Cheminformatics Modeling of Amine Solutions for Assessing their CO₂Absorption Properties

Abstract

As stricter regulations on CO emissions are adopted worldwide, identifying efficient chemical processes to capture and recycle CO is of critical importance for industry. The most common process known as amine scrubbing suffers from the lack of available amine solutions capable of capturing CO efficiently. Tertiary amines characterized by low heats of reaction are considered good candidates but their absorption properties can significantly differ from one analogue to another despite high structural similarity. Herein, after collecting and curating experimental data from the literature, we have built a modeling set of 41 amine structures with their absorption properties. Then we analyzed their chemical composition using molecular descriptors and non-supervised clustering. Furthermore, we developed a series of quantitative structure-property relationships (QSPR) to assess amines' CO absorption properties from their structural characteristics. These models afforded reasonable prediction performances (e. g., Q =0.63 for CO absorption amount) even though they are solely based on 2D chemical descriptors and individual machine learning techniques (random forest and neural network). Overall, we believe the chemical analysis and the series of QSPR models presented in this proof-of-concept study represent new knowledge and innovative tools that could be very useful for screening and prioritizing hypothetical amines to be synthesized and tested experimentally for their CO absorption properties.

Matermetallomics: Concept And Analytical Methodology

“…Different from Pt nanoparticle (Ptnano) doping, single Pt atom doping can reduce Pt atom usage on the one hand, and selectively catalyze the hydrogen oxidation reaction (HOR)/hydrogen evolution reaction (HER) over oxygen reduction reaction (ORR) on the other hand. The temperature-frequency behavior of the dielectric permittivity (9-300 K; 100 Hz-1 MHz, and at 100 GHz) of K0.984Li0.016TaO3, containing the natural ratio of the Li isotopes (7.56% of 6 Li and 92.44% of 7 Li, KLT-7) and only the 6 Li isotope (KLT-6), was studied. 25 The results revealed that the activation energy for 6 Li + relaxation appeared to be smaller and the relaxation time pre-exponent was larger than for the 7 Li + centers.…”

Materials genome: research progress, challenges and outlook

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Modeling of carbon dioxide solubility in ionic liquids based on group method of data handling

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