Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling
Abstract
:1. Introduction
2. Results and Discussion
2.1. Solubility of Ferulic Acid in DESs and DES–Water Mixtures
2.2. Ferulic Acid Intermolecular Interactions in DES
2.3. Machine Learning Model
3. Materials and Methods
3.1. Materials
3.2. Preparation of the Calibration Curve
3.3. Preparation of the Samples and Solubility Measurements
3.4. Conformational Analysis
3.5. Solubility Dataset
3.6. Machine Learning Protocol
3.7. Molecular Descriptors
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Jeliński, T.; Przybyłek, M.; Różalski, R.; Romanek, K.; Wielewski, D.; Cysewski, P. Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling. Molecules 2024, 29, 3841. https://doi.org/10.3390/molecules29163841
Jeliński T, Przybyłek M, Różalski R, Romanek K, Wielewski D, Cysewski P. Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling. Molecules. 2024; 29(16):3841. https://doi.org/10.3390/molecules29163841
Chicago/Turabian StyleJeliński, Tomasz, Maciej Przybyłek, Rafał Różalski, Karolina Romanek, Daniel Wielewski, and Piotr Cysewski. 2024. "Tuning Ferulic Acid Solubility in Choline-Chloride- and Betaine-Based Deep Eutectic Solvents: Experimental Determination and Machine Learning Modeling" Molecules 29, no. 16: 3841. https://doi.org/10.3390/molecules29163841