A temperature-dependent potential model for mercury in the description of vapour-liquid equilibrium & adsorption in activated carbon. (6th April 2020)

• Record Type: Journal Article
• Authors: Liu, Xiu; Fan, Chunyan; Do, D.D.; Pareek, Vishnu; Yang, Peiyu
• Is Part Of: Chemical engineering science. Volume 215(2020)
• Publication Date: 2020-04-06
• Subjects: Mercury -- Liquid-vapor equilibrium -- Potential model -- Adsorption -- Monte Carlo Simulation; Chemical engineering -- Periodicals; Génie chimique -- Périodiques; Chemical engineering; Periodicals; Electronic journals; 660
• DOI: 10.1016/j.ces.2019.115453
• Languages: English
• ISSNs: 0009-2509

Abstract

Highlights: A new temperature-dependent potential model is developed for mercury. This model described the vapour-liquid equilibrium better than pre-existing models. Mercury adsorption within carbonaceous pores was studied with MC for the 1st time. Simulated adsorption data agree qualitatively well with experimental measurement. Abstract: A practical potential equation for mercury was developed, by incorporating the long-ranged interaction and multi-body effects into the temperature-dependent dispersion parameters, to describe the thermodynamic properties of the liquid-vapour equilibrium and adsorption in carbonaceous materials. The collision diameter (σ) decreases and the well depth of interaction energy (ε) increases with temperature, with the product σ 6 ε (a measure of attraction) decreasing with temperature. The critical temperature derived from this model, 1745 K, agrees well with the experimental value of 1751 K, and the wetting temperature of mercury on graphite was found to be 1600 K, supporting the fact that mercury does not wet carbon under ambient conditions. Furthermore, it was illustrated with mercury can fill ultrafine graphitic slit pores, whose widths less than 0.7 nm, under ambient temperatures, because of the enhancement of the solid-fluid potential and the strong intermolecular interactions, and the simulation results qualitatively agree well with experimental data.