show a similar thickness-driven metal-to-insulator transition, albeit with resistivity and transition temperature modified by the different amounts of strain. In particular, the large tensile strain promotes a pronounced Ni 3dx2-y2 orbital polarization for the SL grown on Si/STO, comparable to that reported for LaNiO3 SL epitaxially strained to DyScO3 substrate. Those results illustrate the ability to integrate oxide SLs on silicon with structure and property approaching their counterparts grown on STO single crystal, and also open up new prospects of strain engineering in functional oxides based on the Si platform. |
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Wos |
000588146500001 |
Publication Date |
2020-11-11 |
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ISSN |
0935-9648 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
29.4 |
Times cited |
18 |
Open Access |
OpenAccess |
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Notes |
; This work is supported by the international M-ERA.NET project SIOX (project 4288) and H2020 project ULPEC (project 732642). M.S. acknowledges funding from Slovenian Research Agency (Grants No. J2-9237 and No. P2-0091). This work received support from the ERC CoG MINT (#615759) and from a PHC Van Gogh grant. M.B. thanks the French Academy of Science and the Royal Netherlands Academy of Arts and Sciences for supporting his stays in the Netherlands. This project has received funding as a transnational access project from the European Union's Horizon 2020 research and innovation programme under grant agreement No 823717 – ESTEEM3. N.G. and J.V. acknowledge GOA project “Solarpaint” of the University of Antwerp. ; esteem3TA; esteem3reported |
Approved |
Most recent IF: 29.4; 2020 IF: 19.791 |
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Call Number |
UA @ admin @ c:irua:173516 |
Serial |
6617 |
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Author |
Chen, B.; Gauquelin, N.; Green, R.J.; Lee, J.H.; Piamonteze, C.; Spreitzer, M.; Jannis, D.; Verbeeck, J.; Bibes, M.; Huijben, M.; Rijnders, G.; Koster, G. |
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Title |
Spatially controlled octahedral rotations and metal-insulator transitions in nickelate superlattices |
Type |
A1 Journal article |
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Year |
2021 |
Publication |
Nano Letters |
Abbreviated Journal |
Nano Lett |
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Volume |
21 |
Issue |
3 |
Pages |
1295-1302 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
The properties of correlated oxides can be manipulated by forming short-period superlattices since the layer thicknesses are comparable with the typical length scales of the involved correlations and interface effects. Herein, we studied the metal-insulator transitions (MITs) in tetragonal NdNiO3/SrTiO3 superlattices by controlling the NdNiO3 layer thickness, n in the unit cell, spanning the length scale of the interfacial octahedral coupling. Scanning transmission electron microscopy reveals a crossover from a modulated octahedral superstructure at n = 8 to a uniform nontilt pattern at n = 4, accompanied by a drastically weakened insulating ground state. Upon further reducing n the predominant dimensionality effect continuously raises the MIT temperature, while leaving the antiferromagnetic transition temperature unaltered down to n = 2. Remarkably, the MIT can be enhanced by imposing a sufficiently large strain even with strongly suppressed octahedral rotations. Our results demonstrate the relevance for the control of oxide functionalities at reduced dimensions. |
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000619638600014 |
Publication Date |
2021-01-20 |
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ISSN |
1530-6984 |
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Additional Links |
UA library record; WoS full record; WoS citing articles |
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Impact Factor |
12.712 |
Times cited |
19 |
Open Access |
OpenAccess |
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Notes |
This work is supported by the international M-ERA.NET project SIOX (project 4288). J.V. and N.G. acknowledge funding through the GOA project “Solarpaint” of the University of Antwerp. The microscope used in this work was partly funded by the Hercules Fund from the Flemish Government. D.J. acknowledges funding from FWO Project G093417N from the Flemish fund for scientific research. M.S. acknowledges funding from Slovenian Research Agency (Grants J2-9237 and P2-0091). R.J.G. acknowledges funding from the Natural Sciences and Engineering Research Council of Canada (NSERC). Part of the research described in this paper was performed at the Canadian Light Source, a national research facility of the University of Saskatchewan, which is supported by the Canada Foundation for Innovation (CFI), NSERC, the National Research Council (NRC), the Canadian Institutes of Health Research (CIHR), the Government of Saskatchewan, and the University of Saskatchewan. This work received support from the ERC CoG MINT (No. 615759) and from a PHC Van Gogh grant. M.B. thanks the French Academy of Science and the Royal Netherlands Academy of Arts and Sciences for supporting his stays in The Netherlands. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 823717 -ESTEEM3. |
Approved |
Most recent IF: 12.712 |
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Call Number |
UA @ admin @ c:irua:176753 |
Serial |
6736 |
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Author |
Birkholzer, Y.A.; Sotthewes, K.; Gauquelin, N.; Riekehr, L.; Jannis, D.; van der Minne, E.; Bu, Y.; Verbeeck, J.; Zandvliet, H.J.W.; Koster, G.; Rijnders, G. |
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Title |
High-strain-induced local modification of the electronic properties of VO₂ thin films |
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A1 Journal article |
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Year |
2022 |
Publication |
ACS applied electronic materials |
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Volume |
4 |
Issue |
12 |
Pages |
6020-6028 |
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Keywords |
A1 Journal article; Electron microscopy for materials research (EMAT) |
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Abstract |
Vanadium dioxide (VO2) is a popular candidate for electronic and optical switching applications due to its well-known semiconductor-metal transition. Its study is notoriously challenging due to the interplay of long- and short-range elastic distortions, as well as the symmetry change and the electronic structure changes. The inherent coupling of lattice and electronic degrees of freedom opens the avenue toward mechanical actuation of single domains. In this work, we show that we can manipulate and monitor the reversible semiconductor-to-metal transition of VO2 while applying a controlled amount of mechanical pressure by a nanosized metallic probe using an atomic force microscope. At a critical pressure, we can reversibly actuate the phase transition with a large modulation of the conductivity. Direct tunneling through the VO2-metal contact is observed as the main charge carrier injection mechanism before and after the phase transition of VO2. The tunneling barrier is formed by a very thin but persistently insulating surface layer of the VO2. The necessary pressure to induce the transition decreases with temperature. In addition, we measured the phase coexistence line in a hitherto unexplored regime. Our study provides valuable information on pressure-induced electronic modifications of the VO2 properties, as well as on nanoscale metal-oxide contacts, which can help in the future design of oxide electronics. |
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000890974900001 |
Publication Date |
2022-11-18 |
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ISSN |
2637-6113 |
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Additional Links |
UA library record; WoS full record |
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Impact Factor |
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Times cited |
2 |
Open Access |
OpenAccess |
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Notes |
This work received financial support from the project Green ICT (grant number 400.17.607) of the research program NWA, which is financed by the Dutch Research Council (NWO), Research Foundation Flanders (FWO grant number G0F1320N), and the European Union’s Horizon 2020 research and innovation program within a contract for Integrating Activities for Advanced Communities (grant number 823717 − ESTEEM3). The K2 camera was funded through the Research Foundation Flanders (FWO-Hercules grant number G0H4316N – “Direct electron detector for soft matter TEM”).; esteem3reported; esteem3jra |
Approved |
Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:192712 |
Serial |
7309 |
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Author |
Annys, A.; Jannis, D.; Verbeeck, J.; Annys, A.; Jannis, D.; Verbeeck, J. |
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Title |
Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy |
Type |
A1 Journal article |
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Year |
2023 |
Publication |
Scientific reports |
Abbreviated Journal |
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Volume |
13 |
Issue |
1 |
Pages |
13724 |
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Keywords |
A1 Journal article; Engineering sciences. Technology; Electron microscopy for materials research (EMAT) |
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Abstract |
Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping. |
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001052937600046 |
Publication Date |
2023-08-22 |
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ISSN |
2045-2322 |
ISBN |
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Additional Links |
UA library record; WoS full record |
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Impact Factor |
4.6 |
Times cited |
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Open Access |
OpenAccess |
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Notes |
A.A. would like to acknowledge the resources and services used in this work provided by the VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government. J.V. acknowledges the IMPRESS project. The IMPRESS project has received funding from the HORIZON EUROPE framework program for research and innovation under grant agreement n. 101094299. |
Approved |
Most recent IF: 4.6; 2023 IF: 4.259 |
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Call Number |
UA @ admin @ c:irua:198647 |
Serial |
8846 |
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Author |
Annys, A.; Jannis, D.; Verbeeck, J. |
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Title |
Core-loss EELS dataset and neural networks for element identification |
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Dataset |
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2023 |
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Dataset; Electron microscopy for materials research (EMAT) |
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We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification. The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at: Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323) |
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Most recent IF: NA |
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Call Number |
UA @ admin @ c:irua:203391 |
Serial |
9015 |
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