Dipolar coupling of nanoparticle-molecule assemblies : an efficient approach for studying strong coupling
Fojt, J., Rossi, T. P., Antosiewicz, T. J., Kuisma, M., & Erhart, P. (2021). Dipolar coupling of nanoparticle-molecule assemblies : an efficient approach for studying strong coupling. Journal of Chemical Physics, 154(9), Article 094109. https://doi.org/10.1063/5.0037853
Published inJournal of Chemical Physics
© 2021 the Authors
Strong light–matter interactions facilitate not only emerging applications in quantum and non-linear optics but also modifications of properties of materials. In particular, the latter possibility has spurred the development of advanced theoretical techniques that can accurately capture both quantum optical and quantum chemical degrees of freedom. These methods are, however, computationally very demanding, which limits their application range. Here, we demonstrate that the optical spectra of nanoparticle-molecule assemblies, including strong coupling effects, can be predicted with good accuracy using a subsystem approach, in which the response functions of different units are coupled only at the dipolar level. We demonstrate this approach by comparison with previous time-dependent density functional theory calculations for fully coupled systems of Al nanoparticles and benzene molecules. While the present study only considers few-particle systems, the approach can be readily extended to much larger systems and to include explicit optical-cavity modes. ...
PublisherAmerican Institute of Physics
ISSN Search the Publication Forum0021-9606
Dataset(s) related to the publicationhttp://doi.org/10.5281/zenodo.4501057
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Postdoctoral Researcher, AoF
Additional information about fundinge gratefully acknowledge the Knut and Alice Wallenberg Foundation (Grant No. 2019.0140, J.F., P.E.), the Swedish Research Council (Grant No. 2015-04153, J.F., P.E.), the Academy of Finland (Grant Nos. 332429, T.P.R; 295602, M.K.), and the Polish National Science Center (Grant No. 2019/34/E/ST3/00359, T.J.A.). The computations were enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at NSC, C3SE, and PDC partially funded by the Swedish Research Council through Grant Agreement No. 2018-05973 as well as by the CSC—IT Center for Science, Finland, by the Aalto Science-IT project, Aalto University School of Science, and by the Interdisciplinary Center for Mathematical and Computational Modeling, University of Warsaw (Grant No. G55-6). ...
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