Graph Machine Based-QSAR Approach for Modeling Thermodynamic Properties of Amines: Application to CO2 Capture in Postcombustion

Graph Machine Based-QSAR Approach for Modeling Thermodynamic Properties of Amines: Application to CO2 Capture in Postcombustion — Amine scrubbing is usually considered as the most efficient technology for CO2 mitigation through postcombustion Carbon Capture and Storage (CCS). However, optimization of the amine structure to improve the solvent properties requires to sample a large number of possible candidates and hence to gather a large amount of experimental data. In this context, the use of QSAR (Quantitative Structure Activity Relationship) statistical modeling is a powerful tool as it performs a mapping of a set of input vectors (i.e. the characteristics or the properties of the molecules under consideration) to a set of output vectors (i.e. their targeted properties). In this work, we used a high throughput screening experimental device to measure CO2 solubility data on a set of 46 amine aqueous solutions. Absorption isotherms are represented using a thermodynamic model based on two thermodynamic constants, pKa* and pKc*, accounting for the main chemical reactions occurring in the liquid phase between amine and CO2. Then, we used a statistical approach named Graph Machines at the Oil & Gas Science and Technology – Rev. IFP Energies nouvelles, Vol. 68 (2013), No. 3, pp. 469-486 Copyright © 2013, IFP Energies nouvelles DOI: 10.2516/ogst/2012025 Discovery and Optimization of Catalysts and Adsorbents Using High Throughput Experimentation Découverte et optimisation de catalyseurs et d'adsorbants par expérimentations haut débit Do s s i e r ogst110152_PORCHERON 23/07/13 10:23 Page 469