Proposed Definition of Microchemical Inhomogeneity and Application To Characterize Some Selected Miscible/Immiscible Binary Metal Systems

Li, J. H.; Kong, Lingti; Liu, B. X.

doi:10.1021/jp047897x

Cited by 21 publications

(18 citation statements)

References 36 publications

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“…Metal-metal interactions are described by a model of the Finnis-Sinclair type, [13] a density-dependent potential derived from the tight-binding approximation, which can describe bonding of metal atoms in terms of the local electron density, and is suitable to calculate the properties of metals, including ruthenium. [14] Metal surfaces are conducting, thus highly polarizable, and their interactions with charged entities incorporate manybody effects that are expected to be non-negligible even for small clusters of metal atoms. A specific model of the metalionic liquid interactions was developed here based on quantum chemical calculations.…”

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confidence: 99%

Solvation and Stabilization of Metallic Nanoparticles in Ionic Liquids

2011

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Some room-temperature ionic liquids can hold stable suspensions of nanoparticles without additional surface-active agents [1] through mechanisms of solvation and stabilization that are not understood at present, particularly for metallic nanoparticles. These systems are relevant for applications in catalysis, lubrication, electrochemical devices, and chemical processes. We address this issue by studying the interactions and ordering of ionic liquids around metallic nanoparticles using molecular dynamics simulations, which is a suitable tool because the arrangement of the ions around a 2 nm particle is difficult to observe experimentally. The fundamental obstacle to modeling resides in the description of the interactions between metals and ionic fluids, a problem not only for nanometer-scale objects but for extended surfaces as well. In this work we devised an original strategy to represent accurately the molecular interactions and gain insight into the solvation and stabilization mechanisms of nanoparticles in ionic liquids.Experimental studies of metallic nanoparticles in ionic liquids provide different clues about the stabilization of the colloid. Some postulate an electric double layer (the Deryagin-Landau-Verwey-Overbeek model) in which a first solvation shell of anions surrounds the metal cluster, followed by a less ordered layer of cations, and so on.[2] Other studies present evidence of close interactions of the nanoparticles with the cations, through deuterium exchange on positively charged imidazolium rings [3] and through surface-enhanced Raman spectroscopy on gold nanoparticles in imidazolium liquids.[4] Correlations have been established between the size of metallic nanoparticles synthesized in situ with the anion volume.[5] Still other studies suggest that nanoparticles are solvated in nonpolar regions formed by aggregation of the hydrophobic alkyl side chains of the ions, as there is a relationship between the length scale of the structural heterogeneities of the ionic liquid [6] and the size of nanoparticles synthesized therein. [7] Measurements of the thickness of the electrostatic double layer of ionic liquids at metal surfaces have been performed [9] yielded an interfacial layer with one-ion thickness of 3.3 to 5 . This is consistent with the Debye length of the order of 1 estimated for an electrolyte with a concentration around 4 or 5 m, such as a pure ionic liquid, and constitutes an argument against DLVO-type stabilization. However, measurements on macroscopic flat surfaces may not be immediately transposed to nanoparticle suspensions.Suspensions of metallic nanoparticles in an ionic liquid are governed by three kinds of molecular interaction: ion-ion, metal-metal, and metal-ion, which are all nontrivial and each offers its own difficulties to a description. We adopted an atomistic description for both the nanoparticle and for the ionic liquid, providing a high level of detail regarding the interactions and conformations. We considered a ruthenium nanoparticle in [C 4 C 1 im][Ntf 2 ], 1-buty...

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Solvation and Stabilization of Metallic Nanoparticles in Ionic Liquids

2011

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“…According to initial definitions, p ii 5 (Z ii /Z i ) and p ij 5 (Z ij /Z i ) (j6 ¼i) 29 are the average probabilities of an i atom to have an atom of similar species and to have an atom of dissimilar species as its nearest neighbor, respectively, which can be calculated from CNs for a given composition. In this work, MCI parameter has been further extended to describe the CSROs of Ni-Zr-Ti ternary system with different compositions.…”

Section: Characterization Methods Of Local Atomic Configurationsmentioning

confidence: 99%

“…That is, it may generate three different parameters to describe the CSROs of a ternary alloy. Recently Li et al 29 proposed a parameter, namely microchemical inhomogeneity (MCI) parameter to describe the intrinsic atomic configurations, which quantitatively reflect the CSROs by using one generalized parameter for a given binary alloy. MCI parameters of four binary metal systems, i.e., the Ag-Ru, Ag-Co, Ni-Ru, and Ni-Hf systems, have been selected and investigated in the previous study.…”

Section: Introductionmentioning

confidence: 99%

“…MCI parameters of four binary metal systems, i.e., the Ag-Ru, Ag-Co, Ni-Ru, and Ni-Hf systems, have been selected and investigated in the previous study. 29 Governed by atomic configurations of a system, MCI parameter is evaluated from an interatomic potential of the system through MD simulations as the MD simulations can provide some detailed information concerning the atomic configurations by the proper calculation of the total or partial pair correlation functions.…”

Section: Introductionmentioning

confidence: 99%

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Favored composition region for metallic glass formation and atomic configurations in the ternary Ni–Zr–Ti system derived from n-body potential through molecular dynamics simulations

Zhao

Liu

2011

J. Mater. Res.

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An atomistic scheme is developed based on constructed n-body potential to investigate the glass-forming composition region and atomic configurations in Ni-Zr-Ti system. The glass-forming ranges derived from the n-body potentials through molecular dynamics simulations for the binary Ni-Zr, Ni-Ti, Zr-Ti, and ternary Ni-Zr-Ti systems turns out to be very compatible with theoretical studies and experimental observations. Moreover, the coordination numbers (CNs), microchemical inhomogeneity parameter, and Honeycutt and Anderson pair analysis are also computed to exam the local atomic configurations during crystal-to-amorphous phase transition. It is found that average total CNs of amorphous phases are significantly larger compared with those in solid solution counterparts, owing to the increased fractions of CNs from 13 to 16. A tendency in forming the chemical short-range orders also exists in binary and ternary metallic glasses in the Ni-Zr-Ti system and icosahedra-related atomic configurations play important role in forming those orders.

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“…Metal–metal interactions are described by a model of the Finnis–Sinclair type,13 a density‐dependent potential derived from the tight‐binding approximation, which can describe bonding of metal atoms in terms of the local electron density, and is suitable to calculate the properties of metals, including ruthenium 14…”

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confidence: 99%