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Spatial Separation of Molecular Conformers and Clusters
Published on: January 9, 2014
Molecular Dynamics Study of the Solution Structure, Clustering, and Diffusion of Four Aqueous Alkanolamines
Sergey M Melnikov1, Matthias Stein1
1Molecular Simulations and Design Group , Max-Planck-Institut für Dynamik komplexer technischer Systeme , Sandtorstrasse 1 , 39106 Magdeburg , Germany.
Abstract:
CO2 sequestration from anthropogenic resources is a challenge to the design of environmental processes at a large scale. Reversible chemical absorption by amine-based solvents is one of the most efficient methods of CO2 removal. Molecular simulation techniques are very useful tools to investigate CO2 binding by aqueous alkanolamine molecules for further technological application. In the present work, we have performed detailed atomistic molecular dynamics simulations of aqueous solutions of three prototype amines: monoethanolamine (MEA) as a standard, 3-aminopropanol (MPA), 2-methylaminoethanol (MMEA), and 4-diethylamino-2-butanol (DEAB) as potential novel CO2 absorptive solvents. Solvent densities, radial distribution functions, cluster size distributions, hydrogen-bonding statistics, and diffusion coefficients for a full range of mixture compositions have been obtained. The solvent densities and diffusion coefficients from simulations are in good agreement with those in the experiment. In aqueous solution, MEA, MPA, and MMEA molecules prefer to be fully solvated by water molecules, whereas DEAB molecules tend to self-aggregate. In a range from 30/70-50/50 (w/w) alkanolamine/water mixtures, they form a bicontinuous phase (both alkanolamine and water are organized in two mutually percolating clusters). Among the studied aqueous alkanolamine solutions, the diffusion coefficients decrease in the following order MEA > MPA = MMEA > DEAB. With an increase of water content, the diffusion coefficients increase for all studied alkanolamines. The presented results are a first step for process-scale simulation and provide important qualitative and quantitative information for the design and engineering of efficient new CO2 removal processes.
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