Literature DB >> 23802763

Graphitic carbon-water nonbonded interaction parameters.

Yanbin Wu1, N R Aluru.   

Abstract

In this study, we develop graphitic carbon-water nonbonded interaction parameters entirely from ab initio calculation data of interaction energies between graphene and a single water molecule. First, we employ the Møller-Plesset perturbation theory of the second order (MP2) method to compute the polycyclic aromatic hydrocarbon (PAH)-water interaction energies, with proper size of basis sets and energy component analysis to extrapolate to infinite-sized graphene limit. Then, we develop graphitic carbon-water interaction parameters based on the MP2 data from this work and the ab initio data available in the literature from other methods such as random-phase approximation (RPA), density functional theory-symmetry-adapted perturbation theory (DFT-SAPT), and coupled cluster treatment with single and double excitations and perturbative triples (CCSD(T)). The accuracy of the interaction parameters is evaluated by predicting water contact angle on graphite and carbon nanotube (CNT) radial breathing mode (RBM) frequency shift and comparing them with experimental data. The interaction parameters obtained from MP2 data predict the CNT RBM frequency shift that is in good agreement with experiments. The interaction parameters obtained from RPA and DFT-SAPT data predict the contact angles and the CNT RBM frequency shift that agree well with experiments. The interaction parameters obtained from CCSD(T) data underestimate the contact angles and overestimate the CNT RBM frequency shift probably due to the use of small basis sets in CCSD(T) calculations.

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Year:  2013        PMID: 23802763     DOI: 10.1021/jp402051t

Source DB:  PubMed          Journal:  J Phys Chem B        ISSN: 1520-5207            Impact factor:   2.991


  9 in total

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6.  Nonlinear electrohydrodynamic ion transport in graphene nanopores.

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8.  Molecular Dynamics Simulations Reveal that Water Diffusion between Graphene Oxide Layers is Slow.

Authors:  Ram Devanathan; Dylan Chase-Woods; Yongsoon Shin; David W Gotthold
Journal:  Sci Rep       Date:  2016-07-08       Impact factor: 4.379

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Journal:  Nat Commun       Date:  2020-03-24       Impact factor: 14.919

  9 in total

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