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Other literature type . 2024
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Conference object . 2024
License: CC BY
Data sources: Datacite
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Conference object . 2024
License: CC BY
Data sources: Datacite
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In Silico Design of Deep Eutectic Solvents for Phytosterols Extraction from Vegetal Sources

Authors: Sergio de-la-Huerta-Sainz, María A. Escobedo-Monge, Alberto Gutiérrez, Sonia Martel , Laura Gómez, José Antonio Esteban – Ollo, Laura Montejo-Gil, María Conde-Rioll, Pedro A. Marcos, Alfredo Bol, Mert Atilhan, Santiago Aparicio;

In Silico Design of Deep Eutectic Solvents for Phytosterols Extraction from Vegetal Sources

Abstract

Phytosterols (PTS) are a large family of compounds found in plants with various applications in nutrition, medicine and pharmacy. Their extraction from vegetal sources often involves expensive equipment, intense conditions or harmful chemicals like Volatile Organic Compounds (VOCs). Natural Deep Eutectic Solvents (NADES) aremade from an Hydrogen Bond Donor compound (HBD) and an acceptor (HBA), and possess a lower melting point than their components. They are a promising alternative as solvent for extraction: renewable, non volatile, non toxic, reusable and tunable to the process needs. In this work we propose a computational workflow for designing NADES for PTSextraction, using the Density Functional Theory (DFT) for molecular optimization and COSMORS methodology for thermodynamical calculations, such as the NADES properties and solubility for all PTS tested. VOCs are subjected to the same treatment for comparative purposes.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green