journal article·2026-08

Machine learning prediction of CO₂ solubility in deep eutectic solvent-MDEA mixtures

Amir Hossein Sheikhshoaei, Ali Sanati

Carbon Letters· Volume 36· Issue 4
Publisher page

Abstract

No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.

Source: Not provided · Quality: missing

Research context

OpenAlex topics: Ionic liquids properties and applications · Phase Equilibria and Thermodynamics · Carbon Dioxide Capture Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (43)

Show source-provided references
1. Heydari P et al (2020) Experimental investigation of improved graphene oxide as an efficient catalyst for the sustainable chemical fixation of CO2 with epoxides. J Environ Chem Eng 8(6):10456810.1016/j.jece.2020.104568 ↗
2. Dara A, Jafarbiglookarami A, Hafizi A (2022) Carbon-Based Materials for Carbon Capture and Storage, in Handbook of Energy Materials, Gupta R ( Eds) Springer Nature Singapore: Singapore. pp 1–3810.1007/978-981-16-4480-1_46-1 ↗
3. Hafizi A, Rajabzadeh M, Khalifeh R (2020) Enhanced CO2 absorption and desorption efficiency using DETA functionalized nanomagnetite/water nano-fluid. J Environ Chem Eng 8(4):10384510.1016/j.jece.2020.103845 ↗
4. Ren H et al (2018) Exploiting the hydrophilic role of natural deep eutectic solvents for greening CO2 capture. J Clean Prod 193:802–81010.1016/j.jclepro.2018.05.051 ↗
5. Wang F et al (2018) Current status and challenges of the ammonia escape inhibition technologies in ammonia-based CO2 capture process. Appl Energy 230:734–74910.1016/j.apenergy.2018.08.116 ↗
6. Zhao F et al (2023) An overview on the corrosion mechanisms and inhibition techniques for amine-based post-combustion carbon capture process. Sep Purif Technol 304:12209110.1016/j.seppur.2022.122091 ↗
7. Smith EL, Abbott AP, Ryder KS (2014) Deep eutectic solvents (DESs) and their applications. Chem Rev 114(21):11060–1108210.1021/cr300162p ↗
8. Hansen BB et al (2021) Deep eutectic solvents: A review of fundamentals and applications. Chem Rev 121(3):1232–128510.1021/acs.chemrev.0c00385 ↗
9. Sanati A et al (2022) Surface energy and wetting behavior of dolomite in the presence of carboxylic acid-based deep eutectic solvents. Langmuir 38(50):15622–1563110.1021/acs.langmuir.2c02312 ↗
10. Abbott AP et al (2003) Novel solvent properties of choline chloride/urea mixtures. Chem Commun, (1):70–7110.1039/b210714g ↗
11. Clarke CJ et al (2018) Green and Sustainable Solvents in Chemical Processes. Chem Rev 118(2):747–80010.1021/acs.chemrev.7b00571 ↗
12. Luo F et al (2021) Comprehensive evaluation of a deep eutectic solvent based CO2 capture process through experiment and simulation. ACS Sustain Chem Eng 9(30):10250–1026510.1021/acssuschemeng.1c02722 ↗
13. Rabhi F, Mutelet F, Sifaoui H (2020) Solubility of carbon dioxide in carboxylic acid-based deep eutectic solvents. J Chem Eng Data 66(1):702–71110.1021/acs.jced.0c00844 ↗
14. Dashti A et al (2021) Insight into the estimation of equilibrium CO2 absorption by Deep Eutectic Solvents using computational approaches. Sep Sci Technol 56(14):2351–236810.1080/01496395.2020.1828460 ↗
15. Wang J et al (2021) Prediction of CO2 solubility in deep eutectic solvents using random forest model based on COSMO-RS-derived descriptors. Green Chem Eng 2(4):431–44010.1016/j.gce.2021.08.002 ↗
16. Lemaoui T et al (2023) Predicting the CO2 Capture Capability of Deep Eutectic Solvents and Screening over 1000 of their Combinations Using Machine Learning. ACS Sustain Chem Eng 11(26):9564–958010.1021/acssuschemeng.3c00415 ↗
17. Hu D et al (2025) Quantum Chemistry-Guided Machine Learning for Accelerated Design of CO2-Solubilizing Deep Eutectic Solvents. ACS Sustain Chem Eng 13(25):9705–971810.1021/acssuschemeng.5c02555 ↗
18. Wang Z et al (2022) Synthesis of TBAB-based Deep Eutectic Solvents as the Catalyst in the Coupling Reaction between CO2 and Epoxides under Ambient Temperature. ChemistrySelect 7(36):e20220209110.1002/slct.202202091 ↗
19. Fan J et al (2024) Deep eutectic solvent+ water system in carbon dioxide absorption. Molecules 29(15):357910.3390/molecules29153579 ↗
20. Niktab Y, Haghtalab A (2025) CO2 solubility in tetrabutyl ammonium bromide (TBAB) and ethylene glycol deep eutectic solvents in the presence of N-methyl diethanolamine (MDEA): experimental study and thermodynamic modeling. J Mol Liq 430:12783410.1016/j.molliq.2025.127834 ↗
21. Friedman JH (2001) Greedy function approximation: a gradient boosting machine. Ann Stat. https://doi.org/10.1214/aos/101320345110.1214/aos/1013203451 ↗
22. Awad M, Khanna R (2015) Efficient learning machines: theories, concepts, and applications for engineers and system designers. Apress10.1007/978-1-4302-5990-9 ↗
23. Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2(5):359–36610.1016/0893-6080(89)90020-8 ↗
24. Williams CK, Rasmussen CE (2006) Gaussian processes for machine learning, Vol 2. MIT press, Cambridge, MA10.7551/mitpress/3206.001.0001 ↗
25. Popescu M-C et al (2009) Multilayer perceptron and neural networks. WSEAS Trans Circuits Syst 8(7):579–588
26. Tang J, Deng C, Huang G-B (2015) Extreme learning machine for multilayer perceptron. IEEE Trans neural networks Learn Syst 27(4):809–82110.1109/TNNLS.2015.2424995 ↗
27. Taud H, Mas J-F (2017) Multilayer perceptron (MLP). Geomatic approaches for modeling land change scenarios. Springer, pp 451–45510.1007/978-3-319-60801-3_27 ↗
28. Kumar R, Rai B, Samui P (2023) Machine learning techniques for prediction of failure loads and fracture characteristics of high and ultra-high strength concrete beams. Innov Infrastruct Solut 8(8):21910.1007/s41062-023-01191-w ↗
29. Elith J, Leathwick JR, Hastie T (2008) A working guide to boosted regression trees. J Anim Ecol 77(4):802–81310.1111/j.1365-2656.2008.01390.x ↗
30. James G (2013) An introduction to statistical learning, vol 112. Springer10.1007/978-1-4614-7138-7 ↗
31. Sheikhshoaei AH, Khoshsima A, Zabihzadeh D (2025) Predicting the heat capacity of strontium-praseodymium oxysilicate SrPr4(SiO4)3O using machine learning, deep learning, and hybrid models. Chem Thermodyn Therm Anal 17:10015410.1016/j.ctta.2024.100154 ↗
32. Rasmussen CE (2003) Gaussian processes in machine learning. Summer school on machine learning. Springer, pp 63–7110.1007/978-3-540-28650-9_4 ↗
33. Grbić R, Kurtagić D, Slišković D (2013) Stream water temperature prediction based on Gaussian process regression. Expert Syst Appl 40(18):7407–741410.1016/j.eswa.2013.06.077 ↗
34. Quinonero-Candela J, Rasmussen CE (2005) A unifying view of sparse approximate Gaussian process regression. J Mach Learn Res 6(Dec):1939–1959
35. Sheikhshoaei AH, Sanati A (2025) New insight into viscosity prediction of imidazolium-based ionic liquids and their mixtures with machine learning models. Sci Rep 15(1):2267210.1038/s41598-025-08947-7 ↗
36. Freund Y, Schapire RE (1997) A decision-theoretic generalization of on-line learning and an application to boosting. J Comput Syst Sci 55(1):119–13910.1006/jcss.1997.1504 ↗
37. Obaid RJ et al (2022) Novel and accurate mathematical simulation of various models for accurate prediction of surface tension parameters through ionic liquids. Arab J Chem 15(11):10422810.1016/j.arabjc.2022.104228 ↗
38. Amar MN et al (2019) Modeling oil-brine interfacial tension at high pressure and high salinity conditions. J Pet Sci Eng 183:10641310.1016/j.petrol.2019.106413 ↗
39. Gramatica P (2007) Principles of QSAR models validation: internal and external. QSAR Comb Sci 26(5):694–70110.1002/qsar.200610151 ↗
40. Rousseeuw PJ, Leroy AM (2003) Robust regression and outlier detection. John wiley & sons
41. Sheikhshoaei AH, Khoshsima A (2025) Machine and deep learning models for predicting high pressure density of heterocyclic thiophenic compounds based on critical properties. Scientific Reports 15(1):2546510.1038/s41598-025-09600-z ↗
42. Sheikhshoaei AH, Sanati A, Khoshsima A (2025) Deep learning models to predict CO2 solubility in imidazolium-based ionic liquids. Sci Rep 15(1):2644510.1038/s41598-025-12004-8 ↗
43. Hansen BB et al (2020) Deep eutectic solvents: a review of fundamentals and applications. Chemical reviews 121(3):1232–128510.1021/acs.chemrev.0c00385 ↗