Application of the Consonance Solvent Concept for Accurate Prediction of Buckminster Solubility in 180 Net Solvents using COSMO-RS Approach

Piotr Cysewski

doi:10.3390/sym11060828

Abstract

The default COSMO-RS (Conductor like Screening Model for Real Solvents) approach is incapable of accurate computation of C60 solubility in net solvents. Additionally, there is no adequate selection of single or multiple reference solvent, which can be applied to the whole population of 180 solvents for improving prediction of mole fraction at saturated conditions. This failure cannot be addressed to inaccurate data of the Buckminster fusion, although they pose a challenge for experimental measurement due to intense sublimation of C60 at elevated temperatures and the possibility of solvates precipitation. However, taking advantage of the richness of experimental data of fullerene solubility, it is possible to identify the source of errors expressed in terms of fluidization affinity. Classification of solvents according to the value of this fluidization term allowed for formulation of a consonance solvents approach, which enables accurate prediction of C60 solubility using the single reference solvent method.

Highlights

Buckminster fullerene is a highly symmetric all carbon molecule, in which structure is represented by truncated icosahedron with a cage-like fused-rings made of twenty hexagons and twelve pentagons.The sixty carbon atoms placed at each vertex of each polygon are covalently bonded along each polygon edge
Low solubility of C60 in many organic solvents [7] stands for the major cost of the production from soot [8], since extraction by organic solvents is the first step for obtaining fullerenes-rich fractions further separated using HPLC [9]
The starting point of this project was the frustrating observation of extremely high deviations of values computed using the COSMO-RS approach compared to experimental solubility data of fullerene C60 dissolved in 180 net solvents

Summary

Introduction

Buckminster fullerene is a highly symmetric all carbon molecule, in which structure is represented by truncated icosahedron with a cage-like fused-rings made of twenty hexagons and twelve pentagons.The sixty carbon atoms placed at each vertex of each polygon are covalently bonded along each polygon edge. Fullerene C60 belongs to a broad class of Goldberg polyhedron-like carbon allotropes occurring in the form of spheres, ellipsoids or tubes. It was first generated in 1984 using a laser induced carbon vaporization in a supersonic helium beam [1]. Strong tendency of precipitation in the form of solvates [10,11,12,13,14,15,16,17] makes it difficult to preserve purity of the solid This is why modeling of C60 solubility attracted so much attention and resulted in a variety of theoretical approaches, among which the best predications come so far from non-linear modeling via machine learning [18]. Other approaches taking advantage of quantitative structure-property relationships (QSPR) [19,20,21], the multiple linear regression (MLR) [19,22], partial least square regression (PLS) [23], support vector machines (SVMs) [22]

Objectives

Methods

Results