For obtaining microscopic structural information in binary mixtures, often partial pair correlation functions are used. In the present study, a general approach is presented for obtaining the neighbourhood structural information for binary mixtures in terms of nth nearest neighbour distribution (NND) functions (for $n = 1, 2, 3,\ldots$). These functions are derived from the partial pair correlation functions in a hierarchical manner, based on the approach adopted earlier by us for single component fluids. Comparison of the results with MD simulation for Lennard-Jones binary mixtures is also presented. NND functions show reasonable matching for smaller n values particularly at higher density. The average 𝑛th nearest neighbour distance shows interesting feature.
Volume 134, 2022
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