<div class="csl-bib-body">
<div class="csl-entry">Libisch, F. (2024, September 26). <i>Modeling strain and moiré effects in large-scale reconstructions</i> [Presentation]. Seminar Invitation, Fritz Haber Institute Berlin, Germany.</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/206492
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dc.description.abstract
Large-scale reconstructions, nanostructures, defects and moire patterns typically entail length scales of several nanometers. Their ab-initio modeling thus requires unit cells with a prohibitively large number of atoms. For example, the unit cell of magic-angle bilayer graphene, featuring superconducting many-body states, includes around 12 000 carbon atoms. Conversely, the resulting modulations in local electronic structure, strain or charge states critically affect surface properties. We combine machine learning [1] and numerical optimization techniques with small-scale DFT calculations to derive large-scale tight-binding parametrizations. I will review several approaches we used to describe the local density of states, strain patterns [2], quantum transport [3], phonons and excitons [4] in moire superstructures and defects. Our toolset is general and can be applied to a wide range of other materials, enabling accurate large-scale simulations of material properties in the presence of large-scale reconstructions.
[1] Machine learning sparse tight-binding parameters for defects, npj Computational Materials 8, 116 (2022)
[2] Quantifying Strain in Moiré Superlattice, Nano Letters 23, 11510 (2023)
[3] Stability of destructive quantum interference antiresonances in electron transport through graphene nanostructures, Carbon 214, 118358 (2023)
[4] Strain fingerprinting of exciton valley character A. Kumar et al., Nature Comm 15, 7546 (2024)
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dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.subject
Catalysis
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dc.subject
Moire systems
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dc.subject
Moire systems
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dc.subject
Strain
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dc.title
Modeling strain and moiré effects in large-scale reconstructions
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dc.type
Presentation
en
dc.type
Vortrag
de
dc.relation.grantno
COE 5
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dc.type.category
Presentation
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tuw.publication.invited
invited
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tuw.project.title
Cluster of Excellence "Materialien für Energieumwandlung und -speicherung (MECS)"
