Determination of the Dissociation Constants (pKa) of Eight Amines of Importance in Carbon Capture: Computational Chemistry Calculations, and Artificial Neural Network Models

Author:

Alluri Venkata Sai Priyatham Varma1,Nguyen William (Hoang Chi Hieu)1ORCID,Henni Amr1ORCID

Affiliation:

1. Clean Energy Technologies Research Institute (CETRi), Acid Gas Removal Laboratory (AGRL), Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada

Abstract

This work focuses on determining the dissociation constants (pKa) of eight amines, namely, 3-(Diethylamino) propylamine, 1,3-Diaminopentane, 3-Butoxypropylamine, 2-(Methylamino) ethanol, Bis(2-methoxyethyl) amine, α-Methylbenzylamine, 2-Aminoheptane, and 3-Amino-1-phenylbutane, within temperatures ranging from 293.15 K to 323.15 K. The thermodynamic properties of the protonated reactions were regressed from the pKa work. In addition, the protonated order of both 3-(Diethylamino) propylamine and 1,3-Diaminopentane were determined using computational chemistry methods owing to their unsymmetrical structures. In addition to the experimental methods, the dissociation constants at the standard temperature (298.15 K) were also estimated using group functional models (paper–pencil) and computational methods. The computational methods include COSMO-RS and computational chemistry calculations. An artificial neural network (ANN) method was employed to model the data by collecting and combining the experimental properties to estimate the missing pKa values. Although the ANN models can provide acceptable results, they depend on the availability of the data. Instead of using the experimental properties, they were generated using software such as Aspen Plus or CosmothermX. The simulated ANN model can also provide very good fits to the experimental constant values.

Funder

Natural Science and Engineering Council (NSERC), Canada

Publisher

MDPI AG

Subject

General Medicine

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