Deciphering pH Behavior in Deep Eutectic Solvents: Synergizing Experimental Data and Computational Modeling
13 affiliations
- 1CASCAT GmbH Straubing Germany
- 2Technical University of Munich Straubing Germany
- 3Departamento De Química Orgánica Universidad De Sevilla y Centro De Innovación en Química Avanzada (ORFEO‐CIN) Sevilla Spain
- 4Institute of Technical Chemistry Leibniz University Hannover Hannover Germany
- 5Department of Chemistry in Pharmaceutical Sciences Complutense University of Madrid (UCM) Madrid Spain
- 6Faculty of Food Technology and Biotechnology University of Zagreb Zagreb Croatia
- 7Chair of Chemistry of Biogenic Resources Technical University of Munich TUM Campus Straubing for Biotechnology and Sustainability Straubing Germany
- 8School of Chemistry and Molecular Biosciences The University of Queensland St. Lucia Australia
- 9SynBioFoundry@TUM, Technical University of Munich Straubing Germany
- 10TUM Catalysis Research Center Ernst‐Otto‐Fischer‐Straβe1 Garching Germany
- 11Sustainable Momentum, SL Las Palmas de Gran Canaria Spain
- 12CICECO−Aveiro Institute of Materials Department of Chemistry University of Aveiro Aveiro Portugal
- 13Biocatalysis and Bioprocessing Group Department of Biological and Chemical Engineering Aarhus University Aarhus Denmark
Abstract
The expanding application of deep eutectic solvents (DESs) in both upstream and downstream processes has brought increasing attention to the role of pH in these systems. Despite its importance, accurate pH determination in DESs remains a significant challenge, mainly due to the lack of standardized measurement protocols. This has resulted in limited and sometimes contradictory data in literature. In this study, we investigate the acid–base properties of representative DESs using two complementary techniques: pH electrode measurements and UV–vis spectrophotometry with pH‐sensitive indicators. The DESs examined include hydrophilic systems based on choline chloride, betaine, and tetrabutylammonium chloride combined with glycerol or ethylene glycol, as well as a hydrophobic lidocaine‐oleic acid system. Indicator solutions were titrated with hydrochloric acid, while absorbance and electrode pH values were recorded across each dye's transition range. The resulting absorbance–pH curves were fitted using an inverse Boltzmann model, showing excellent correlation ( R 2 > 0.99) and enabling reliable interpolation. Additionally, Gaussian process (GP)‐based machine learning (ML) confirmed strong agreement between methods within a 95% confidence interval. This integrated approach provides a robust framework for accurate pH assessment in DESs.
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BibTeX
@article{puglisi2026deciphering,
title = {{Deciphering pH Behavior in Deep Eutectic Solvents: Synergizing Experimental Data and Computational Modeling}},
author = {Andrea Puglisi and Chiara Falcini and Francesco Napoletano and D. Alonzo Durante-Salmerón and Marina Cvjetko Bubalo and Gonzalo Gonzalo and Volker Sieber and André Pick and Andrés R. Alcántara and Pablo Domı́nguez de Marı́a and Dinis O. Abranches and João A. P. Coutinho and Selin Kara},
journal = {ChemCatChem},
year = {2026},
month = jun,
doi = {10.1002/cctc.70846},
url = {https://doi.org/10.1002/cctc.70846},
note = {CC BY},
}
RIS
TY - JOUR
TI - Deciphering pH Behavior in Deep Eutectic Solvents: Synergizing Experimental Data and Computational Modeling
AU - Andrea Puglisi
AU - Chiara Falcini
AU - Francesco Napoletano
AU - D. Alonzo Durante-Salmerón
AU - Marina Cvjetko Bubalo
AU - Gonzalo Gonzalo
AU - Volker Sieber
AU - André Pick
AU - Andrés R. Alcántara
AU - Pablo Domı́nguez de Marı́a
AU - Dinis O. Abranches
AU - João A. P. Coutinho
AU - Selin Kara
PY - 2026
DA - 2026/06/01
JO - ChemCatChem
DO - 10.1002/cctc.70846
UR - https://doi.org/10.1002/cctc.70846
AB - The expanding application of deep eutectic solvents (DESs) in both upstream and downstream processes has brought increasing attention to the role of pH in these systems. Despite its importance, accurate pH determination in DESs remains a significant challenge, mainly due to the lack of standardized measurement protocols. This has resulted in limited and sometimes contradictory data in literature. In this study, we investigate the acid–base properties of representative DESs using two complementary techniques: pH electrode measurements and UV–vis spectrophotometry with pH‐sensitive indicators. The DESs examined include hydrophilic systems based on choline chloride, betaine, and tetrabutylammonium chloride combined with glycerol or ethylene glycol, as well as a hydrophobic lidocaine‐oleic acid system. Indicator solutions were titrated with hydrochloric acid, while absorbance and electrode pH values were recorded across each dye's transition range. The resulting absorbance–pH curves were fitted using an inverse Boltzmann model, showing excellent correlation ( R 2 > 0.99) and enabling reliable interpolation. Additionally, Gaussian process (GP)‐based machine learning (ML) confirmed strong agreement between methods within a 95% confidence interval. This integrated approach provides a robust framework for accurate pH assessment in DESs.
SN - 1867-3880
SN - 1867-3899
ER -