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Titel:

Machine Learned Charge Transfer Integrals for Multiscale Simulations in Organic Thin Films

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Rinderle, M.; Kaiser, W.; Mattoni, A.; Gagliardi, A.
Abstract:
Gaining insight into structure-property relations is a key factor for the development of organic electronics. We present a multiscale framework for charge carrier mobilities in organic thin films empowered by machine learned charge transfer integrals. The choice of the molecular representation is crucial for accurate and sensitive predictions. Using pentacene thin films, we investigate kernel based algorithms and systematically compare representations ranging from system-specific geometric to Co...     »
Zeitschriftentitel:
J. Phys. Chem. C, XXXX, XXX, XXX-XXX 2020-07
Jahr:
2020
Jahr / Monat:
2020-07
Quartal:
3. Quartal
Monat:
Jul
Seitenangaben Beitrag:
1-34
Sprache:
en
Volltext / DOI:
doi:10.1021/acs.jpcc.0c04355
WWW:
https://pubs.acs.org/doi/abs/10.1021/acs.jpcc.0c04355
Verlag / Institution:
American Chemical Society ACS
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