Quantum-mechanical assessment of the energetics of silver decahedron nanoparticles

0524119 - ÚFM 2021 RIV CH eng J - Článek v odborném periodiku
Polsterová, S. - Friák, Martin - Všianská, Monika - Šob, Mojmír
Quantum-mechanical assessment of the energetics of silver decahedron nanoparticles.
Nanomaterials. Roč. 10, č. 4 (2020), č. článku 767. E-ISSN 2079-4991
Grant CEP: GA MŠMT(CZ) LQ1601; GA ČR(CZ) GA16-24711S
Institucionální podpora: RVO:68081723
Klíčová slova: Ab initio calculations * Decahedron * Excess energy * Nanoparticles * Silver * Thermodynamics
Obor OECD: Thermodynamics
Impakt faktor: 5.076, rok: 2020
Způsob publikování: Open access
https://www.mdpi.com/2079-4991/10/4/767

We present a quantum-mechanical study of silver decahedral nanoclusters and nanoparticles containing from 1 to 181 atoms in their static atomic configurations corresponding to the minimum of the ab initio computed total energies. Our thermodynamic analysis compares T = 0 K excess energies (without any excitations) obtained from a phenomenological approach, which mostly uses bulk-related properties, with excess energies from ab initio calculations of actual nanoclusters/nanoparticles. The phenomenological thermodynamic modeling employs (i) the bulk reference energy, (ii) surface energies obtained for infinite planar (bulk-related) surfaces and (iii) the bulk atomic volume. We show that it can predict the excess energy (per atom) of nanoclusters/nanoparticles containing as few as 7 atoms with the error lower than 3%. The only information related to the nanoclusters/nanoparticles of interest, which enters the phenomenological modeling, is the number of atoms in the nanocluster/nanoparticle, the shape and the crystallographic orientation(s) of facets. The agreement between both approaches is conditioned by computing the bulk-related properties with the same computational parameters as in the case of the nanoclusters/nanoparticles but, importantly, the phenomenological approach is much less computationally demanding. Our work thus indicates that it is possible to substantially reduce computational demands when computing excess energies of nanoclusters and nanoparticles by ab initio methods.
Trvalý link: http://hdl.handle.net/11104/0309679