First-Principles Prediction of Surface Wetting.
Journal
Langmuir : the ACS journal of surfaces and colloids
ISSN: 1520-5827
Titre abrégé: Langmuir
Pays: United States
ID NLM: 9882736
Informations de publication
Date de publication:
27 Oct 2020
27 Oct 2020
Historique:
pubmed:
26
9
2020
medline:
26
9
2020
entrez:
25
9
2020
Statut:
ppublish
Résumé
We have developed a method for predicting the solvation contribution to solid-liquid interfacial tension (IFT) based on density functional theory and the implicit solvent model COSMO-RS. Our method can be used to predict wetting behavior for a solid surface in contact with two liquids. We benchmarked our method against measurements of contact angle from water-in-oil on silica wafers and a range of self-assembled monolayers (SAMs) with different compositions, ranging from oil-wet to water-wet. We also compared our predictions to literature data for wetting of a polydimethylsilane surface. By explicitly including deprotonation for silica surfaces and carboxylic acid SAMs, very good agreement was obtained with experimental data for nearly all surfaces. Poor agreement was found for amine-terminated SAMs, which could be the result of both method and model insufficiencies and impurities known to be present for such surfaces. Solid-liquid IFT cannot be measured directly, making predictions such as from our method all the more important.
Identifiants
pubmed: 32975124
doi: 10.1021/acs.langmuir.0c01241
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM