Structure of aqueous NaOH solutions: insights from neural-network-based molecular dynamics simulations. Issue 1 (2nd November 2016)

• Record Type: Journal Article
• Authors: Hellström, Matti; Behler, Jörg
• Is Part Of: Physical chemistry chemical physics. Volume 19:Issue 1(2017)
• Page Start: 82
• Page End: 96
• Publication Date: 2016-11-02
• Subjects: Chemistry, Physical and theoretical -- Periodicals; 541.3
• DOI: 10.1039/c6cp06547c
• Languages: English
• ISSNs: 1463-9076

Abstract

Abstract : A reactive neural network potential is used to identify coordination polyhedra and interpolyhedron connectivity patterns of NaOH solutions. Abstract : Sodium hydroxide, NaOH, is one of the most widely-used chemical reagents, but the structural properties of its aqueous solutions have only sparingly been characterized. Here, we automatically classify the cation coordination polyhedra obtained from molecular dynamics simulations. We find that, for example, with increasing concentration, octahedral coordination geometries become less favored, while the opposite is true for the trigonal prism. At high concentrations, the coordination polyhedra frequently deviate considerably from "ideal" polyhedra, because of an increased extent of interligand hydrogen-bonding, in which hydrogen bonds between two ligands, either OH2 or OH −, around the same Na + are formed. In saturated solutions, with concentrations of about 19 mol L −1, ligands are frequently shared between multiple Na + ions as a result of the deficiency of solvent molecules. This results in more complex structural patterns involving certain "characteristic" polyhedron connectivities, such as octahedra sharing ligands with capped trigonal prisms, and tetrahedra sharing ligands with trigonal bipyramids. The simulations were performed using a density-functional-theory-based reactive high-dimensional neural network potential, that was extensively validated against available neutron and X-ray diffraction data from the literature.