2018
DOI: 10.1140/epje/i2018-11646-3
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On the calculation of the potential of mean force between atomistic nanoparticles

Abstract: We study the potential of mean force (PMF) between atomistic silica and gold nanoparticles in the vacuum by using molecular dynamics simulations. Such an investigation is devised in order to fully characterize the effective interactions between atomistic nanoparticles, a crucial step to describe the PMF in high-density coarse-grained polymer nanocomposites. In our study, we first investigate the behavior of silica nanoparticles, considering cases corresponding to different particle sizes and assessing results … Show more

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Cited by 29 publications
(34 citation statements)
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“…On the other hand, the main advantage of SCFT in relation to FOMC is that it can directly calculate the free energy, enthalpy and entropy of mixing between the NP and the polymer matrix and the potential of mean force between two nanoparticles immersed in a host polymer matrix. 39,49,50 The calculations were performed by employing the SCFT in one dimension (radial distance or normal distance coordinates) by taking advantage of the symmetry of the nanoparticle/planar surface. This one-dimensional treatment is expected to perform fairly well at moderate to large grafting densities and molecular weights of grafted chains.…”
Section: Introductionmentioning
confidence: 99%
“…On the other hand, the main advantage of SCFT in relation to FOMC is that it can directly calculate the free energy, enthalpy and entropy of mixing between the NP and the polymer matrix and the potential of mean force between two nanoparticles immersed in a host polymer matrix. 39,49,50 The calculations were performed by employing the SCFT in one dimension (radial distance or normal distance coordinates) by taking advantage of the symmetry of the nanoparticle/planar surface. This one-dimensional treatment is expected to perform fairly well at moderate to large grafting densities and molecular weights of grafted chains.…”
Section: Introductionmentioning
confidence: 99%
“…For example, Monte Carlo simulations demonstrated that ligand-mediated short-range attractive interactions between monolayer-protected AuNPs can lead to aggregation despite long-range electrostatic energy barriers 29 . All-atom Molecular Dynamics (MD) emphasized that the aggregation energy profile between polyethylene coated gold NPs is driven by short-range attraction and characterized by a large attractive well 25 , while coarse grained model demonstrated the effect of surface chemistry and coverage on the aggregation of thiol coated AuNPs 28 . Taken together these studies confirmed that hydrophobic interactions are the driving force behind NP aggregation, in agreement with the DLVO framework.…”
Section: Introductionmentioning
confidence: 99%
“…When gold interacts with silicon we can take σ 11 = 0.293 nm for Au and σ 22 = 0.392 nm for Si [61] and find for h c = 0.245 nm.…”
Section: Roughness Contributionmentioning
confidence: 99%