Recent Developments in Deep Eutectic Solvents Applications in Liquid Chromatography: 2019–2025 DOI Creative Commons
Derya Dilek Demir, Joanna Antos, František Švec

et al.

Journal of Separation Science, Journal Year: 2025, Volume and Issue: 48(5)

Published: May 1, 2025

ABSTRACT Deep eutectic solvents (DES) are used as mobile phase and stationary modifiers, or for the itself thin layer/liquid/supercritical chromatography. Their specific properties can improve separation selectivity, reduce peak tailing, shorten time. In terms of environmental impact, advantages DES based on their biodegradability, recyclability, stability in mechanical/chemical/thermal properties. The disadvantages related to higher viscosity degradation aqueous solutions. This review focuses works that have been published since 2019, year excellent comprehensive by Cai Qiu was printed. Selected parameters discussed should be considered when preferred over commonly phases due green chemistry trends, while taking into account limitations modern LC separations. also centres critical aspects applications field liquid supercritical fluid chromatographic

Language: Английский

Consensus Modeling for Predicting Chemical Binding to Transthyretin as the Winning Solution of the Tox24 Challenge DOI Creative Commons
Dmitriy M. Makarov, Alexander A. Ksenofontov, Yury A. Budkov

et al.

Chemical Research in Toxicology, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 19, 2025

The utilization of predictive methodologies for the assessment toxicological properties represents an alternative approach that facilitates identification safe compounds while concurrently reducing financial costs associated with process. objective Tox24 Challenge was to assess progress in computational methods predicting activity chemical binding transthyretin (TTR). In order fulfill requirements this task, data set, measured by Environmental Protection Agency, consisted 1512 substances diverse nature. This paper describes model won and steps taken its further improvement. Transformer convolutional neural network (CNN) achieved best performance as a standalone solution. Meanwhile, multitask built on graph CNN, trained using 11 additional acute systemic toxicity sets increased weighting TTR activity, showed comparable results blind test set. winning solution consensus consisting two catBoost models OEstate Mold2 descriptor sets, well transformer-based models. improvement involved adding fifth based learning CNN method, which led reduction RMSE set 20.3%. developed OCHEM web platform is available online at https://ochem.eu/article/162082.

Language: Английский

Citations

2
Efficient synthesis of isoamyl acetate in deep eutectic solvent utilizing in-situ aqueous phase immobilized lipase biocatalyst DOI
Yuyang Zhang, Qiujie Wang, Zhiyuan Lin

et al.

Food Bioscience, Journal Year: 2025, Volume and Issue: unknown, P. 105963 - 105963

Published: Jan. 1, 2025

Language: Английский

Citations

1
Machine Learning for Predicting and Optimizing Physicochemical Properties of Deep Eutectic Solvents: Review and Perspectives DOI
Francisco Javier López-Flores, César Ramírez‐Márquez, J. Betzabe González‐Campos

et al.

Industrial & Engineering Chemistry Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 19, 2024

This review explores the application of machine learning in predicting and optimizing key physicochemical properties deep eutectic solvents, including CO2 solubility, density, electrical conductivity, heat capacity, melting temperature, surface tension, viscosity. By leveraging learning, researchers aim to enhance understanding customization a critical step expanding their use across various industrial research domains. The integration represents significant advancement tailoring solvents for specific applications, marking progress toward development greener more efficient processes. As continues unlock full potential it is expected play an increasingly pivotal role revolutionizing sustainable chemistry driving innovations environmental technology.

Language: Английский

Citations

4
Improved Solubility Predictions in scCO2 Using Thermodynamics-Informed Machine Learning Models DOI
Dmitriy M. Makarov, Nikolai N. Kalikin, Yury A. Budkov

et al.

Journal of Chemical Information and Modeling, Journal Year: 2025, Volume and Issue: unknown

Published: April 15, 2025

Accurate solubility prediction in supercritical carbon dioxide (scCO2) is crucial for optimizing experimental design by eliminating unnecessary and costly trials at an early stage, thereby streamlining the workflow. A comprehensive database containing 31,975 records has been compiled, providing a foundation developing predictive models applicable to diverse class of chemical compounds, with particular focus on drug-like substances. In this study, we propose domain-aware machine learning approach that incorporates thermodynamic properties governing phase transitions predictions scCO2. Predictive were developed using CatBoost algorithm graph-based architecture employing directed message passing identify most effective approach. Furthermore, auxiliary solute, including melting point, critical parameters, enthalpy vaporization, Gibbs free energy solvation, predicted as part work. The findings underscore efficacy incorporating domain-specific features enhance accuracy scCO2 modeling. interpretation applicability domain assessment have confirmed qualitative selection employed descriptors, demonstrating their ability generalize unique compounds fall outside defined domain.

Language: Английский

Citations

0
ChemBERTa Embeddings and Ensemble Learning for Prediction of Density and Melting Point of Deep Eutectic Solvents with Hybrid Features DOI
Ting Wu, Peng Zhan, Weiqiu Chen

et al.

Computers & Chemical Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 109065 - 109065

Published: Feb. 1, 2025

Language: Английский

Citations

0
Investigation of CO2 Absorption and Physicochemical Properties of Deep Eutectic Solvents Based on Amine Hydrohalides and Alkanolamines DOI
Dmitriy M. Makarov, Yu. A. Fadeeva, Mikhail A. Krestianinov

et al.

Journal of Chemical & Engineering Data, Journal Year: 2025, Volume and Issue: unknown

Published: April 7, 2025

Language: Английский

Citations

0
The Physicochemical Properties and Plausible Implication of Deep Eutectic Solvents in Analytical Techniques DOI

Vahishta K. Katrak,

Ninad K Patel,

Sushma P. Ijardar

et al.

Critical Reviews in Analytical Chemistry, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 24

Published: April 9, 2025

Volatile organic solvents and fluoride-containing ionic liquids (ILs) have few drawbacks like toxicity, non-biodegradability, environmental issues. Even though ILs are considered as new safest solvent for their lower volatility. They pose toxicity sustainability concerns. Deep eutectic (DESs) garnered significant attention substitutes these solvents, addressing aligning with specific principles of green chemistry, such reduced biodegradability, the use renewable resources. This review thoroughly explains emergence inception DESs through development. It deals physicochemical properties density, polarity, viscosity. The factors dealing variation in density viscosity DES been discussed. preparation operation DESs, encompassing various variants hydrophobic hydrophilic types examined to provide a comprehensive grasp chemical properties. Beyond basic characteristics, article delves into applications demonstrate flexibility. show promising multifarious utility, ranging from acting extractant critical roles sorbent-based extractions, solvent-based role analytical techniques. covers opportunities difficulties associated offering prospective viewpoint on future advancements difficulties. outlines different facets research, emphasizing level knowledge at moment potential influence emerging subject DESs.

Language: Английский

Citations

0
Recent Developments in Deep Eutectic Solvents Applications in Liquid Chromatography: 2019–2025 DOI Creative Commons
Derya Dilek Demir, Joanna Antos, František Švec

et al.

Journal of Separation Science, Journal Year: 2025, Volume and Issue: 48(5)

Published: May 1, 2025

ABSTRACT Deep eutectic solvents (DES) are used as mobile phase and stationary modifiers, or for the itself thin layer/liquid/supercritical chromatography. Their specific properties can improve separation selectivity, reduce peak tailing, shorten time. In terms of environmental impact, advantages DES based on their biodegradability, recyclability, stability in mechanical/chemical/thermal properties. The disadvantages related to higher viscosity degradation aqueous solutions. This review focuses works that have been published since 2019, year excellent comprehensive by Cai Qiu was printed. Selected parameters discussed should be considered when preferred over commonly phases due green chemistry trends, while taking into account limitations modern LC separations. also centres critical aspects applications field liquid supercritical fluid chromatographic

Language: Английский

Citations

0