Determination of the structural properties of the aqueous electrolyte LiCl6H 2 O at the supercooled state using the Reverse Monte Carlo (RMC) simulation

7th Maghreb Days of Material Sciences

Ziane, M.^1,3 ; Habchi, M.^2,3 ; Derouiche, A.^1 ; Mesli, S.M.^2,3 ; Benzouine, F.^1 ; Kotbi, M.^4

LPPPC, Physics Department, Sciences Faculty Ben Msik, P.O. 7955, Casablanca, Morocco^1

École Préparatoire en Sciences et Thecniques, BP 165RP, Bel Horizon, Tlemcen

13000, Algeria^2

ISP Group, NMSE Division, URMER, Abou Bekr Belkaid University of Tlemcen, Algeria^3

Department of Physics, LPT, Abou Bekr Belkaid University, BP 119, Tlemcen, Algeria^4

关键词: Aqueous electrolyte;    Aqueous electrolyte solutions;    Neutron scattering techniques;    Partial distributions;    Reverse Monte Carlo method;    Reverse monte carlo simulation;    Structural studies;    Temperature decrease;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/186/1/012010/pdf
DOI  :  10.1088/1757-899X/186/1/012010

来源: IOP

【 摘 要 】

A structural study of an aqueous electrolyte whose experimental results are available. It is a solution of A structural study of an aqueous electrolyte whose experimental results are available. It is a solution LiCl6H2O type at supercooled state (162K) contrasted with pure water at room temperature by means of Partial Distribution Functions (PDF) issue from neutron scattering technique. The aqueous electrolyte solution of the chloride lithium LiCl presents interesting properties which is studied by different methods at different concentration and thermodynamical states: This system possesses the property to become a glass through a metastable supercooled state when the temperature decreases. Based on these partial functions, the Reverse Monte Carlo method (RMC) computes radial correlation functions which allow exploring a number of structural features of the system. The purpose of the RMC is to produce a consistent configuration with the experimental data. They are usually the most important in the limit of systematic errors (of unknown distribution).