Efficient Extraction of Ln(III) from Nitric Acid Feed using a Novel and Undiluted Hydrophobic Deep Eutectic Solvent

Hydrophobic deep eutectic solvents (HDESs) are regarded as the green and new generation solvents for the separation of metal ions and other valuables from their waste solutions. In this context, a strongly HDES based on trioctylphosphine oxide and decanoic acid is employed in its undiluted condition for the solvent extraction of Eu(III) (taken as Ln(III) representative) from a broad range of nitric acid solutions. The projected HDES is highly hydrophobic and less viscous in nature. Various solvent extraction parameters are tuned to realize the extractant behavior of the proposed HDES. Though the extraction shows a decline at high feed acidity, the system is efficient to extract Eu(III) from pH range to concentrated acid solution with a high % extraction. The involvement of two HDES in the metal–solvate species (metal–ligand complex) formation with fast extraction kinetics corroborates the suitability of the extractant for extracting Eu(III) from the acidic phase. The phase volume ratio is changed to affirm the best possible extraction factors at the expense of minimum volume of HDES. The stripping performance of Eu(III) from the loaded HDES phase is investigated using Milli‐Q water as the stripping solution, thereby establishing the sustainability of the system.

Authors

Institutions

Publication Details

Journal
European Journal of Inorganic Chemistry
Published
2025-05-20
DOI
https://doi.org/10.1002/ejic.202500052
Citations
1
Primary Topic
Ionic liquids properties and applications
Type
article
Field-Weighted Citation Impact
0.39
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Efficient Extraction of Ln(III) from Nitric Acid Feed using a Novel and Undiluted Hydrophobic Deep Eutectic Solvent

Alok Rout, N. Ramanathan
1 citations
European Journal of Inorganic Chemistry
Ionic liquids properties and applications
0.39
article

Efficient Extraction of Ln(III) from Nitric Acid Feed using a Novel and Undiluted Hydrophobic Deep Eutectic Solvent

Alok Rout, N. Ramanathan
article en
1 citations

Abstract

Hydrophobic deep eutectic solvents (HDESs) are regarded as the green and new generation solvents for the separation of metal ions and other valuables from their waste solutions. In this context, a strongly HDES based on trioctylphosphine oxide and decanoic acid is employed in its undiluted condition for the solvent extraction of Eu(III) (taken as Ln(III) representative) from a broad range of nitric acid solutions. The projected HDES is highly hydrophobic and less viscous in nature. Various solvent extraction parameters are tuned to realize the extractant behavior of the proposed HDES. Though the extraction shows a decline at high feed acidity, the system is efficient to extract Eu(III) from pH range to concentrated acid solution with a high % extraction. The involvement of two HDES in the metal–solvate species (metal–ligand complex) formation with fast extraction kinetics corroborates the suitability of the extractant for extracting Eu(III) from the acidic phase. The phase volume ratio is changed to affirm the best possible extraction factors at the expense of minimum volume of HDES. The stripping performance of Eu(III) from the loaded HDES phase is investigated using Milli‐Q water as the stripping solution, thereby establishing the sustainability of the system.

European Journal of Inorganic ChemistryVol. 28(15)
Homi Bhabha National Institute (IN), Indira Gandhi Centre for Atomic Research (IN)
Openalex Percentile: Top 45%
Ionic liquids properties and applications
0.39
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.