{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,12]],"date-time":"2026-10-12T13:45:15Z","timestamp":1791812715336,"version":"4.3.4"},"reference-count":52,"publisher":"American Chemical Society (ACS)","issue":"19","license":[{"start":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T00:00:00Z","timestamp":1790640000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100014180","name":"Junta de Castilla y Le?n","doi-asserted-by":"publisher","award":["PhD fellowship"],"award-info":[{"award-number":["PhD fellowship"]}],"id":[{"id":"10.13039\/501100014180","id-type":"DOI","asserted-by":"publisher"}]},{"name":"P&G"},{"name":"Fondo Social Europeo +"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Surfactant mixtures exhibit non-ideal interactions that govern their macroscopic behavior, yet their prediction is limited by the need for experimentally derived interaction parameters. Within Rubingh\u2019s Regular Solution Approximation (RST), these interactions are described by the parameter \u03b2, which is typically obtained by fitting experimental mixture data, restricting its applicability in large-scale formulation design. In this work, a computational hybrid approach combining machine learning with thermodynamic modeling is introduced to enable end-to-end prediction and optimization of surfactant mixtures. A dataset of interaction parameters derived from experimental binary surfactant mixtures was constructed to train predictive models for \u03b2, together with models for pure-component properties. The predicted, composition-dependent \u03b2 values are incorporated into the RST framework to estimate mixture behavior without requiring experimental mixture data, while treating the resulting activity coefficients as effective quantities. The overall framework was further validated against a comprehensive dataset of binary surfactant mixtures and further evaluated on ternary systems, showing good agreement with experimental values across diverse interaction regimes and compositions. In addition, a multi-objective optimization strategy is introduced to identify formulations that balance performance and molecular complexity, enabling efficient exploration of chemical space. A case study on representative systems further demonstrates the applicability of the framework for computational formulation design. Overall, the proposed approach provides a scalable computational tool for surfactant mixture design, reducing reliance on experimental parameterization while enabling rapid virtual screening of formulation space.<\/jats:p>","DOI":"10.1021\/acs.jcim.6c02030","type":"journal-article","created":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T12:06:58Z","timestamp":1790683618000},"page":"12463-12476","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Synergistic and Antagonistic Micellization\nEffects in Surfactant Blends for Optimized Formulation Design"],"prefix":"10.1021","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-2659-1456","authenticated-orcid":true,"given":"Sofi\u0301a","family":"Gonza\u0301lez-Nu\u0301n\u0303ez","sequence":"first","affiliation":[{"name":"Universidad de Salamanca , , Pza. Cai\u0301dos 1-5 , ,","place":["Salamanca, Spain, 37008"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Amador","sequence":"additional","affiliation":[{"name":"Newcastle Innovative Centre, Procter and Gamble , Whitley Rd, Longbenton, Newcastle Upon Tyne, Tyne And Wear , ,","place":["Newcastle upon Tyne, England, NE12 9SR"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8554-4813","authenticated-orcid":true,"given":"Mariano","family":"Marti\u0301n","sequence":"additional","affiliation":[{"name":"Universidad de Salamanca , , Pza. 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Surfactants Deterg."},{"issue":"3","key":"2026101208081229200_cit6","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1002\/jsde.12230","article-title":"Methyl Ester Sulfonate: A High-performance\nSurfactant Capable of Reducing Builders Dosage in Detergents","volume":"22","author":"Lim","year":"2019","journal-title":"J. Surfactants Deterg."},{"issue":"6","key":"2026101208081229200_cit7","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1080\/17460441.2023.2211801","article-title":"Promising Strategies\nfor Improving Oral Bioavailability of Poor Water-Soluble Drugs","volume":"18","author":"Rocha","year":"2023","journal-title":"Expert Opin. Drug Discovery"},{"key":"2026101208081229200_cit8","doi-asserted-by":"publisher","first-page":"670","DOI":"10.1016\/j.cis.2014.10.001","article-title":"Current Applications\nof Foams Formed from Mixed Surfactant\u2013Polymer Solutions","volume":"222","author":"Bureiko","year":"2015","journal-title":"Adv. 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Surfactants Deterg."},{"issue":"31","key":"2026101208081229200_cit29","doi-asserted-by":"publisher","first-page":"20746","DOI":"10.1021\/acs.langmuir.5c02224","article-title":"Surface Activity, Aggregation Behavior,\nand Wettability of a Mixture\nof Perfluorinated Branched Short Chain Sulfonate Surfactants and Hydrocarbon\nCationic Surfactants in Dilute Solutions","volume":"41","author":"Li","year":"2025","journal-title":"Langmuir"},{"key":"2026101208081229200_cit30","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1016\/j.jcis.2022.01.045","article-title":"Strong Synergistic\nInteractions in Zwitterionic\u2013Anionic Surfactant Mixtures at\nthe Air\u2013Water Interface and in Micelles: The Role of Steric\nand Electrostatic Interactions","volume":"613","author":"Ma","year":"2022","journal-title":"J. Colloid Interface\nSci."},{"key":"2026101208081229200_cit31","doi-asserted-by":"publisher","DOI":"10.1016\/j.molliq.2019.110882","article-title":"Isooctane-Based\nAnionic and Zwitterionic Surfactant: Synergistic Interaction of Mixed\nReverse Micelle and Solubilisation of Erythromycin","volume":"286","author":"Mohamad-Aziz","year":"2019","journal-title":"J. Mol. Liq."},{"issue":"1","key":"2026101208081229200_cit32","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-025-01112-2","article-title":"Predicting the Critical\nMicelle Concentration of Binary\nSurfactant Mixtures Using Machine Learning","volume":"17","author":"Choudhary","year":"2025","journal-title":"J. Cheminf."},{"key":"2026101208081229200_cit33","doi-asserted-by":"publisher","DOI":"10.1016\/j.colsurfa.2025.138427","article-title":"Predicting\nthe Surface Tension of Mixed Surfactant Systems through Theory and\nMachine Learning","volume":"727","author":"Qing","year":"2025","journal-title":"Colloids Surf., A"},{"key":"2026101208081229200_cit34","doi-asserted-by":"publisher","DOI":"10.1016\/j.compchemeng.2025.109085","article-title":"Predicting the Temperature-Dependent\nCMC of Surfactant Mixtures with Graph Neural Networks","volume":"198","author":"Brozos","year":"2025","journal-title":"Comput. Chem. 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Colloid Interface Sci."},{"key":"2026101208081229200_cit51","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1016\/j.jiec.2022.12.057","article-title":"Interaction and\nMicellar Behavior of Ternary Mixture\nof Amphoteric Amino Sulfonate Surfactant with Traditional Anionic\nand Nonionic Surfactants: Effect of Hydrophilicity","volume":"120","author":"Zhang","year":"2023","journal-title":"J. Ind. Eng. Chem."},{"issue":"2","key":"2026101208081229200_cit52","doi-asserted-by":"publisher","first-page":"560","DOI":"10.1021\/acs.iecr.6b03453","article-title":"Application and Analysis of Methods\nfor Selecting an\nOptimal Solution from the Pareto-Optimal Front Obtained by Multiobjective\nOptimization","volume":"56","author":"Wang","year":"2017","journal-title":"Ind. Eng. Chem. 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