Efficient modeling of organic adsorbates on oxygen-intercalated graphene on Ir(111)

Jari Järvi*, Milica Todorović, Patrick Rinke

*Tämän työn vastaava kirjoittaja

Tutkimustuotos: LehtiartikkeliArticleScientificvertaisarvioitu

6 Sitaatiot (Scopus)
64 Lataukset (Pure)

Abstrakti

Organic charge transfer complexes (CTCs) can be grown as thin films on intercalated graphene (Gr). Deciphering their precise film morphologies requires global ab initio structure search, where configurational sampling is computationally intractable unless we reconsider the model for the complex substrate. In this study, we employ charged freestanding Gr to approximate an intercalated Gr/O/Ir(111) substrate, without altering the adsoption properties of deposited molecules. We compare different methods of charging Gr and select the most appropriate substitute model for Gr/O/Ir(111) that maintains the adsorption properties of fluorinated tetracyanoquinodimethane (F4TCNQ) and tetrathiafulvalene (TTF), prototypical electron acceptor/donor molecules in CTCs. Next, we apply our model in the Bayesian optimization structure search method and density-functional theory to identify the stable structures of F4TCNQ and TTF on supported Gr. We find that both molecules physisorb to Gr in various configurations. The narrow range of adsorption energies indicates that the molecules may diffuse easily on the surface and molecule-molecule interactions likely have a central role in film formation. Our study shows that complex intercalated substrates may be approximated with charged freestanding Gr, which can facilitate exhaustive structure search of CTCs.

AlkuperäiskieliEnglanti
Artikkeli195304
Sivut1-10
Sivumäärä10
JulkaisuPhysical Review B
Vuosikerta105
Numero19
DOI - pysyväislinkit
TilaJulkaistu - 15 toukok. 2022
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

The authors wish to acknowledge Dr. V. Havu for insightful discussions. M.T. and P.R. have received funding from the Academy of Finland via the Artificial Intelligence for Microscopic Structure Search (AIMSS) Project No. 316601 and the Flagship Programme: Finnish Center for Artificial Intelligence FCAI. J.J. has been funded by the Emil Aaltonen Foundation. Generous computational resources were provided by CSC – IT Center for Science, Finland, and the Aalto Science-IT project.

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  • -: Finnish Center for Artificial Intelligence

    Kaski, S. (Vastuullinen johtaja)

    01/01/201931/12/2022

    Projekti: Academy of Finland: Other research funding

  • Mikroskooppisen rakenteen määritys tekoälyn avulla

    Rinke, P. (Vastuullinen johtaja), Lehto, E.-K. (Projektin jäsen), Geurts, A. (Projektin jäsen), Paulamäki, H. (Projektin jäsen), Homm, H. (Projektin jäsen), Todorovic, M. (Projektin jäsen), Ghosh, K. (Projektin jäsen), Himanen, L. (Projektin jäsen), Kuchelmeister, M. (Projektin jäsen) & Li, J. (Projektin jäsen)

    01/01/201831/12/2021

    Projekti: Academy of Finland: Other research funding

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