Specific heat capacity enhancement studied in silica doped potassium nitrate via molecular dynamics simulation.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
20 May 2019
Historique:
received: 21 02 2019
accepted: 09 05 2019
entrez: 22 5 2019
pubmed: 22 5 2019
medline: 22 5 2019
Statut: epublish

Résumé

Molten salts serve an important purpose for short term heat energy storage and as heat transfer fluids in solar power plants. Different experimental groups have shown that certain mixtures containing salts doped with small amounts of nanoparticles exhibit much greater specific heat capacities compared to the same base salts without nanoparticles. This effect is technically interesting and economically important. Thus far, however, it is not understood. Our aim is the theoretical investigation of the specific heat capacity in the aforementioned nanofluids on the molecular level using simulations. Here we present results for liquid potassium nitrate doped with silica nanoparticles. We discuss the observed increase of the specific heat in terms of the particle induced hydrodynamic reinforcement and liquid structure. The theoretical background of this discussion is a ω-space resolved phonon theory of liquids in conjunction with differential spectral densities, computed for the different systems with and without nanoparticles.

Identifiants

pubmed: 31110229
doi: 10.1038/s41598-019-44132-3
pii: 10.1038/s41598-019-44132-3
pmc: PMC6527606
doi:

Types de publication

Journal Article

Langues

eng

Pagination

7606

Subventions

Organisme : Deutsche Forschungsgemeinschaft (German Research Foundation)
ID : HE1545/18-1

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Auteurs

Sven Engelmann (S)

School of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal, D-42097, Germany. s.engelmann@uni-wuppertal.de.

Reinhard Hentschke (R)

School of Mathematics and Natural Sciences, University of Wuppertal, Wuppertal, D-42097, Germany. hentschk@uni-wuppertal.de.

Classifications MeSH