Molecular interaction between asymmetric ligand-capped gold nanocrystals

Liu, Xuepeng; Lü, Peng; Zhai, Hua

doi:10.1063/1.5065476

Cited by 9 publications

(4 citation statements)

References 48 publications

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“…For dodecanethiol ( n = 12) ligands this formula gives F min ≈ −194.4 k B T , which is definitely a very strong cohesive energy. Subsequently, other studies − have reported consistent results. Extensions to other shapes, such as tetrahedra and cubes, and characterization of many-body effects , are also relevant, but extending the results in this study to these more general situations does not raise any new conceptual issues, so we will not discuss them any further.…”

Section: Introductionmentioning

confidence: 55%

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Upah,

Thomas,

Hallstrom

et al. 2023

J. Chem. Theory Comput.

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Thermodynamic stability assessment of nanocrystal systems requires precise free energy calculations. This study highlights the importance of meticulous control over various factors, including the thermostat, time step, potential cutoff, initial configuration, sampling method, and overall simulation duration. Free energy computations in dry (solvent-free) systems are on the order of several hundred k B T but can be obtained with consistent accuracy. However, calculation of internal energies becomes challenging, as they are typically much larger in magnitude than free energies and exhibit significant noise and reduced reliability. To address this limitation, we propose a new internal energy estimate that drastically reduces the noise. We also present formulas that enable the optimization of the parameters of the harmonic bias potential for optimal convergence. Finally, we discuss the implications of these findings for the computation of free energies in nanocrystal clusters and superlattices.

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Section: Introductionmentioning

confidence: 55%

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Upah,

Thomas,

Hallstrom

et al. 2023

J. Chem. Theory Comput.

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“…42 With the OTM, systems of nanocrystals with a coordination number of 6 or greater could be described well 42 for systems with smaller coordination numbers, the overlap cone model (OCM) was developed. 41 Several theoretical studies applied these models in MD simulations with united-atom approaches, where SH, CH 2 , and CH 3 groups were treated as united atoms, 41,43−47 revealing either strong 48 or little interdigitation 43,44,47 of the ligands. Furthermore, both Liu et al 46 and Liepold et al 47 found a significant correlation between the ligand coverage and the interparticle spacing of two alkanethiol-capped nanocrystals.…”

Section: Introductionmentioning

confidence: 99%

“…Several theoretical studies applied these models in MD simulations with united-atom approaches, where SH, CH 2 , and CH 3 groups were treated as united atoms, ,− revealing either strong or little interdigitation ,, of the ligands. Furthermore, both Liu et al and Liepold et al found a significant correlation between the ligand coverage and the interparticle spacing of two alkanethiol-capped nanocrystals.…”

Section: Introductionmentioning

confidence: 99%

Cross-Linked Gold Nanoparticle Assemblies: What Can We Learn from Single Flat Interfaces?

Schaefer,

Liu,

Meyer

et al. 2024

J. Phys. Chem. C

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Cross-linked gold nanoparticle (GNP) assemblies are valuable for a variety of applications, such as transducers for strain or gas sensors. To pave the way for understanding their sensing behavior on an atomistic scale, we ask whether their properties can be modeled by a single, flat, particle–particle interface. Employing reactive force field (ReaxFF) molecular dynamics simulations and a tight-binding density functional theory approach to coherent tunneling, we find that for alkane dithiolates, where most molecules will typically bridge between the gold surfaces, the interparticle distances, as well as the conductivity of the assembly, can be modeled to even quantitative accuracy with a single-interface modelif compared to sufficiently large GPNs for which the flat surface is a good approximation. For alkane monothiols, where each molecule is only attached on one side, the difficulty of estimating surface density and the resulting degree of interlacing results, in our case, in underestimating the interparticle distances by around 5 Å. The increase of these distances (and the decrease of conductivity) on going to longer alkane chains, however, is still well reproduced. We discuss shortcomings of ReaxFF, such as not being able to describe thiol physisorption and producing spurious reactions between dithiolates, as well as factors influencing the validity of a single, flat, particle–particle interface model. Our model reduces the system complexity significantly compared to simulating entire GNP assemblies, enabling further mechanistic investigations of the sensing properties of these systems with atomistic approaches and, potentially, screening of ligands for specific sensing applications.

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“…These effective interactions are computed from fully atomistic molecular simulations of nanoparticles. In this regard there have been a number of studies previously reported [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] that have computed effective inter-particle interactions. These studies looked at various aspects of interactions between nanoparticles including length of ligand chains, role of solvent, three-body interactions, etc.…”

Section: Introductionmentioning

confidence: 99%

Modeling of effective interactions between ligand coated nanoparticles through symmetry functions

Chintha,

Veesam,

Boattini

et al. 2022

Preprint

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Ligand coated nanoparticles are complex objects consisting of a metallic or semiconductor core with organic ligands grafted on their surface. These organic ligands provide stability to a nanoparticle suspension. In solutions, the effective interactions between such nanoparticles are mediated through a complex interplay of interactions between the nanoparticle cores, the surrounding ligands and the solvent molecules. While it is possible to compute these interactions using fully atomistic molecular simulations, such computations are too expensive for studying self-assembly of a large number of nanoparticles. The problem can be made tractable by removing the degrees of freedom associated with the ligand chains and solvent molecules and using the potentials of mean force (PMF) between nanoparticles. In general, the functional dependence of the PMFs on the inter-particle distance is unknown and can be quite complex. In this article, we present a method to model the two-body and three-body potentials of mean force between ligand coated nanoparticles through a linear combination of symmetry functions. The method is quite general and can be extended to model interactions between different types of macromolecules.

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Molecular interaction between asymmetric ligand-capped gold nanocrystals

Cited by 9 publications

References 48 publications

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

High-Precision Calculation of Nanoparticle (Nanocrystal) Potentials of Mean Force and Internal Energies

Cross-Linked Gold Nanoparticle Assemblies: What Can We Learn from Single Flat Interfaces?

Modeling of effective interactions between ligand coated nanoparticles through symmetry functions

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