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A computational probe into the physicochemical properties of cyclodextrin-based deep eutectic solvents for extraction processes

The use of deep eutectic solvents (DESs) as environmentally friendly alternatives to traditional volatile organic solvents has attracted significant attention in the industrial sector. In this study, molecular dynamics simulations were utilized to examine the physicochemical and structural character...

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Bibliographic Details
Published in:Carbohydrate polymer technologies and applications 2024-12, Vol.8, p.100596, Article 100596
Main Authors: Jahanbakhsh-Bonab, Parisa, Khoshnazar, Zahra, Sardroodi, Jaber Jahanbin, Heidaryan, Ehsan
Format: Article
Language:English
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Summary:The use of deep eutectic solvents (DESs) as environmentally friendly alternatives to traditional volatile organic solvents has attracted significant attention in the industrial sector. In this study, molecular dynamics simulations were utilized to examine the physicochemical and structural characteristics of novel DESs—specifically DES1, DES2, and DES3—comprising methyl-β-cyclodextrin (MBCD) mixed with formic acid (FA), propionic acid (PA), and acetic acid (AA), respectively, in a 1:3 molar ratio. Structural analysis, as revealed by the combined distribution function and radial distribution function, indicated that the dominant interactions within the DESs occur between the hydroxyl hydrogen of the acids and the hydroxyl oxygen of MBCD, as well as between the hydroxyl hydrogen of MBCD and the carbonyl oxygen of the acids. Furthermore, it was observed that MBCD forms more hydrogen bonds and non-bonded interactions with PA than with FA or AA. As a result, PA exhibits a lower self-diffusion coefficient compared to FA and AA. The findings also demonstrate that the influence of the acid type on the density and isothermal compressibility of the DESs follows the order: DES2 > DES1 > DES3 for density and DES3 > DES2 > DES1 for compressibility. Overall, this study provides valuable insights into the behavior of novel MBCD-based DESs, offering predictive insights for their potential applications in extraction processes.
ISSN:2666-8939
2666-8939
DOI:10.1016/j.carpta.2024.100596