Monte Carlo and reverse Monte Carlo simulations on molten zinc chloride

Literature Information

Publication Date 2000-03-09
DOI 10.1039/A907592E
Impact Factor 3.676
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Abstract

Monte Carlo and reverse Monte Carlo simulations on molten ZnCl2 were performed on the basis of the total atom pair correlation functions, recently determined with X-ray diffraction experiments at T=623 and 873 K. A new pair-wise additive potential model is presented that is based on an intermediate-range oscillating function for the Zn–Zn interaction in combination with a modified Coulomb potential. This potential mimics the effect of induced anion polarization, which has been found as to be the reason for the highly directional interactions between the cations and anions in the melt. With this simple potential model, the experimentally determined total atom pair correlation functions and the total structure factor, the prepeak included, are well reproduced. The analysis of the configurations, generated with the Monte Carlo method, confirms the existence of a network structure with rings and chains of small and medium size consistent with corner connected [ZnCl4] units of high tetrahedricity. In contrast, the reverse Monte Carlo method generates more disordered structures and is obviously not able to give a correct description of the ion arrangement in molten ZnCl2.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
Self-citation Rate: 10.3%
Articles per Year: 3036

Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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