Ethanol is a hydrogen bonding liquid. When mixed in small concentrations with water or alkanes, it forms aggregate structures reminiscent of, respectively, the direct and inverse micellar aggregates found in emulsions, albeit at much smaller sizes. At higher concentrations, micro-heterogeneous mixing with segregated domains is found. We examine how different statistical methods, namely correlation function analysis, structure factor analysis and cluster distribution analysis, can describe efficiently these morphological changes in these mixtures. In particular, we explain how the neat alcohol pre-peak of the structure factor evolves into the domain pre-peak under mixing conditions, and how this evolution differs whether the co-solvent is water or alkane. This study clearly establishes the heuristic superiority of the correlation function/structure factor analysis to study the micro-heterogeneity, since cluster distribution analysis is insensitive to domain segregation. Correlation functions detect the domains, with a clear structure factor pre-peak signature, while the cluster techniques detect the cluster hierarchy within domains. The main conclusion is that, in micro-segregated mixtures, the domain structure is a more fundamental statistical entity than the underlying cluster structures. These findings could help better understand comparatively the radiation scattering experiments, which are sensitive to domains, versus the spectroscopy-NMR experiments, which are sensitive to clusters.

Hydrogen bonding liquids, typically water and alcohols, are known to form labile structures (network, chains, etc...), hence the lifetime of such structures is an important microscopic parameter, which can be...

The evolution of the micro-segregated structure of aqueous methanol mixtures, in the temperature range 300 K-120 K, is studied with computer simulations, from the static structural point of view. The structural heterogeneity of water is reinforced at lower temperatures, as witnessed by a pre-peak in the oxygen-oxygen structure factor. Water tends to form predominantly chain-like clusters at lower temperatures and smaller concentrations. Methanol domains have essentially the same chain-like cluster structure as the pure liquid at high concentrations and becomes monomeric at smaller ones. Concentration fluctuations decrease with temperature, leading to quasi-ideal Kirkwood-Buff integrals, despite the enhanced molecular interactions, which we interpret as the signature of non-interacting segregated water and methanol clusters. This study throws a new light on the nature of the micro-heterogeneous structure of this mixture: the domain segregation is essentially based on the appearance of linear water clusters, unlike other alcohol aqueous mixtures, such as with propanol or butanol, where the water domains are more bulky.

Some binary mixtures, such as specific alcohol-alkane mixtures, or even water-tbutanol, exhibit two humps "camel back" shaped KBI. This is in sharp contrast with usual KBI of binary mixtures having a single extremum. This extremum is interpreted as the region of maximum concentration fluctuations, and usually occurs in binary mixtures presenting appreciable micro-segregation, and corresponds to where the mixture exhibit a percolation of the two species domains. In this paper, it is shown that two extrema occur in binary mixtures when one species forms "meta-particle" aggregates, the latter which act as a meta-species, and have their own concentration fluctuations, hence their own KBI extremum. This "meta-extremum" occurs at low concentration of the aggregate-forming species (such as alcohol in alkane), and is independant of the other usual extremum observed at mid volume fraction occupancy. These systems are a good illustration of the concept of the duality between concentration fluctuations and micro-segregation.

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