Water clusters on graphite: Methodology for quantum chemical A priori prediction of reaction rate constants

S. Xu, S. Irle*, D. G. Musaev, Ming-Chang Lin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

47 Scopus citations


The properties, interactions, and reactions of cyclic water clusters (H 2O) n=1-5 on model systems for a graphite surface have been studied using pure B3LYP, dispersion-augmented density functional tight binding (DFTBD), and integrated ONIOM(B3LYP:DFTB-D) methods. Coronene C 24H 12 as well as polycircumcoronenes C 96H 24 and C 216H 36 in monolayer, bilayer, and trilayer arrangements were used as model systems to simulate ABA bulk graphite. Structures, binding energies, and vibrational frequencies of water clusters on mono- and bilayer graphite models have been calculated, and structural changes and frequency shifts due to the water cluster-graphite interactions are discussed. ONIOM(B3LYP:DFTB-D) with coronene and water in the high level and C 90H 24 in the low level mimics the effect of extended graphite π-conjugation on the water-graphite interaction very reasonably and suggests that water clusters only weakly interact with graphite surfaces, as suggested by the fact that water is an excellent graphite lubricant. We use the ONIOM(B3LYP:DFTB-D) method to predict rate constants for model pathways of water dissociative adsorption on graphite. Quantum chemical molecular dynamics (QM/MD) simulations of water clusters and water addition products on the C 96H 24 graphite model are presented using the DFTB-D method. A three-stage strategy is devised for a priori investigations of high temperature corrosion processes of graphite surfaces due to interaction with water molecules and fragments.

Original languageEnglish
Pages (from-to)9563-9572
Number of pages10
JournalJournal of Physical Chemistry A
Issue number42
StatePublished - 27 Oct 2005

Fingerprint Dive into the research topics of 'Water clusters on graphite: Methodology for quantum chemical A priori prediction of reaction rate constants'. Together they form a unique fingerprint.

Cite this