A method for structure prediction of metal-ligand interfaces of hybrid nanoparticles
Malola, S., Nieminen, P., Pihlajamäki, A., Hämäläinen, J., Kärkkäinen, T., & Häkkinen, H. (2019). A method for structure prediction of metal-ligand interfaces of hybrid nanoparticles. Nature Communications, 10, Article 3973. https://doi.org/10.1038/s41467-019-12031-w
Published inNature Communications
© The Authors, 2019
Hybrid metal nanoparticles, consisting of a nano-crystalline metal core and a protecting shell of organic ligand molecules, have applications in diverse areas such as biolabeling, catalysis, nanomedicine, and solar energy. Despite a rapidly growing database of experimentally determined atom-precise nanoparticle structures and their properties, there has been no successful, systematic way to predict the atomistic structure of the metal-ligand interface. Here, we devise and validate a general method to predict the structure of the metal-ligand interface of ligand-stabilized gold and silver nanoparticles, based on information about local chemical environments of atoms in experimental data. In addition to predicting realistic interface structures, our method is useful for investigations on the steric effects at the metal-ligand interface, as well as for predicting isomers and intermediate structures induced by thermal dynamics or interactions with the environment. Our method is applicable to other hybrid nanomaterials once a suitable set of reference structures is available. ...
PublisherNature Publishing Group
ISSN Search the Publication Forum2041-1723
Publication in research information system
MetadataShow full item record
Related funder(s)Academy of Finland
Funding program(s)Research profiles, AoF; Academy Programme, AoF
Additional information about fundingThis work was supported by Academy of Finland through the AIPSE research program, grants 315549 (H.H.), 315550 (T.K.) and 311877 (T.K.), and through H.H.’s Academy Professorship. The computations were done at the Nanoscience Center (NSC) of University of Jyväskylä, at the CSC supercomputing center in Finland and as part of a PRACE project in the Barcelona Supercomputing Center.
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