cover image: Assessing Low-Cost Computational Methods against Structural Properties and Size Effects of Pt nanoparticles

Assessing Low-Cost Computational Methods against Structural Properties and Size Effects of Pt nanoparticles

21 Sep 2023

An evaluation of the performances of several known low-cost methods for the reproduction of structural features of differently sized Pt nanoparticles (NPs) is presented. The full density functional theory PBE-dDsC functional (within the planewave formalism) was employed to benchmark the semiempirical tight-binding DFTB and GFNn-xTB (n = 0, 1, 2) and the reactive force-field ReaxFF. Performances were evaluated by comparing several size-dependent features (such as relative stabilities, structural descriptors, and vibrational features) computed with the different methods. Various structures (ordered and amorphous) and sizes (from Pt13 to Pt561) were considered in the datasets. ReaxFF molecular dynamics (MD) was employed to achieve the amorphization of cuboctahedral Pt147, Pt309, and Pt561 geometries, which were subsequently optimized with both the low-cost methods and the DFT reference, within a multilevel modeling approach. The structures were further annealed with GFN0-xTB MD. While DFTB performs quite well over all the selected structures, GFN2- xTB and the cheaper GFN0-xTB show a general predilection for amorphous geometries. The performances of GFN2-xTB are found to worsen with the increasing size of the system, while ReaxFF and GFN0-xTB undergo the opposite trend. We suggest that the semiempirical DFTB (and within certain limitations GFN0-xTB and ReaxFF) could be suited for fast screening through amorphous big-sized Pt NPs.

Authors

Alberto Ricchebuono, Eleonora Vottero, Andrea Piovano, Elena Groppo, Pascal Raybaud, Céline Chizallet

Related Organizations

Bibliographic Reference
Alberto Ricchebuono, Eleonora Vottero, Andrea Piovano, Elena Groppo, Pascal Raybaud, et al.. Assessing Low-Cost Computational Methods against Structural Properties and Size Effects of Pt nanoparticles. Journal of Physical Chemistry C, 2023, 127 (37), pp.18454-18465. ⟨10.1021/acs.jpcc.3c02799⟩. ⟨hal-04289810⟩
DOI
https://doi.org/10.1021/acs.jpcc.3c02799
Funding
This work was performed using HPC resources from the supercomputers ENER440 of IFPEN, Fram of the Norwegian academic HPC infrastructure (for which we thank Prof. Stian Svelle and Prof. Silvia Bordiga), and OCCAM of the University of Torino.
HAL Collection
IFP Energies Nouvelles
HAL Identifier
4289810
Institution
['Università degli studi di Torino = University of Turin', 'Institut Laue-Langevin', 'IFP Energies nouvelles']
Published in
France

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